chore: ✨ stash audio experiments

.gitignore

@@ -2,7 +2,4 @@ __pycache__
 *.py[cod]
 *.onnx
 wheels/
-node_modules/
+node_modules/
-compose.yaml
-comfy_mtb.wsb
-Dockerfile

CHANGELOG.md

@@ -1,402 +0,0 @@
-# Changelog
-
-This is an automated changelog based on the commits in this repository.
-
-Check the notes in the [releases](https://github.com/melMass/comfy_mtb/releases) for more information.
-## [main] - 2024-03-07
-
-### Bug Fixes
-
-- 🐛 font fallback ([9fccdee](https://github.com/melMass/comfy_mtb/commit/9fccdee82d721e88c64d2292c209fec869524dd2))
-- ✨ optional inputs of colored image ([cd32f26](https://github.com/melMass/comfy_mtb/commit/cd32f26b167088d6b489e43b260c187ea5e4d223)) by [@ScottNealon](https://github.com/ScottNealon) in [#147](https://github.com/melMass/comfy_mtb/pull/147)
-- 📝 adds a way to not load the imagefeed ([501c330](https://github.com/melMass/comfy_mtb/commit/501c3301056b2851555cccd75ab3ff15b1ab8e0c))
-- 🐛 colored image mask input ([30c4311](https://github.com/melMass/comfy_mtb/commit/30c4311b69f6481a34f968cb67a9b5ce5d2e9fda))
-- 🐛 handle font cache errors ([c43a661](https://github.com/melMass/comfy_mtb/commit/c43a661ba31dcd7720b4f32d8e96760e6191fbd9))
-- 💄 register the COLOR type even for external extensions ([12b134a](https://github.com/melMass/comfy_mtb/commit/12b134ab4c937c192aaf4a3667d9885dd4fe43ca))
-- ✨ mask crop output ([59a361a](https://github.com/melMass/comfy_mtb/commit/59a361af5870b8ffc984c6680dd3282d3553dcf9))
-- 🚑️ thread font loading ([e4da832](https://github.com/melMass/comfy_mtb/commit/e4da832b99bd640b72c31b67178a3168e3238fa0))
-- 📦 changed way of creating bbox from mask ([14ee9e2](https://github.com/melMass/comfy_mtb/commit/14ee9e23c009ab55fa3b2fc6ec60fb683c46d57d)) by [@Yurchikian](https://github.com/Yurchikian) in [#124](https://github.com/melMass/comfy_mtb/pull/124)
-- ✨ expose invert of bboxfrommask ([53cb503](https://github.com/melMass/comfy_mtb/commit/53cb503866da6d83b47eaeb8073039ace2ae0a95))
-- ✨ less strict csv parsing ([d5c4c5f](https://github.com/melMass/comfy_mtb/commit/d5c4c5f2649ecdb4bf7b517c5b33bbf8df753047))
-- 🐛 fit number regression ([c8658df](https://github.com/melMass/comfy_mtb/commit/c8658dfbdd3a0ca8c3e88cd1adfddc55c7444045))
-- 🐛 remove uneeded installs ([4e07450](https://github.com/melMass/comfy_mtb/commit/4e07450bcabb0105b5610e52f7d4692ea07f9c1d))
-- 🐛 import issue ([255ac03](https://github.com/melMass/comfy_mtb/commit/255ac036bab1d776301857843d0e7a85e9a9dcb8))
-- 🐛 wrong output for bbox ([8d12b59](https://github.com/melMass/comfy_mtb/commit/8d12b59844958fbc696d01d51162f97262664ae9))
-- 🚑️ fallback when symlink detection fails ([278f22c](https://github.com/melMass/comfy_mtb/commit/278f22c2093b6eca63d2d00f7936774918707e4e))
-- ✨ handle malformed styles.csv ([e6f6502](https://github.com/melMass/comfy_mtb/commit/e6f65026735770df8aced4a3acb75550ff1c84da))
-- 🐛 encoding ([5af2840](https://github.com/melMass/comfy_mtb/commit/5af284067c65042bcdfff04a5d5a2360bf9e4af7))
-- ⚡️ add the cli deps ([bb90e04](https://github.com/melMass/comfy_mtb/commit/bb90e0415f6a1ececbf468815dc0f5959d9a34e8))
-- 🚑️ check for symlink ([25b933c](https://github.com/melMass/comfy_mtb/commit/25b933c698b250a411549d2600fae49bec225b7a))
-- 🚑️ remove problematic dependencies ([5dfea51](https://github.com/melMass/comfy_mtb/commit/5dfea51dd8db2a4829e559eadeda22374b51c8a4))
-- 🐛 batch support ([f1ff9fc](https://github.com/melMass/comfy_mtb/commit/f1ff9fc7c4684ad673c3178df3b8142dcf0b16ac))
-- 🐛 automatically disable tiling if seamless is on ([4605f74](https://github.com/melMass/comfy_mtb/commit/4605f74f370d4d221ab1d50f21b72910fa6909c7))
-- 🐛 debug node ([dc500b7](https://github.com/melMass/comfy_mtb/commit/dc500b788e885205f017956da6a71a677f822941))
-- ⚡️ hack to handle prompt validation ([d49b257](https://github.com/melMass/comfy_mtb/commit/d49b2578c247dcba9b09b374d99f5cc45cac172d))
-- ✨ deepbump update ([87b245c](https://github.com/melMass/comfy_mtb/commit/87b245c6a6895490e3612b235879fa90b62dea2b))
-- 👷 user folder_paths to retrieve comfy root ([38df58a](https://github.com/melMass/comfy_mtb/commit/38df58a78c363ef2657011893d4d811676b1c664))
-- 🐛 typo ([90aee83](https://github.com/melMass/comfy_mtb/commit/90aee83797a863cf4797cdbe187f949061cbd176))
-- 🐛 do not resolve symlink for "here" ([a50b11b](https://github.com/melMass/comfy_mtb/commit/a50b11bdaa66f4e805811b1676c937ade11318c2))
-- ✏️ use Union to allow support for <3.10 ([88a2779](https://github.com/melMass/comfy_mtb/commit/88a277968745ac990406b14d300a8ada9c575b11)) by [@M1kep](https://github.com/M1kep) in [#91](https://github.com/melMass/comfy_mtb/pull/91)
-- ⚡️ simplify widgets cleanup ([cdd098e](https://github.com/melMass/comfy_mtb/commit/cdd098e10258401402b8023c9143532cfa4a1745))
-- ✨ don't assume the install was ran ([cc43654](https://github.com/melMass/comfy_mtb/commit/cc43654af2987bc8860557caa99cde91e8309b21))
-- 🐛 install ([616b2bf](https://github.com/melMass/comfy_mtb/commit/616b2bfc6c629cef1d30cb0d717bd805c3a086aa))
-- 🐛 properly escape paths ([22cac9b](https://github.com/melMass/comfy_mtb/commit/22cac9b2d95910197941b73e7548735470bd3b17))
-- 🐛 use relative paths in JS ([e2773ff](https://github.com/melMass/comfy_mtb/commit/e2773ff22e43e7756ad618344a03d661a576cf35))
-- 💄 BatchFromHistory when "listening" ([3b07984](https://github.com/melMass/comfy_mtb/commit/3b07984716402fbbf5da41020bf73befd52e7ebf))
-- ✨ save gif widget removal ([fe8f519](https://github.com/melMass/comfy_mtb/commit/fe8f519f8860b0610d8cafcd9b843b4171c2b3d4))
-
-### Documentation
-
-- 📝 add changelog ([0d817bf](https://github.com/melMass/comfy_mtb/commit/0d817bf326b4a22e2221264a414af50c3b7048b9))
-- 📄 add note+ screenshot ([90d9636](https://github.com/melMass/comfy_mtb/commit/90d96366c8b7637b55d1b4f88cb9aca217c1414b))
-- 📝 add cover image ([6b993b8](https://github.com/melMass/comfy_mtb/commit/6b993b84071bbb80ba1b8bd63576f31e35d05590))
-- 📝 fix image size ([3e8c2fe](https://github.com/melMass/comfy_mtb/commit/3e8c2fe789925e7017c2f8c8d9164c139588aba4))
-- 📝 add image ([3e93ea6](https://github.com/melMass/comfy_mtb/commit/3e93ea6f2c73353891b1a3f6223b5730bc69df37))
-- 📝 explain optional nodes ([cea0b08](https://github.com/melMass/comfy_mtb/commit/cea0b08eb044756ab1b408f630435095b8969d36))
-- 📝 add the example previews from the wiki ([8f90986](https://github.com/melMass/comfy_mtb/commit/8f909864bfaa9f2d0fbdcf3942eacb9d78ee8fb8))
-- 📝 update node list ([4917e31](https://github.com/melMass/comfy_mtb/commit/4917e31c427c74d28c830fd7b2423cab393ba0f8))
-- 📝 add some deprecation warnings and recommendations ([e11df9d](https://github.com/melMass/comfy_mtb/commit/e11df9d45c81d93f4334841de036b4aa3364375a))
-- 📝 add a reference to SlickComfy for colab ([bb35098](https://github.com/melMass/comfy_mtb/commit/bb35098c656b0b2d30909b83df0a3b65c5975f78))
-
-### Features
-
-- ✨ add "To Device" ([c28181f](https://github.com/melMass/comfy_mtb/commit/c28181f1615d2e183767aa76cc2350934330e546))
-- ✨ add note+ example ([90f3bc2](https://github.com/melMass/comfy_mtb/commit/90f3bc2d953b299ea34e9e3a925f1a824b488855))
-- 💄 node+ improvements ([4b29395](https://github.com/melMass/comfy_mtb/commit/4b29395000254382882c0d1be115b2ed80cd7c99))
-- 📝 add note plus ([605c8db](https://github.com/melMass/comfy_mtb/commit/605c8db320e1531c6347f6888606fa50d8eb268b))
-- 🚧 add playlist nodes ([cf96572](https://github.com/melMass/comfy_mtb/commit/cf965727e8e7064328704d88cd0410c61f1e686e))
-- 🚨 add missing node ([16c1a59](https://github.com/melMass/comfy_mtb/commit/16c1a59312b1d9841f5f8a814eff93a1ddf04edb))
-- ✨ Math Expression node ([142624e](https://github.com/melMass/comfy_mtb/commit/142624eea616a5622387b1b641c02605455ee6f1))
-- 🚀 add optional inputs to colored image ([049983d](https://github.com/melMass/comfy_mtb/commit/049983dbe2dbce6b772908468c4042d2bfde5eb2))
-- ✨ Add support for extra_model_paths.yaml ([d7b8ac8](https://github.com/melMass/comfy_mtb/commit/d7b8ac8e0c98b0d7a2e21889d35aad9f6b093560))
-- ✨ add batch shake ([af94203](https://github.com/melMass/comfy_mtb/commit/af94203d1b461d934ca1c44211ca0f71a5d05d48))
-- ✨ enhance concat images ([a798eb0](https://github.com/melMass/comfy_mtb/commit/a798eb07d0d891cfbd47013b442ef2fa3d7cc5bc))
-- 💄 add a few more batch nodes ([c1d42de](https://github.com/melMass/comfy_mtb/commit/c1d42de0fcde86d2a167fb4b5e781ee987814da2))
-- ✨ Batch node utilities ([cef5023](https://github.com/melMass/comfy_mtb/commit/cef5023efc17366a2e937ef43944de3587707fac))
-- 🚨 Image Stack node (horizontal and vertical stack) ([bb3277d](https://github.com/melMass/comfy_mtb/commit/bb3277d85f4ca21735cb1f5237cb1430db88c183))
-- 🚀 add seamless model hack ([21acc87](https://github.com/melMass/comfy_mtb/commit/21acc87ff0a84b7588f4b5aae0aeb5ae94bbbfbe))
-- 🔧 debug handle a few more types ([638498c](https://github.com/melMass/comfy_mtb/commit/638498c6b47c2b2cab82f76aec1f3d46df67f263))
-- 🎨 Add an editor for the styles loader ([2faa2f2](https://github.com/melMass/comfy_mtb/commit/2faa2f2a148a4dbf5525e4945f688a239f244546))
-- ✨ add a static assets path ([6a00d1d](https://github.com/melMass/comfy_mtb/commit/6a00d1da5a8a5fa47af1bf1ab5d3cd206c599841))
-- ✨ add  Interpolate Clip Sequential ([a71c273](https://github.com/melMass/comfy_mtb/commit/a71c273baf450ad7e2a7e032451f015d3be3e9e9))
-
-### Miscellaneous Tasks
-
-- 🧹 applied some linting ([fe49312](https://github.com/melMass/comfy_mtb/commit/fe49312cbef03c6540304448fa88aa7a88391efa))
-- 📝 header links not parsed ([514c0d2](https://github.com/melMass/comfy_mtb/commit/514c0d2eda9990435eb18258d4bbd1aa137feb3d))
-- 📝 hardcode links in changelog ([915b744](https://github.com/melMass/comfy_mtb/commit/915b7444a9db83f349d83b636304af0d276f529f))
-- 🔖 local updates ([6c5e5d3](https://github.com/melMass/comfy_mtb/commit/6c5e5d36379bdab223b4503e42b7956b55a82ab0))
-- 📝 update node list ([dd27f99](https://github.com/melMass/comfy_mtb/commit/dd27f990c72fa94aff205eb314a8ea360f57479e))
-- ✨ update node_list ([537a0d8](https://github.com/melMass/comfy_mtb/commit/537a0d8108d0caa3ab2daeafd1d25d680214ef26))
-- ✨ local stuff ([9afad1a](https://github.com/melMass/comfy_mtb/commit/9afad1a1680073006d946be10f8c97b75ddfe253))
-- 📝 fix update issue template ([da290db](https://github.com/melMass/comfy_mtb/commit/da290dbcf2952a56be9334f7bf9dc4d8fa64a21d))
-- 📝 update issue template ([b949bb4](https://github.com/melMass/comfy_mtb/commit/b949bb406bc1929634600465ea389eaedefe6e6f))
-
-### Refactor
-
-- ⚡️ small local fixes ([bcac665](https://github.com/melMass/comfy_mtb/commit/bcac66508d2e788cc437da289d1ccede19465b8c))
-- 🗑️ remove unused code in install script ([5b75436](https://github.com/melMass/comfy_mtb/commit/5b75436610c6312adf47c6baa3e9fe9cc7d56dcf))
-
-### Merge
-
-- 🔀 pull request #109 from melMass/dev/0.2.0 ([87e301d](https://github.com/melMass/comfy_mtb/commit/87e301d120a542d5aabe544bec10d38dbd19b2f6)) in [#109](https://github.com/melMass/comfy_mtb/pull/109)
-- 🔀 pull request #86 from melMass/feature/styles-editor ([cbdb816](https://github.com/melMass/comfy_mtb/commit/cbdb816164900061ddaa1671f4287763d0b79ee1)) in [#86](https://github.com/melMass/comfy_mtb/pull/86)
-
-### Wip
-
-- 🚧 add text template node ([af2175a](https://github.com/melMass/comfy_mtb/commit/af2175a1fc0c2fb29ef3493f242fe45ec6fcabac))
-
-## New Contributors
-* [@ScottNealon](https://github.com/ScottNealon) made their first contribution in [#147](https://github.com/melMass/comfy_mtb/pull/147)
-* [@Yurchikian](https://github.com/Yurchikian) made their first contribution in [#124](https://github.com/melMass/comfy_mtb/pull/124)
-* [@M1kep](https://github.com/M1kep) made their first contribution in [#91](https://github.com/melMass/comfy_mtb/pull/91)
-## [0.1.4] - 2023-08-12
-
-### Bug Fixes
-
-- 🚀 pending fixes ([ea5d73d](https://github.com/melMass/comfy_mtb/commit/ea5d73d48cfa4046f48a52609cff7f754d8364ed))
-- 🚑️ image resize infinite loop ([30d6cfe](https://github.com/melMass/comfy_mtb/commit/30d6cfe81292d0f7702544b3c2cbad1820c4a926))
-- ✨ update example files ([610afe0](https://github.com/melMass/comfy_mtb/commit/610afe031f21d737b2fd5128e4be7100b6666181))
-- 🐛 simplify install steps ([4fc84d6](https://github.com/melMass/comfy_mtb/commit/4fc84d615dd0f546442c3537f00c52366db4ca9b))
-- ✨ refactor ([8523392](https://github.com/melMass/comfy_mtb/commit/8523392df74c586dc940841ddbb5069943b16f7d))
-- 🐛 debug rgba ([40560f8](https://github.com/melMass/comfy_mtb/commit/40560f8154d3ddeabf708be4d111370648d466ac))
-- 🎨 rename fun to generate ([e7f72f9](https://github.com/melMass/comfy_mtb/commit/e7f72f9825da58254e3084b4ba91f76e6cf2cf5f))
-- ✨ refactor existing ([1144466](https://github.com/melMass/comfy_mtb/commit/11444662b9198861b62aff06a08b9c9ea01dd8bd))
-- ⚡️ move getbatchfromhistory to graphutils ([2eccba4](https://github.com/melMass/comfy_mtb/commit/2eccba4e33b21d1d080cb2f415f76a93488120f0))
-- 🚧 wip dependency installer UI ([630b492](https://github.com/melMass/comfy_mtb/commit/630b492347f75d7308b31a000061b41d7dfa4a10))
-- 🐛 image feed zorder ([0fb2d4d](https://github.com/melMass/comfy_mtb/commit/0fb2d4da90a7e65f82b3f9c8942a68e360456cf7))
-- ⬇️ download_antelopev2 ([4dd5321](https://github.com/melMass/comfy_mtb/commit/4dd532185223a1fa5978446e7bb75d32d77ebdb5))
-- 🚑️ frontend pushed too early ([91f60d4](https://github.com/melMass/comfy_mtb/commit/91f60d4c463c474ac10e868e8e73e13fa019856b))
-- 🚑️ missing input ([84ac8ac](https://github.com/melMass/comfy_mtb/commit/84ac8ac852aeb962029bfd8369fe5ed59a203977))
-- 🐛 shell command bug ([3d5075f](https://github.com/melMass/comfy_mtb/commit/3d5075fea2e219a179271c9810017c7e38bff6cc))
-- 🚑️ remove pipe mode from the install.py ([b854a30](https://github.com/melMass/comfy_mtb/commit/b854a302ce4708d2ad2dac249860308dbdcae5a6))
-- ⚡️ colab install ([36d8e6b](https://github.com/melMass/comfy_mtb/commit/36d8e6bdb06edab72ccfb686266d2e644a9f028c))
-- 🚑️ install typo ([ffa1a87](https://github.com/melMass/comfy_mtb/commit/ffa1a87b9184df5a3699a6118714b39d359bde4d))
-
-### Documentation
-
-- 📝 link the actual action instead of badge ([098d74a](https://github.com/melMass/comfy_mtb/commit/098d74a3cd8449d836569a074995e20d775c6728))
-- 📝 add action badge ([e74314b](https://github.com/melMass/comfy_mtb/commit/e74314b04eb218c140482ccf704b61af06db3f4d))
-
-### Features
-
-- 💫 export to prores -> export with ffmpeg ([a4d99d9](https://github.com/melMass/comfy_mtb/commit/a4d99d966b1207191243a9749385b998d1a9c6b1))
-- 🔥 add any to string & refactor ([dbdb872](https://github.com/melMass/comfy_mtb/commit/dbdb872b74e18c16feb44bd037abc3aafbb4700f))
-- ✨ add UI for interpolate clip sequential ([5ec5511](https://github.com/melMass/comfy_mtb/commit/5ec551143302b2a94ca82e477f684ecee23f1459))
-- ✨ add portable reqs ([3f14b16](https://github.com/melMass/comfy_mtb/commit/3f14b1676d28f5ffa1f47fda00b9bc244951045c))
-- ✨ add border extension ([fb64484](https://github.com/melMass/comfy_mtb/commit/fb644847ca434123e8e8e4991d33949fd31e3cbe))
-- ✨ use PIL for gif saving ([2bc7ae8](https://github.com/melMass/comfy_mtb/commit/2bc7ae88bf4cdfa575d11233c0e6f7b07f9dfd23))
-- 🎨 update node list ([a54d7d5](https://github.com/melMass/comfy_mtb/commit/a54d7d5346c272898dd4e67c65495de7325ab3a0))
-- ✨ install fix ([512de60](https://github.com/melMass/comfy_mtb/commit/512de6023e55f2cc47516bf44436efe22157273f)) in [#41](https://github.com/melMass/comfy_mtb/pull/41)
-
-### Miscellaneous Tasks
-
-- 💄 encoding ([49c64c7](https://github.com/melMass/comfy_mtb/commit/49c64c74eb3e99f456b563bbd79e3fe47a85c70d))
-- 🚀 only fetch controlnet_preprocessor deps ([414beb9](https://github.com/melMass/comfy_mtb/commit/414beb99a1f9bf719eca6ac139c9b2ccdfd6d743))
-- 🚀 add controlnetpreprocessors to tests ([63b3aec](https://github.com/melMass/comfy_mtb/commit/63b3aece2ba05adc2b655afeb41e3d47e7887b33))
-- ✨ remove unused input ([d4f791d](https://github.com/melMass/comfy_mtb/commit/d4f791d7a14ba9cb8abd7c95ba70b081fee5fb7c))
-- ✨ use the same cwd as manager ([2ff0467](https://github.com/melMass/comfy_mtb/commit/2ff04672daff773d52e1552dca1bf616bc32daa6))
-- 🎨 no brace glob ([bbfcb62](https://github.com/melMass/comfy_mtb/commit/bbfcb62c398de39058bcb6e18161425059d53e8e))
-- 🎨 extract txt ([a22fd01](https://github.com/melMass/comfy_mtb/commit/a22fd01d664276e4cd833ae1326feeece1d1deaf))
-- 🎨 also push wheels_order to releases ([8e5b776](https://github.com/melMass/comfy_mtb/commit/8e5b7765cc0c6730bd5517ccfd56e817ea39bd3a))
-- 🚧 more info for bug reports ([3dadc11](https://github.com/melMass/comfy_mtb/commit/3dadc119f44fca1029ec4b349d71ce99fb20a4b6))
-- ✨ individual wheels ([346ff64](https://github.com/melMass/comfy_mtb/commit/346ff649d50c9f0286ad2243938406fefb62853b))
-
-### Refactor
-
-- 🚧 tidy ([4f30829](https://github.com/melMass/comfy_mtb/commit/4f30829e06c41b3685644bfe7bece07e0bcfb70e))
-- ♻️ get batch from history ([13d255a](https://github.com/melMass/comfy_mtb/commit/13d255a730b08c4903647875350b9b3dcd61b4a6))
-
-### Revert
-
-- 💄 use BOOLEAN instead of BOOL ([cfb3b23](https://github.com/melMass/comfy_mtb/commit/cfb3b237cf64b512414a17f71e6d89c3355aa8ef))
-
-### Testing
-
-- 🧪 remove sha input ([c5bbe83](https://github.com/melMass/comfy_mtb/commit/c5bbe83008bb194cbd6ad5e3dc70cb3850b18985))
-- 🧪 ci for comfy embedded ([7b3afca](https://github.com/melMass/comfy_mtb/commit/7b3afca8179760e35e8a6fbf742080dee13e4fc7))
-
-### Merge
-
-- 🔀 pull request #50 from melMass/dev/august-refactor ([2ecd470](https://github.com/melMass/comfy_mtb/commit/2ecd4700d77c0727e6b5d2124e0a6ebd48ec96ed)) in [#50](https://github.com/melMass/comfy_mtb/pull/50)
-
-## [0.1.3] - 2023-07-29
-
-### Bug Fixes
-
-- 🔥 manage pip from install only, remove requirements.txt ([247fbfb](https://github.com/melMass/comfy_mtb/commit/247fbfbc216b8259d607e0699d5b990b6a06ca71)) in [#38](https://github.com/melMass/comfy_mtb/pull/38)
-- 🎨 use image ratio for imagefeed ([f5cd56c](https://github.com/melMass/comfy_mtb/commit/f5cd56ce861c8c0a931744ae6cf2b96e9c8bca06))
-
-### Documentation
-
-- 📝 update imagefeed preview ([cbcacbe](https://github.com/melMass/comfy_mtb/commit/cbcacbe3c92ebb5f74d046b83504c3723710f130))
-- 📝 fix typo and add more details ([7c020ba](https://github.com/melMass/comfy_mtb/commit/7c020bab288aa7d17dc937b5f102319d43c3ebb3))
-
-### Miscellaneous Tasks
-
-- ✨ use wheel order if present ([9b24edd](https://github.com/melMass/comfy_mtb/commit/9b24eddd9c51004af08d7ac6ff2b6473dd3ee161))
-- ✨ store order of install for wheels ([5053142](https://github.com/melMass/comfy_mtb/commit/505314294f02e7c19ac95e4d0ed37fd397a54b46))
-
-## [0.1.2] - 2023-07-28
-
-### Bug Fixes
-
-- ✨ various small things ([0e311cf](https://github.com/melMass/comfy_mtb/commit/0e311cf2c64cf2b4861d4cc612a3409390e3039a))
-- 📝 last release ([889f08c](https://github.com/melMass/comfy_mtb/commit/889f08c08b721be8fdb4e4d7eacc47169d5692d6)) in [#36](https://github.com/melMass/comfy_mtb/pull/36)
-- 📝 narrow requirements ([5d661b2](https://github.com/melMass/comfy_mtb/commit/5d661b2509fecf3940c3c0fab25b16ec0eae7a2d))
-- ✨ Separate FaceAnalysis model loading ([d143e83](https://github.com/melMass/comfy_mtb/commit/d143e83dba3bffa16e1b98d7ad1e9cf92dc94db2))
-- ⚡️ update examples to match wiki ([3dfe98c](https://github.com/melMass/comfy_mtb/commit/3dfe98c7957df48723380de85e1242a424ec23de))
-
-### Documentation
-
-- 📝 add readme for web extensions features ([be162a2](https://github.com/melMass/comfy_mtb/commit/be162a20477258627fa0d742c97a478bd085ff4f))
-- 📝 link to the proper lang instructions ([232cf89](https://github.com/melMass/comfy_mtb/commit/232cf8966cc20291b60c68f487dfd37bf6aa4dfa)) in [#33](https://github.com/melMass/comfy_mtb/pull/33)
-- 📝 update readmes ([96a0618](https://github.com/melMass/comfy_mtb/commit/96a0618c5990a8559a9e2dd17c868d3465b8ca90))
-
-### Miscellaneous Tasks
-
-- 🎉 bump version ([9e751a2](https://github.com/melMass/comfy_mtb/commit/9e751a242f4e9afee3dc5c871c414b29b9706ff6))
-- 👷 remove stale example ([c237737](https://github.com/melMass/comfy_mtb/commit/c2377374201fc34b107c8b7db1cdeb2f483d1e18))
-- 🐛 fix size ([c0cc557](https://github.com/melMass/comfy_mtb/commit/c0cc5572d8c727568eca8a3d0f116a1f540c31ff))
-
-## [0.1.1] - 2023-07-24
-
-### Bug Fixes
-
-- 🎨 improve a bit the HTML response of endpoints ([50d51c7](https://github.com/melMass/comfy_mtb/commit/50d51c70d04e49e9df524975c171288c0fc0b20f))
-- 🐛 caching issues ([55c9736](https://github.com/melMass/comfy_mtb/commit/55c9736a9b2ca036926be4b06406121bfb9ebad2))
-- 🔥 remove notice ([abf1e82](https://github.com/melMass/comfy_mtb/commit/abf1e82adb9fac8cd70d5c409baad55309ef6fe1))
-- 🔥 use BOOL everywhere ([a393793](https://github.com/melMass/comfy_mtb/commit/a393793cfa93721eac46295723076a1dda940dcd))
-
-### Documentation
-
-- 📝 added lang links ([bbdac97](https://github.com/melMass/comfy_mtb/commit/bbdac97e49af4e90d22eeec3f63b96ecc126ffcf))
-- 📝 add comfyforum example ([10d0503](https://github.com/melMass/comfy_mtb/commit/10d05031b1791ab3534cf838be6eb75df638dfb6))
-
-### Features
-
-- 🚧 jupyter seems to require an __init__ there ([9a4eda3](https://github.com/melMass/comfy_mtb/commit/9a4eda3ef573bf382c13515f67ae8a415bf61abd))
-- ⚡️ use notify ([a2ecc11](https://github.com/melMass/comfy_mtb/commit/a2ecc11ebde79c2403959bf09c258f3a2465894a))
-- ✨ first version of Notify ([7e9c97e](https://github.com/melMass/comfy_mtb/commit/7e9c97ecb48672b25e5ed17b9b35dba9208ac311))
-- ⚡️ add an "actions" endpoint ([3de160a](https://github.com/melMass/comfy_mtb/commit/3de160af25b516c02aaa8cc32baec16e9ef358fb))
-- ✨ add Unsplash Image node ([8d3cc39](https://github.com/melMass/comfy_mtb/commit/8d3cc39b72dff1b5eb61bf7e2e395753c138ec8a))
-- ✨ add back Save Tensors ([7142b28](https://github.com/melMass/comfy_mtb/commit/7142b284adc7fba9a1bdafd1a52621bfc168bde1))
-- ✨ add TransformImage node ([11128ff](https://github.com/melMass/comfy_mtb/commit/11128ff85a7e0b4a54f405548969c2478da26df6))
-
-### Miscellaneous Tasks
-
-- 🚀 bump version ([cf86552](https://github.com/melMass/comfy_mtb/commit/cf865529ab64b350cd7af964b41160e7d130d12d))
-- 🚀 Remove large files from release ([3b9190a](https://github.com/melMass/comfy_mtb/commit/3b9190a69b002b8933c097fd6655bb4fe07264d2))
-
-### Refactor
-
-- ✨ cleaned up frontend code a bit ([3801a44](https://github.com/melMass/comfy_mtb/commit/3801a443bc1e89c70fdb35ce0b1724d86fa22928))
-- ⚡️ remove empty inits ([21729b2](https://github.com/melMass/comfy_mtb/commit/21729b2784a50fcaf24a63ac283bdae475a53ce7))
-
-### Merge
-
-- 🔀 pull request #32 from melMass/dev/next ([8695cd3](https://github.com/melMass/comfy_mtb/commit/8695cd3f1b6d27b5cd6c616ed1215ea2f25c5304)) in [#32](https://github.com/melMass/comfy_mtb/pull/32)
-
-## [0.1.0] - 2023-07-22
-
-### Bug Fixes
-
-- 🔥 properly match built wheels ([119b4d6](https://github.com/melMass/comfy_mtb/commit/119b4d6e16c2a90db1664ccaac748507feb73ea0)) in [#30](https://github.com/melMass/comfy_mtb/pull/30)
-- ✨ also try to copy web if symlink fails ([0df55de](https://github.com/melMass/comfy_mtb/commit/0df55def29fb992751010f6b8a707699f230ff37))
-- ✨ install process tested in comfy-manager (embed, colab) ([b40730d](https://github.com/melMass/comfy_mtb/commit/b40730ddbc3f8e3e7d5a17e9e9e4526ff37977fd))
-- 🚀 try to support remote install too ([3c66de2](https://github.com/melMass/comfy_mtb/commit/3c66de2500a89efd2d2e3af88fc58429af725789))
-- 💄 save gif issues ([7335003](https://github.com/melMass/comfy_mtb/commit/7335003346e83666c5dee631b8e6b15586d871e7))
-- 🚑️ always use latest for now ([fccf313](https://github.com/melMass/comfy_mtb/commit/fccf31348994ab6e344a1ab00a8f9998309f9319))
-- 🐛 install logic ([7e301e2](https://github.com/melMass/comfy_mtb/commit/7e301e2a067d41cba9b8ef357496dd1df94e4cdd))
-- 🎉 remove tests & add missing docs ([4e6b877](https://github.com/melMass/comfy_mtb/commit/4e6b87719989aa144946c5c9a43b9398c20bf11e))
-- ⚡️ update node_list ([c794d6a](https://github.com/melMass/comfy_mtb/commit/c794d6a071778220d654b526d2edfddcc79752fc))
-- 🚑️ set debug level from endpoint ([18402e3](https://github.com/melMass/comfy_mtb/commit/18402e3be1ab47e10109cfd2dff18863a1ee56f7))
-- 🐛 add base64 prefix to outputs ([0950f99](https://github.com/melMass/comfy_mtb/commit/0950f9914c9bbed7c89f3de33a967cb76f9d0bbb))
-- 🎨 refactor and add Gif preview on node ([c2e8379](https://github.com/melMass/comfy_mtb/commit/c2e83794faeb8da708c98908882e38b2a42827bd))
-- ✨ Various widgets issues ([27500ca](https://github.com/melMass/comfy_mtb/commit/27500ca432d686774b991045b7cffc58c0b67faf))
-- 🔥 deprecate some nodes and fix image list ([9aa934f](https://github.com/melMass/comfy_mtb/commit/9aa934f70ff6adf91efb26aa8e5cb21ec575196a))
-- 🐛 crop nodes ([67d3783](https://github.com/melMass/comfy_mtb/commit/67d3783ac9186da6bba4b7dc7e8dc3d5db5a1b0f))
-- 🐛 tensor2pil ([8a59508](https://github.com/melMass/comfy_mtb/commit/8a59508ff91d6b2d9ca287ef1c054ec5755337a4))
-- ⚡️ a few missing __doc__ ([ab09cca](https://github.com/melMass/comfy_mtb/commit/ab09ccadd905bebbf1b7b2d992e96e36fc60d68a))
-- ⚡️ from tensor2np always returning a list ([6168b3a](https://github.com/melMass/comfy_mtb/commit/6168b3a2ac38b5eebed3daf9e52df5742abf6813))
-- 🚑️ TF by default fills vram ([c225da5](https://github.com/melMass/comfy_mtb/commit/c225da5f298acb4cb2b39022382543c0c966d428))
-- ✨ leftovers ([da3e6f4](https://github.com/melMass/comfy_mtb/commit/da3e6f47c6073e73cf9d3a3cd23ba5ccbe1fedce))
-- ✨ handle non fork gdown in model dll ([95797e8](https://github.com/melMass/comfy_mtb/commit/95797e823e12e62ae8758753f60c34afbe19ec90))
-- ✨ properly add the submodules ([00510ed](https://github.com/melMass/comfy_mtb/commit/00510ed0b8583dd64518daa67d963582f4f029d3))
-- 📌 remove sad talker for now ([1622cbc](https://github.com/melMass/comfy_mtb/commit/1622cbcb9d51ddd0e1a8b4d87ba47b99327163eb))
-- 🎨 narrow requirements ([1a92ef7](https://github.com/melMass/comfy_mtb/commit/1a92ef734dd4271efc875856038f9e3b6b9ded6c))
-- 🚀 use the comfy util to handle graph interruption ([9752f3e](https://github.com/melMass/comfy_mtb/commit/9752f3e9dec9aa59cfa809aa14f0151594c03858))
-- 🔥 much faster (using GPU) on windows ([2f455aa](https://github.com/melMass/comfy_mtb/commit/2f455aaca55c0a044735c768b295d077b2f5b8d6))
-- 🐛 uint8 to uint16 ([be5a655](https://github.com/melMass/comfy_mtb/commit/be5a655cfaba1794f7b09c82d65de42e2b031720))
-- ✨ add missing requirements ([b779bc3](https://github.com/melMass/comfy_mtb/commit/b779bc39ac19f779aeb73c98b916671d1d16806f))
-- 📝 don't propagate base logs ([7fd99c2](https://github.com/melMass/comfy_mtb/commit/7fd99c25c4e50566def5c5166a9d9059b1febfa6))
-- 🐛 bg upscaler in gfpgan ([fee48ad](https://github.com/melMass/comfy_mtb/commit/fee48adff3d66960cb17836f3f4efbfd0c8740c4))
-- 📝 separate debug / info better ([e24863d](https://github.com/melMass/comfy_mtb/commit/e24863d1f9f63f367a2b392e6228ffa42927b71b))
-- 🔥 change log level of the base logger ([7538c2c](https://github.com/melMass/comfy_mtb/commit/7538c2c4bad8390a32226dc0a5a6ef978b00d201))
-- ✨ handle externs dynamicly ([6ef308a](https://github.com/melMass/comfy_mtb/commit/6ef308a87062c91e2d7249c05d96c6fb76e5a6c4))
-- 🐛 separate faceswap model load ([8e267c0](https://github.com/melMass/comfy_mtb/commit/8e267c0204ce5abe8e113fd401234d49f377646a))
-
-### Documentation
-
-- 📝 fold each comfy mode ([3c3c438](https://github.com/melMass/comfy_mtb/commit/3c3c4380bd1a3f0eed5216b835e076c26fce2f88))
-- 📝 add more description to examples ([46eab5c](https://github.com/melMass/comfy_mtb/commit/46eab5ca2f0e04d872d87c849b11551fd219bdb9))
-- 📝 add model notice ([cbe67ed](https://github.com/melMass/comfy_mtb/commit/cbe67edd4befb7260be01fa09af8448e5bcf5680))
-- 📝 add preview for examples ([b5176ca](https://github.com/melMass/comfy_mtb/commit/b5176ca0ee489ada52b6632f68b794b4f709d5ba))
-- 📝 add jp and cn (using deep translation) ([da559b9](https://github.com/melMass/comfy_mtb/commit/da559b9eaf135a49c0ab9bfa45573baf0c18dfb2))
-- 📝 update readme ([b0fb522](https://github.com/melMass/comfy_mtb/commit/b0fb5222cb19e4004533d3367863be5c9ce8e72b)) in [#15](https://github.com/melMass/comfy_mtb/pull/15)
-- 📝 update README.md ([f8dc768](https://github.com/melMass/comfy_mtb/commit/f8dc768635a2d21f6ff81b42c418724c432159bf))
-- 📝 updated instructions ([c3b9fd4](https://github.com/melMass/comfy_mtb/commit/c3b9fd4afedbb46748aef17b40e167a4cfad65f5))
-
-### Features
-
-- ✨ update install instructions ([7be37db](https://github.com/melMass/comfy_mtb/commit/7be37dbbfac45e8038f94ced8a2fa8ec2b06fb34))
-- 🚀 add install script ([dad3966](https://github.com/melMass/comfy_mtb/commit/dad3966ba219c1998e4fc7f6e641864fb0e7c3e8))
-- 🚧 add my CLIs ([44eaae5](https://github.com/melMass/comfy_mtb/commit/44eaae5c79f4dbec344053d945e7275be5c3c0a5))
-- ✨comfy_widget shared utils ([91bb95d](https://github.com/melMass/comfy_mtb/commit/91bb95da914468de533b040324700c7f9707e4fb))
-- 🚀 debug node ([b27b8ef](https://github.com/melMass/comfy_mtb/commit/b27b8ef91fe7335b1df3766547edaf4b9625ae4d))
-- ✨ add FitNumber node ([aa551eb](https://github.com/melMass/comfy_mtb/commit/aa551ebe57801c69010815119fe21e19a858780c))
-- 🔥 add API endpoints ([95afbdb](https://github.com/melMass/comfy_mtb/commit/95afbdbf76e66897e632252d876384ada9acf153))
-- ✨ categorize ([d2b3962](https://github.com/melMass/comfy_mtb/commit/d2b396236a10fe620ebebabd5a22c36159921913))
-- 🚀 add a few examples ([b9c1d3d](https://github.com/melMass/comfy_mtb/commit/b9c1d3df7a1460fe9ffa84f6f9ea0cfb5409de1a))
-- ✨ added a way to export the node list ([5f5297f](https://github.com/melMass/comfy_mtb/commit/5f5297f80debc77f3fda2f0d37b3acff8419140d))
-- ✨ WIP batch from history ([cde7293](https://github.com/melMass/comfy_mtb/commit/cde72938d5ffd09179f5974676e12d4599a8d6ff))
-- ✨ extract node names using ast ([38f6147](https://github.com/melMass/comfy_mtb/commit/38f61473bc23b4c5d4efc5048d54c059565a6fa0))
-- 🔥 add batch support for load image sequence ([3faadc4](https://github.com/melMass/comfy_mtb/commit/3faadc4b8a5049cb8c264b8a3d50565adec405f1))
-- 🎨 add support for image.size(0) == 0 ([629e2b5](https://github.com/melMass/comfy_mtb/commit/629e2b5f5fbebe4e79e8b7a4cff2de6017e79225))
-- ✨ image feed ([99eb5ae](https://github.com/melMass/comfy_mtb/commit/99eb5ae0c7413f6ab1f24cfc8337c9b1b2d9824c))
-- ✨ FILM interpolation nodes ([e04e77e](https://github.com/melMass/comfy_mtb/commit/e04e77eb097735ec1369dec51238cdcc5abe39b7))
-- ✨ add an headless option for model downloads ([217e8a1](https://github.com/melMass/comfy_mtb/commit/217e8a1546d06b97250d99612ac6bdb5ce89e155))
-- 🐛 support batch count > 1 for restore face ([8ef48a0](https://github.com/melMass/comfy_mtb/commit/8ef48a013a8d6b832b8c0c7dcabc1b78c27ff207))
-- 🚧 wrapper for GFPGAN bg upscaler ([88cdcc6](https://github.com/melMass/comfy_mtb/commit/88cdcc6a87dae452924e8915eccdadc69d7d136e))
-- ✨ add GFPGAN (FaceRestore) ([3a6e545](https://github.com/melMass/comfy_mtb/commit/3a6e5450502f3b1d7c505178fc9ba337cd95c39e))
-
-### Miscellaneous Tasks
-
-- ✨ before categorize ([0cc54e5](https://github.com/melMass/comfy_mtb/commit/0cc54e58ec86c28354cae37e14f39e831c13ea02))
-- ✨ add more issue templates ([710a638](https://github.com/melMass/comfy_mtb/commit/710a638a8187ef08254478f684307dccdebcded2)) in [#25](https://github.com/melMass/comfy_mtb/pull/25)
-- ✨ add bug report template ([f927bc7](https://github.com/melMass/comfy_mtb/commit/f927bc7c9a82951e6df4763433732f20ea87e9cb))
-- 🍻 create FUNDING.yml ([f634fe0](https://github.com/melMass/comfy_mtb/commit/f634fe0e6b2db28138e4bd7932fbfc8606a0f033))
-- 🍻 add bmc to readme ([cd1b603](https://github.com/melMass/comfy_mtb/commit/cd1b603565464fe98a718e1fbaa8c7cd84057576))
-- 📝 extra files from another branch ([b78be8f](https://github.com/melMass/comfy_mtb/commit/b78be8fd3cd36666fd94a3ab08eca11cce526043))
-- 🚀 push leftovers ([4c41fe7](https://github.com/melMass/comfy_mtb/commit/4c41fe7af9f8e16d895eb06223349e1294dd4698))
-
-### Refactor
-
-- ♻️ removes a few nodes, moved other around ([4d8ddac](https://github.com/melMass/comfy_mtb/commit/4d8ddaca320ce483640d030618e70730b3453df2))
-- ♻️ remove test ([68c250e](https://github.com/melMass/comfy_mtb/commit/68c250e890dacae9f627b0d266ad6dcab0fa0c8b))
-- 🚧 remove color_widget ([e480d07](https://github.com/melMass/comfy_mtb/commit/e480d071171cffa789930620f1e7ccc76473bf93))
-
-### Testing
-
-- 🔧 pipe detection ([ee17d57](https://github.com/melMass/comfy_mtb/commit/ee17d57c3d6d71fda1a5acc2cf85f936c525bc87))
-
-### Install
-
-- 🚧 handle symlink errors ([d982b69](https://github.com/melMass/comfy_mtb/commit/d982b69a58c05ccead9c49370764beaa4549992a))
-
-### Merge
-
-- 🔀 pull request #22 from melMass/dev/next-release ([c34de0a](https://github.com/melMass/comfy_mtb/commit/c34de0ab351b2c95d7fa4fab4487155bee6bfa3a)) in [#22](https://github.com/melMass/comfy_mtb/pull/22)
-- 🎉 pull request #11 from dev/frame_interpolation ([1e28606](https://github.com/melMass/comfy_mtb/commit/1e28606427bcc8d895b87eaa6cd4147ab6d9a11f)) in [#11](https://github.com/melMass/comfy_mtb/pull/11)
-- 🎉 pull request #8 from dev/small-fixes ([7585624](https://github.com/melMass/comfy_mtb/commit/7585624de5895eb34c6a520d4dab18b47e64b6ca)) in [#8](https://github.com/melMass/comfy_mtb/pull/8)
-
-## [0.0.1] - 2023-06-28
-
-### Bug Fixes
-
-- 🤦 add missing file ([e2c4561](https://github.com/melMass/comfy_mtb/commit/e2c456147c260b4e9d583662e3bb9d6d9a019a5e))
-- ✨ small edits ([bcf55ca](https://github.com/melMass/comfy_mtb/commit/bcf55ca9a3a07067be3319182501f7b635e5d2ba))
-- ⚡️ add support for batch in roop ([2dae020](https://github.com/melMass/comfy_mtb/commit/2dae02056a11ddfe1f84ee040818028177e404b5))
-- 🔥 various preparing for the first tag ([793784a](https://github.com/melMass/comfy_mtb/commit/793784a5fd08e8a70d670fc8edbc3bb5b6e13e67))
-- 🐛 various bugs ([afd0843](https://github.com/melMass/comfy_mtb/commit/afd08431458e3bbb14a25c84a87408113edf5db5))
-- ⚡️ add missing controls to QRCode ([7e86b0e](https://github.com/melMass/comfy_mtb/commit/7e86b0ed4d300021517f6c5cf28a45012497b5c5))
-
-### Documentation
-
-- 📝 add rembg screenshot ([9a2d523](https://github.com/melMass/comfy_mtb/commit/9a2d52325f87ecf6342ef4897da919006755b9db))
-- 📝 add a few screenshots ([e162336](https://github.com/melMass/comfy_mtb/commit/e162336cd366d39cd4b96f05b3c9c68eecec3dc4))
-- 📝 update readme ([7f3070d](https://github.com/melMass/comfy_mtb/commit/7f3070debbc3330da50ff845621ce299894cf862))
-
-### Features
-
-- 💄 faceswap node using roop ([966a14b](https://github.com/melMass/comfy_mtb/commit/966a14b40d88f4fccfb2eaa5ff9b222f0eedd7cb))
-- ✨ sync local changes ([647bf9e](https://github.com/melMass/comfy_mtb/commit/647bf9e94195c279a620c74c2253471b9c4b90f7))
-- ✨ bbox from alpha ([37abf8a](https://github.com/melMass/comfy_mtb/commit/37abf8aad12f4711c6d82c6be4be6fa3578e7af5))
-- ✨ a111 like style loader ([f59b68e](https://github.com/melMass/comfy_mtb/commit/f59b68e3ad92841a4d189d8dddf7b41e915c9b4e))
-- ✨ add a color type and widget ([9a2e986](https://github.com/melMass/comfy_mtb/commit/9a2e986327c34227a707beab6d9929b0a05e41e6))
-- ✨ add a few nodes ([811443b](https://github.com/melMass/comfy_mtb/commit/811443b92161815db1cdff81898e8834dcd6fbfa))
-- ✨ add SadTalker as a submodule ([3fb8716](https://github.com/melMass/comfy_mtb/commit/3fb871651b12bce62d8e911bd3884f417f80c937))
-- 🚨 push local changes ([6cac344](https://github.com/melMass/comfy_mtb/commit/6cac344f6fb15ebb902acee70ee71edc585ec4bc))
-- ⚡️ initial commit ([1ae3bbc](https://github.com/melMass/comfy_mtb/commit/1ae3bbc89ae6e0d2e8c61122485bd0df837e17c2))
-
-### Miscellaneous Tasks
-
-- 🚀 add gh action ([572b4d5](https://github.com/melMass/comfy_mtb/commit/572b4d52bce1398660d4d7ca0c5c48c11e0128e3)) in [#4](https://github.com/melMass/comfy_mtb/pull/4)
-
-[main]: https://github.com/melMass/comfy_mtb/compare/v0.1.4..main
-[0.1.4]: https://github.com/melMass/comfy_mtb/compare/v0.1.3..v0.1.4
-[0.1.3]: https://github.com/melMass/comfy_mtb/compare/v0.1.2..v0.1.3
-[0.1.2]: https://github.com/melMass/comfy_mtb/compare/v0.1.1..v0.1.2
-[0.1.1]: https://github.com/melMass/comfy_mtb/compare/v0.1.0..v0.1.1
-[0.1.0]: https://github.com/melMass/comfy_mtb/compare/v0.0.1..v0.1.0
-

__init__.py

@@ -322,6 +322,14 @@ if hasattr(PromptServer, "instance"):
 
         return await endpoint.do_action(request)
 
+    @PromptServer.instance.routes.get("/mtb/audio")
+    async def get_audio(request):
+        from . import endpoint
+
+        reload(endpoint)
+
+        return await endpoint.get_audio(request)
+
 
 # - WAS Dictionary
 MANIFEST = {

cliff.toml

@@ -1,83 +0,0 @@
-[changelog]
-header = """
-# Changelog\n
-This is an automated changelog based on the commits in this repository.
-
-Check the notes in the [releases](https://github.com/melMass/comfy_mtb/releases) for more information.
-"""
-# https://keats.github.io/tera/docs/#introduction
-body = """
-{% if version -%}\
-    ## [{{ version | trim_start_matches(pat="v") }}] - {{ timestamp | date(format="%Y-%m-%d") }}
-{% else %}\
-    ## [Unreleased]
-{% endif -%}\
-
-{% for group, commits in commits | group_by(attribute="group") %}
-    ### {{ group | upper_first }}
-    {% for commit in commits %}
-        - {% if commit.breaking %}[**breaking**] {% endif %}{{ commit.message | upper_first | trim }} ([{{ commit.id | truncate(length=7, end="") }}](<REPO>/commit/{{ commit.id }}))\
-            {% if commit.github.username and commit.github.username != remote.github.owner %} by [@{{ commit.github.username }}](https://github.com/{{ commit.github.username }}){%- endif -%}
-            {% if commit.github.pr_number %} in [#{{ commit.github.pr_number }}](<REPO>/pull/{{ commit.github.pr_number }}){%- endif -%}
-    {% endfor %}
-{% endfor %}
-
-{%- if github.contributors | filter(attribute="is_first_time", value=true) | length != 0 %}
-  ## New Contributors
-{%- endif -%}
-
-{% for contributor in github.contributors | filter(attribute="is_first_time", value=true) %}
-  * [@{{ contributor.username }}](https://github.com/{{ contributor.username }}) made their first contribution in [#{{ contributor.pr_number }}](<REPO>/pull/{{ contributor.pr_number }})\
-{%- endfor %}\n
-"""
-footer = """
-{% for release in releases -%}
-    {% if release.version -%}
-        {% if release.previous.version -%}
-            [{{ release.version | trim_start_matches(pat="v") }}]: \
-                <REPO>/compare/{{ release.previous.version }}..{{ release.version }}
-        {% endif -%}
-    {% else -%}
-        [unreleased]: <REPO>/compare/{{ release.previous.version }}..HEAD
-    {% endif -%}
-{% endfor %}
-"""
-trim = true
-postprocessors = [
-  { pattern = '<REPO>', replace = "https://github.com/melMass/comfy_mtb" }, # replace repository URL
-]
-
-[git]
-# https://www.conventionalcommits.org
-conventional_commits = true
-filter_unconventional = true
-split_commits = false
-commit_preprocessors = [
-  # { pattern = '\((\w+\s)?#([0-9]+)\)', replace = "([#${2}](<REPO>/issues/${2}))" }, # replace issue numbers
-  { pattern = '\((\w+\s)?#([0-9]+)\)', replace = "" },
-]
-commit_parsers = [
-  { message = "^feat", group = "Features" },
-  { message = "^fix", group = "Bug Fixes" },
-  { message = "^doc", group = "Documentation" },
-  { message = "^perf", group = "Performance" },
-  { message = "^refactor", group = "Refactor" },
-  { message = "^style", group = "Styling" },
-  { message = "^test", group = "Testing" },
-  { message = "^chore\\(release\\): prepare for", skip = true },
-  { message = "^chore\\(deps\\)", skip = true },
-  { message = "^chore\\(pr\\)", skip = true },
-  { message = "^chore\\(pull\\)", skip = true },
-  { message = "^chore|ci", group = "Miscellaneous Tasks" },
-  { body = ".*security", group = "Security" },
-  { message = "^revert", group = "Revert" },
-]
-protect_breaking_commits = false
-filter_commits = false
-tag_pattern = "v[0-9].*"
-topo_order = false
-sort_commits = "newest"
-
-[remote.github]
-owner = "melMass"
-repo = "comfy_mtb"

endpoint.py

@@ -3,7 +3,16 @@ import csv
 from aiohttp import web
 
 from .log import mklog
-from .utils import backup_file, here, import_install, reqs_map, run_command, styles_dir
+from .utils import (
+    audioInputDir,
+    backup_file,
+    comfy_dir,
+    here,
+    import_install,
+    reqs_map,
+    run_command,
+    styles_dir,
+)
 
 endlog = mklog("mtb endpoint")
 
@@ -15,6 +24,29 @@ from pathlib import Path
 import_install("requirements")
 
 
+def ACTIONS_loadAudio(args):
+    if not audioInputDir.exists():
+        audioInputDir.mkdir()
+
+    endlog.debug(f"Received Load Audio request for {args}")
+
+    if not args.file:
+        return web.Response(status=400)
+
+    filename = args.filename
+    if not filename:
+        return web.Response(status=400)
+
+    target = audioInputDir / filename
+    if target.exists():
+        target.unlink()
+
+    with target.open("wb") as f:
+        f.write(args.file.read())
+
+    return {"name": filename}
+
+
 def ACTIONS_installDependency(dependency_names=None):
     if dependency_names is None:
         return {"error": "No dependency name provided"}
@@ -88,7 +120,7 @@ def ACTIONS_saveStyle(data):
 
 async def do_action(request) -> web.Response:
     endlog.debug("Init action request")
-    request_data = await request.json()
+    request_data = await request.post()
     name = request_data.get("name")
     args = request_data.get("args")
 
@@ -100,14 +132,33 @@ async def do_action(request) -> web.Response:
     if callable(method):
         result = method(args) if args else method()
         endlog.debug(f"Action result: {result}")
-        return web.json_response({"result": result})
+        return web.json_response({"result": result}, status=200)
 
     available_methods = [
         attr[len("ACTIONS_") :] for attr in globals() if attr.startswith("ACTIONS_")
     ]
 
     return web.json_response(
-        {"error": "Invalid method name.", "available_methods": available_methods}
+        {"error": "Invalid method name.", "available_methods": available_methods},
+        status=400,
+    )
+
+
+async def get_audio(request):
+    name = request.rel_url.query.get("filename")
+    if not name:
+        return web.json_response(
+            {"error": "No filename provided as url query."}, status=400
+        )
+
+    target = audioInputDir / name
+    if not target.exists():
+        return web.json_response(
+            {"error": f"File {name} (in {audioInputDir}) not found..."}, status=404
+        )
+
+    return web.FileResponse(
+        target, headers={"Content-Disposition": f'filename="{name}"'}
     )
 
 

examples/08-note-plus.json

@@ -1 +0,0 @@
-{"last_node_id":9,"last_link_id":0,"nodes":[{"id":9,"type":"Note Plus (mtb)","pos":[332, 139, 0, 0, 0, 0, 0, 0, 0, 0],"size":[573.4446126650389, 1292.5298919072263],"flags":{},"order":0,"mode":0,"inputs":[],"outputs":[],"title":"Note+ (mtb)","properties":{},"widgets_values":["# Note+ Demo\n\n# Images \nyou can resize them (see showdown syntax)\n\n![Minion](https://octodex.github.com/images/minion.png =120x*)\n\n# iFrame (embeds)\n<iframe src=\"https://www.youtube.com/embed/tgbNymZ7vqY\">\n</iframe>\n\n# Headings\n\n# h1 Heading:smile:\n\n## h2 Heading\n\n### h3 Heading\n\n#### h4 Heading\n\n##### h5 Heading\n\n###### h6 Heading\n\n# Tables\n\nColons can be used to align columns.\n\n| Tables|Are|Cool |\n| ------------- |:-----------:| ----:|\n| col 3 is| right-aligned | $1600 |\n| col 2 is| centered| $12 |\n| zebra stripes | are neat|$1 |\n\nEmphasis, aka italics, with _asterisks_ or _underscores_.\n\nStrong emphasis, aka bold, with **asterisks** or **underscores**.\n\nCombined emphasis with **asterisks and _underscores_**.\n\nStrikethrough uses two tildes. ~~Scratch this.~~\n\n**This is bold text**\n\n**This is bold text**\n\n_This is italic text_\n\n_This is italic text_\n\n~~Strikethrough~~\n\n1. First ordered list item\n2. Another item\n\n- Unordered sub-list.\n\n1. Actual numbers don't matter, just that it's a number\n1. Ordered sub-list\n1. And another item.\n1.\n\n- [x] Finish my changes\n- [] Push my commits to GitHub\n- [] Open a pull request\n- [x] mentions:@melmass, #refs, [links](), **formatting**, and <del>tags</del> supported\n- [x] list syntax required (any unordered or ordered list supported)\n- [x] this is a complete item\n- [] this is an incomplete item\n","markdown","*{\ncolor:whitesmoke;\n}\n\nh1{\ncolor:cyan;\n}\nh2{\ncolor:yellow;\n}\nh3{\ncolor:pink;\n}\n\nstrong{\ncolor:red;\n}"],"color":"#223","bgcolor":"#335","shape":1}],"links":[],"groups":[],"config":{},"extra":{},"version":0.4}

node_list.json

@@ -42,14 +42,13 @@
     "Mask To Image (mtb)": "Converts a mask (alpha) to an RGB image with a color and background",
     "Math Expression (mtb)": "Node to evaluate a simple math expression string",
     "Model Patch Seamless (mtb)": "Uses the stable diffusion 'hack' to infer seamless images by setting the model layers padding mode to circular (experimental)",
-    "Pick From Batch (mtb)": "Pick a specific number of images from a batch, either from the start or end.",
     "Qr Code (mtb)": "Basic QR Code generator",
     "Restore Face (mtb)": "Uses GFPGan to restore faces",
     "Save Gif (mtb)": "Save the images from the batch as a GIF",
     "Save Image Grid (mtb)": "Save all the images in the input batch as a grid of images.",
     "Save Image Sequence (mtb)": "Save an image sequence to a folder. The current frame is used to determine which image to save.\n\n    This is merely a wrapper around the `save_images` function with formatting for the output folder and filename.\n    ",
     "Save Tensors (mtb)": "Save torch tensors (image, mask or latent) to disk, useful to debug things outside comfy",
-    "Sharpen (mtb)": "Sharpens an image using a Gaussian kernel.",
+    "Sharpen (mtb)": "Sharpens an image using a Gaussian kernel.",
     "Smart Step (mtb)": "Utils to control the steps start/stop of the KAdvancedSampler in percentage",
     "Stack Images (mtb)": "Stack the input images horizontally or vertically",
     "String Replace (mtb)": "Basic string replacement",

nodes/__init__.py

@@ -1 +0,0 @@
-"""MTB Nodes module."""

nodes/animation.py

@@ -2,7 +2,7 @@ from ..log import log
 
 
 class AnimationBuilder:
-    """Simple maths for animation."""
+    """Convenient way to manage basic animation maths at the core of many of my workflows"""
 
     @classmethod
     def INPUT_TYPES(cls):

nodes/batch.py

@@ -1,6 +1,7 @@
 from io import BytesIO
 
 import cv2
+import torchaudio
 import numpy as np
 import torch
 from PIL import Image
@@ -9,6 +10,11 @@ from ..log import log
 from ..utils import apply_easing, pil2tensor
 from .transform import TransformImage
 
+try:
+    import librosa
+except ImportError:
+    log.warning("librosa not installed. Batch Audio features will not be available.")
+
 
 def hex_to_rgb(hex_color, bgr=False):
     hex_color = hex_color.lstrip("#")
@@ -92,9 +98,7 @@ class BatchShape:
         res = []
         for x in range(count):
             # Initialize an image canvas
-            canvas = np.full(
+            canvas = np.full((image_height, image_width, 3), bg_color, dtype=np.uint8)
-                (image_height, image_width, 3), bg_color, dtype=np.uint8
-            )
             mask = np.zeros((image_height, image_width), dtype=np.uint8)
 
             # Compute the center point of the shape
@@ -124,9 +128,7 @@ class BatchShape:
             # Apply shading effects to a separate shading canvas
             shading = np.zeros_like(canvas, dtype=np.float32)
             shading[:, :, 0] = shadex * np.linspace(0, 1, image_width)
-            shading[:, :, 1] = shadey * np.linspace(
+            shading[:, :, 1] = shadey * np.linspace(0, 1, image_height).reshape(-1, 1)
-                0, 1, image_height
-            ).reshape(-1, 1)
             shading_canvas = cv2.addWeighted(
                 canvas.astype(np.float32), 1, shading, 1, 0
             ).astype(np.uint8)
@@ -159,9 +161,7 @@ class BatchFloatFill:
     def fill_floats(self, floats, direction, value, count):
         size = len(floats)
         if size > count:
-            raise ValueError(
+            raise ValueError(f"Size ({size}) is less then target count ({count})")
-                f"Size ({size}) is less then target count ({count})"
-            )
 
         rem = count - size
         if direction == "tail":
@@ -264,10 +264,7 @@ class BatchMerge:
     def INPUT_TYPES(cls):
         return {
             "required": {
-                "fusion_mode": (
+                "fusion_mode": (["add", "multiply", "average"], {"default": "average"}),
-                    ["add", "multiply", "average"],
-                    {"default": "average"},
-                ),
                 "fill": (["head", "tail"], {"default": "tail"}),
             }
         }
@@ -285,9 +282,7 @@ class BatchMerge:
             frame_count = img.shape[0]
             if frame_count < max_frames:
                 fill_frame = img[0] if fill == "head" else img[-1]
-                fill_frames = fill_frame.repeat(
+                fill_frames = fill_frame.repeat(max_frames - frame_count, 1, 1, 1)
-                    max_frames - frame_count, 1, 1, 1
-                )
                 adjusted_batch = (
                     torch.cat((fill_frames, img), dim=0)
                     if fill == "head"
@@ -360,12 +355,9 @@ class Batch2dTransform:
         shear=None,
     ):
         if all(
-            self.get_num_elements(param) <= 0
+            self.get_num_elements(param) <= 0 for param in [x, y, zoom, angle, shear]
-            for param in [x, y, zoom, angle, shear]
         ):
-            raise ValueError(
+            raise ValueError("At least one transform parameter must be provided")
-                "At least one transform parameter must be provided"
-            )
 
         keyframes = {"x": [], "y": [], "zoom": [], "angle": [], "shear": []}
 
@@ -408,138 +400,6 @@ class Batch2dTransform:
         return (torch.cat(res, dim=0),)
 
 
-class PlotBatchFloat:
-    """Plot floats"""
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "width": ("INT", {"default": 768}),
-                "height": ("INT", {"default": 768}),
-                "point_size": ("INT", {"default": 4}),
-                "seed": ("INT", {"default": 1}),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    RETURN_NAMES = ("plot",)
-    FUNCTION = "plot"
-    CATEGORY = "mtb/batch"
-
-    def plot(self, width, height, point_size, seed, **kwargs):
-        import matplotlib
-
-        matplotlib.use("Agg")
-        import matplotlib.pyplot as plt
-
-        fig, ax = plt.subplots(figsize=(width / 100, height / 100), dpi=100)
-        fig.set_edgecolor("black")
-        fig.patch.set_facecolor("#2e2e2e")
-        # Setting background color and grid
-        ax.set_facecolor("#2e2e2e")  # Dark gray background
-        ax.grid(color="gray", linestyle="-", linewidth=0.5, alpha=0.5)
-
-        # Finding global min and max across all lists for scaling the plot
-        global_min = min(min(values) for values in kwargs.values())
-        global_max = max(max(values) for values in kwargs.values())
-
-        # Color cycle to ensure each plot has a distinct color
-        colormap = plt.cm.get_cmap("viridis", len(kwargs))
-        color_normalization_factor = (
-            0.5 if len(kwargs) == 1 else (len(kwargs) - 1)
-        )
-
-        # Plotting each list with a unique color
-        for i, (label, values) in enumerate(kwargs.items()):
-            color_value = i / color_normalization_factor
-            ax.plot(values, label=label, color=colormap(color_value))
-
-        ax.set_ylim(global_min, global_max)  # Scaling the y-axis
-        ax.legend(
-            title="Legend",
-            title_fontsize="large",
-            fontsize="medium",
-            edgecolor="black",
-        )
-
-        # Setting labels and title
-        ax.set_xlabel("Time", fontsize="large", color="white")
-        ax.set_ylabel("Value", fontsize="large", color="white")
-        ax.set_title(
-            "Plot of Values over Time", fontsize="x-large", color="white"
-        )
-
-        # Adjusting tick colors to be visible on dark background
-        ax.tick_params(colors="white")
-
-        # Changing color of the axes border
-        for _, spine in ax.spines.items():
-            spine.set_edgecolor("white")
-
-        # Rendering the plot into a NumPy array
-        buf = BytesIO()
-        plt.savefig(buf, format="png", bbox_inches="tight")
-        buf.seek(0)
-        image = Image.open(buf)
-        plt.close(fig)  # Closing the figure to free up memory
-
-        return (pil2tensor(image),)
-
-    def draw_point(self, image, point, color, point_size):
-        x, y = point
-        y = image.shape[0] - 1 - y  # Invert Y-coordinate
-        half_size = point_size // 2
-        x_start, x_end = (
-            max(0, x - half_size),
-            min(image.shape[1], x + half_size + 1),
-        )
-        y_start, y_end = (
-            max(0, y - half_size),
-            min(image.shape[0], y + half_size + 1),
-        )
-        image[y_start:y_end, x_start:x_end] = color
-
-    def draw_line(self, image, start, end, color):
-        x1, y1 = start
-        x2, y2 = end
-
-        # Invert Y-coordinate
-        y1 = image.shape[0] - 1 - y1
-        y2 = image.shape[0] - 1 - y2
-
-        dx = x2 - x1
-        dy = y2 - y1
-        is_steep = abs(dy) > abs(dx)
-        if is_steep:
-            x1, y1 = y1, x1
-            x2, y2 = y2, x2
-        swapped = False
-        if x1 > x2:
-            x1, x2 = x2, x1
-            y1, y2 = y2, y1
-            swapped = True
-        dx = x2 - x1
-        dy = y2 - y1
-        error = int(dx / 2.0)
-        y = y1
-        ystep = None
-        if y1 < y2:
-            ystep = 1
-        else:
-            ystep = -1
-        for x in range(x1, x2 + 1):
-            coord = (y, x) if is_steep else (x, y)
-            image[coord] = color
-            error -= abs(dy)
-            if error < 0:
-                y += ystep
-                error += dx
-        if swapped:
-            image[(x1, y1)] = color
-            image[(x2, y2)] = color
-
-
 DEFAULT_INTERPOLANT = lambda t: t * t * t * (t * (t * 6 - 15) + 10)
 
 
@@ -595,9 +455,7 @@ class BatchShake:
         delta = (res[0] / shape[0], res[1] / shape[1])
         d = (shape[0] // res[0], shape[1] // res[1])
         grid = (
-            np.mgrid[0 : res[0] : delta[0], 0 : res[1] : delta[1]].transpose(
+            np.mgrid[0 : res[0] : delta[0], 0 : res[1] : delta[1]].transpose(1, 2, 0)
-                1, 2, 0
-            )
             % 1
         )
         # Gradients
@@ -616,9 +474,7 @@ class BatchShake:
         n00 = np.sum(np.dstack((grid[:, :, 0], grid[:, :, 1])) * g00, 2)
         n10 = np.sum(np.dstack((grid[:, :, 0] - 1, grid[:, :, 1])) * g10, 2)
         n01 = np.sum(np.dstack((grid[:, :, 0], grid[:, :, 1] - 1)) * g01, 2)
-        n11 = np.sum(
+        n11 = np.sum(np.dstack((grid[:, :, 0] - 1, grid[:, :, 1] - 1)) * g11, 2)
-            np.dstack((grid[:, :, 0] - 1, grid[:, :, 1] - 1)) * g11, 2
-        )
         # Interpolation
         t = interpolant(grid)
         n0 = n00 * (1 - t[:, :, 0]) + t[:, :, 0] * n10
@@ -666,10 +522,7 @@ class BatchShake:
         amplitude = 1
         for _ in range(octaves):
             noise += amplitude * self.generate_perlin_noise_2d(
-                shape,
+                shape, (frequency * res[0], frequency * res[1]), tileable, interpolant
-                (frequency * res[0], frequency * res[1]),
-                tileable,
-                interpolant,
             )
             frequency *= lacunarity
             amplitude *= persistence
@@ -763,14 +616,61 @@ class BatchShake:
         return (shaken_images, x_translations, y_translations, rotations)
 
 
+class BatchFloatsFromSound:
+    """Extracts a list of floats based on audio frequency band peaks."""
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "audio": ("AUDIO",),
+                "sensitivity": ("FLOAT", {"default": 1.0}),
+                "low_freq": ("FLOAT", {"default": 100.0}),
+                "high_freq": ("FLOAT", {"default": 2000.0}),
+                "hop_length": ("INT", {"default": 512}),
+            },
+        }
+
+    RETURN_TYPES = ("FLOATS",)
+    RETURN_NAMES = ("float_data",)
+    FUNCTION = "process_audio"
+    CATEGORY = "mtb/audio"
+
+    def process_audio(
+        self,
+        audio,
+        sensitivity=1.0,
+        low_freq=100,
+        high_freq=2000,
+        hop_length=512,
+    ):
+        # audio_data, _ = librosa.load(audio_file_path, sr=sample_rate)
+
+        # audio_data_tensor = audio.squeeze(1)  # Remove the channel dimension if present
+        # audio_tensor = audio_data_tensor.float()
+        audio_data = audio.to(device=torchaudio.transforms.Spectrogram().window.device)
+
+        hop_length = 512
+        stft = torchaudio.transforms.Spectrogram()(audio_data)
+        freqs = torchaudio.transforms.FrequencyMasking(low_freq, high_freq)(stft)
+        band_energy = torch.sum(freqs, dim=1)
+
+        min_val = torch.min(band_energy)
+        max_val = torch.max(band_energy)
+        normalized_peaks = (band_energy - min_val) / (max_val - min_val)
+        scaled_peaks = normalized_peaks * sensitivity
+
+        return (scaled_peaks.tolist(),)
+
+
 __nodes__ = [
     BatchFloat,
     Batch2dTransform,
+    BatchFloatsFromSound,
     BatchShape,
     BatchMake,
     BatchFloatAssemble,
     BatchFloatFill,
     BatchMerge,
     BatchShake,
-    PlotBatchFloat,
 ]

nodes/conditions.py

@@ -1,4 +1,5 @@
-import csv, shutil
+import csv
+import shutil
 from pathlib import Path
 
 import folder_paths
@@ -156,21 +157,13 @@ class StylesLoader:
             for file in files:
                 with open(file, "r", encoding="utf8") as f:
                     parsed = csv.reader(f)
-                    for i, row in enumerate(parsed):
+                    for row in parsed:
                         log.debug(f"Adding style {row[0]}")
                         try:
-                            name, positive, negative = (row + [None] * 3)[:3]
+                            cls.options[row[0]] = (row[1], row[2])
-                            positive = positive or ""
+                        except Exception:
-                            negative = negative or ""
-                            if name is not None:
-                                cls.options[name] = (positive, negative)
-                            else:
-                                # Handle the case where 'name' is None
-                                log.warning(f"Missing 'name' in row {i}.")
-
-                        except Exception as e:
                             log.warning(
-                                f"There was an error while parsing {file}, make sure it respects A1111 format, i.e 3 columns name, positive, negative:\n{e}"
+                                f"There was an error while parsing {file}, make sure it respects A1111 format, i.e 3 columns name, positive, negative"
                             )
                             continue
 

nodes/crop.py

@@ -44,7 +44,6 @@ class BboxFromMask:
         return {
             "required": {
                 "mask": ("MASK",),
-                "invert": ("BOOLEAN", {"default": False}),
             },
             "optional": {
                 "image": ("IMAGE",),
@@ -62,7 +61,7 @@ class BboxFromMask:
     FUNCTION = "extract_bounding_box"
     CATEGORY = "mtb/crop"
 
-    def extract_bounding_box(self, mask: torch.Tensor, invert: bool, image=None):
+    def extract_bounding_box(self, mask: torch.Tensor, image=None):
         # if image != None:
         #     if mask.size(0) != image.size(0):
         #         if mask.size(0) != 1:
@@ -74,8 +73,9 @@ class BboxFromMask:
         #                 f"Batch count mismatch for mask and image, it can either be 1 mask for X images, or X masks for X images (mask: {mask.shape} | image: {image.shape})"
         #             )
 
+        _mask = tensor2pil(1.0 - mask)[0]
+
         # we invert it
-        _mask = tensor2pil(1.0 - mask)[0] if invert else tensor2pil(mask)[0]
         alpha_channel = np.array(_mask)
 
         non_zero_indices = np.nonzero(alpha_channel)
@@ -141,23 +141,19 @@ class Crop:
         self, image: torch.Tensor, mask=None, x=0, y=0, width=256, height=256, bbox=None
     ):
         image = image.numpy()
-        if mask is not None:
+        if mask:
             mask = mask.numpy()
 
-        if bbox is not None:
+        if bbox != None:
             x, y, width, height = bbox
 
         cropped_image = image[:, y : y + height, x : x + width, :]
-        cropped_mask = None
+        cropped_mask = mask[y : y + height, x : x + width] if mask != None else None
-        if mask is not None:
-            cropped_mask = (
-                mask[:, y : y + height, x : x + width] if mask is not None else None
-            )
         crop_data = (x, y, width, height)
 
         return (
             torch.from_numpy(cropped_image),
-            torch.from_numpy(cropped_mask) if cropped_mask is not None else None,
+            torch.from_numpy(cropped_mask) if mask != None else None,
             crop_data,
         )
 

nodes/curve.py

@@ -1,36 +0,0 @@
-import json
-
-
-def deserialize_curve(curve):
-    if isinstance(curve, str):
-        curve = json.loads(curve)
-    return curve
-
-
-def serialize_curve(curve):
-    if not isinstance(curve, str):
-        curve = json.dumps(curve)
-    return curve
-
-
-class MTB_Curve:
-    """A basic FLOAT_CURVE input node."""
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "curve": ("FLOAT_CURVE",),
-            },
-        }
-
-    RETURN_TYPES = ("FLOAT_CURVE",)
-    FUNCTION = "do_curve"
-
-    CATEGORY = "mtb/curve"
-
-    def do_curve(self, curve):
-        return (curve,)
-
-
-__nodes__ = [MTB_Curve]

nodes/debug.py

@@ -39,14 +39,11 @@ def process_list(anything):
         and isinstance(first_element[0], torch.Tensor)
     ):
         text.append(
-            "List of List of Tensors: "
+            f"List of List of Tensors: {first_element[0].shape} (x{len(anything)})"
-            f"{first_element[0].shape} (x{len(anything)})"
         )
 
     elif isinstance(first_element, torch.Tensor):
-        text.append(
+        text.append(f"List of Tensors: {first_element.shape} (x{len(anything)})")
-            f"List of Tensors: {first_element.shape} (x{len(anything)})"
-        )
 
     return {"text": text}
 
@@ -54,9 +51,7 @@ def process_list(anything):
 def process_dict(anything):
     text = []
     if "samples" in anything:
-        is_empty = (
+        is_empty = "(empty)" if torch.count_nonzero(anything["samples"]) == 0 else ""
-            "(empty)" if torch.count_nonzero(anything["samples"]) == 0 else ""
-        )
         text.append(f"Latent Samples: {anything['samples'].shape} {is_empty}")
 
     return {"text": text}
@@ -74,10 +69,7 @@ def process_text(anything):
 
 
 class Debug:
-    """Experimental node to debug any Comfy values.
+    """Experimental node to debug any Comfy values, support for more types and widgets is planned"""
-
-    support for more types and widgets is planned.
-    """
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -111,15 +103,15 @@ class Debug:
 
             for ui_key, ui_value in processed_data.items():
                 output["ui"][ui_key].extend(ui_value)
+            # log.debug(
+            #     f"Processed input {k}, found {len(processed_data.get('b64_images', []))} images and {len(processed_data.get('text', []))} text items."
+            # )
 
         return output
 
 
 class SaveTensors:
-    """Save torch tensors (image, mask or latent) to disk.
+    """Save torch tensors (image, mask or latent) to disk, useful to debug things outside comfy"""
-
-    useful to debug things outside comfy.
-    """
 
     def __init__(self):
         self.output_dir = folder_paths.get_output_directory()
@@ -174,8 +166,7 @@ class SaveTensors:
             torch.save(latent, full_output_folder / latent_file)
             # pickle.dump(latent, open(full_output_folder/ latent_file, "wb"))
 
-            # np.save(full_output_folder / latent_file,
+            # np.save(full_output_folder/ latent_file, latent[""].cpu().numpy())
-            # latent[""].cpu().numpy())
 
         return f"{filename_prefix}_{counter:05}"
 

nodes/deep_bump.py

@@ -8,13 +8,7 @@ from PIL import Image
 
 from ..errors import ModelNotFound
 from ..log import mklog
-from ..utils import (
+from ..utils import get_model_path, tensor2pil, tiles_infer, tiles_merge, tiles_split
-    get_model_path,
-    tensor2pil,
-    tiles_infer,
-    tiles_merge,
-    tiles_split,
-)
 
 # Disable MS telemetry
 ort.disable_telemetry_events()
@@ -22,13 +16,9 @@ log = mklog(__name__)
 
 
 # - COLOR to NORMALS
-def color_to_normals(
+def color_to_normals(color_img, overlap, progress_callback, save_temp=False):
-    color_img, overlap, progress_callback, *, save_temp=False
+    """Computes a normal map from the given color map. 'color_img' must be a numpy array
-):
+    in C,H,W format (with C as RGB). 'overlap' must be one of 'SMALL', 'MEDIUM', 'LARGE'.
-    """Compute a normal map from the given color map.
-
-    'color_img' must be a numpy array in C,H,W format (with C as RGB).
-    'overlap' must be one of 'SMALL', 'MEDIUM', 'LARGE'.
     """
     temp_dir = Path(tempfile.mkdtemp()) if save_temp else None
 
@@ -41,8 +31,7 @@ def color_to_normals(
         )
 
     log.debug(
-        "Converting color image to grayscale by taking "
+        f"Converting color image to grayscale by taking the mean over color channels: {img.shape}"
-        f"the mean over color channels: {img.shape}"
     )
 
     # Split image in tiles
@@ -73,15 +62,13 @@ def color_to_normals(
 
     # Predict normal map for each tile
     log.debug("DeepBump Color → Normals : generating")
-    pred_tiles = tiles_infer(
+    pred_tiles = tiles_infer(tiles, ort_session, progress_callback=progress_callback)
-        tiles, ort_session, progress_callback=progress_callback
-    )
 
     if temp_dir:
         for i, pred_tile in enumerate(pred_tiles):
-            Image.fromarray(
+            Image.fromarray((pred_tile.transpose(1, 2, 0) * 255).astype(np.uint8)).save(
-                (pred_tile.transpose(1, 2, 0) * 255).astype(np.uint8)
+                temp_dir / f"pred_tile_{i}.png"
-            ).save(temp_dir / f"pred_tile_{i}.png")
+            )
 
     # Merge tiles
     log.debug("DeepBump Color → Normals : merging")
@@ -93,17 +80,17 @@ def color_to_normals(
     )
 
     if temp_dir:
-        Image.fromarray(
+        Image.fromarray((pred_img.transpose(1, 2, 0) * 255).astype(np.uint8)).save(
-            (pred_img.transpose(1, 2, 0) * 255).astype(np.uint8)
+            temp_dir / "merged_img.png"
-        ).save(temp_dir / "merged_img.png")
+        )
 
     # Normalize each pixel to unit vector
     pred_img = normalize(pred_img)
 
     if temp_dir:
-        Image.fromarray(
+        Image.fromarray((pred_img.transpose(1, 2, 0) * 255).astype(np.uint8)).save(
-            (pred_img.transpose(1, 2, 0) * 255).astype(np.uint8)
+            temp_dir / "final_img.png"
-        ).save(temp_dir / "final_img.png")
+        )
 
         log.debug(f"Debug images saved in {temp_dir}")
 
@@ -112,47 +99,40 @@ def color_to_normals(
 
 # - NORMALS to CURVATURE
 def conv_1d(array, kernel_1d):
-    """Perform row by row 1D convolutions.
+    """Performs row by row 1D convolutions of the given 2D image with the given 1D kernel."""
 
-    of the given 2D image with the given 1D kernel.
-    """
     # Input kernel length must be odd
     k_l = len(kernel_1d)
-
     assert k_l % 2 != 0
     # Convolution is repeat-padded
     extended = np.pad(array, k_l // 2, mode="wrap")
     # Output has same size as input (padded, valid-mode convolution)
     output = np.empty(array.shape)
     for i in range(array.shape[0]):
-        output[i] = np.convolve(
+        output[i] = np.convolve(extended[i + (k_l // 2)], kernel_1d, mode="valid")
-            extended[i + (k_l // 2)], kernel_1d, mode="valid"
-        )
 
     return output * -1
 
 
 def gaussian_kernel(length, sigma):
-    """Return a 1D gaussian kernel of size 'length'."""
+    """Returns a 1D gaussian kernel of size 'length'."""
+
     space = np.linspace(-(length - 1) / 2, (length - 1) / 2, length)
     kernel = np.exp(-0.5 * np.square(space) / np.square(sigma))
     return kernel / np.sum(kernel)
 
 
 def normalize(np_array):
-    """Normalize all elements of the given numpy array to [0,1]."""
+    """Normalize all elements of the given numpy array to [0,1]"""
-    return (np_array - np.min(np_array)) / (
+
-        np.max(np_array) - np.min(np_array)
+    return (np_array - np.min(np_array)) / (np.max(np_array) - np.min(np_array))
-    )
 
 
 def normals_to_curvature(normals_img, blur_radius, progress_callback):
-    """Compute a curvature map from the given normal map.
+    """Computes a curvature map from the given normal map. 'normals_img' must be a numpy array
+    in C,H,W format (with C as RGB). 'blur_radius' must be one of 'SMALLEST', 'SMALLER', 'SMALL',
+    'MEDIUM', 'LARGE', 'LARGER', 'LARGEST'."""
 
-    'normals_img' must be a numpy array in C,H,W format (with C as RGB).
-    'blur_radius' must be one of:
-        'SMALLEST', 'SMALLER', 'SMALL', 'MEDIUM', 'LARGE', 'LARGER', 'LARGEST'.
-    """
     # Convolutions on normal map red & green channels
     if progress_callback is not None:
         progress_callback(0, 4)
@@ -177,12 +157,8 @@ def normals_to_curvature(normals_img, blur_radius, progress_callback):
         "LARGER": 1 / 8,
         "LARGEST": 1 / 4,
     }
-    if blur_radius not in blur_factors:
+    assert blur_radius in blur_factors
-        raise ValueError(f"{blur_radius} not found in {blur_factors}")
+    blur_radius_px = int(np.mean(normals_img.shape[1:3]) * blur_factors[blur_radius])
-
-    blur_radius_px = int(
-        np.mean(normals_img.shape[1:3]) * blur_factors[blur_radius]
-    )
 
     # If blur radius too small, do not blur
     if blur_radius_px < 2:
@@ -219,9 +195,8 @@ def normals_to_grad(normals_img):
 
 def copy_flip(grad_x, grad_y):
     """Concat 4 flipped copies of input gradients (makes them wrap).
+    Output is twice bigger in both dimensions."""
 
-    Output is twice bigger in both dimensions.
-    """
     grad_x_top = np.hstack([grad_x, -np.flip(grad_x, axis=1)])
     grad_x_bottom = np.hstack([np.flip(grad_x, axis=0), -np.flip(grad_x)])
     new_grad_x = np.vstack([grad_x_top, grad_x_bottom])
@@ -235,6 +210,7 @@ def copy_flip(grad_x, grad_y):
 
 def frankot_chellappa(grad_x, grad_y, progress_callback=None):
     """Frankot-Chellappa depth-from-gradient algorithm."""
+
     if progress_callback is not None:
         progress_callback(0, 3)
 
@@ -274,8 +250,8 @@ def frankot_chellappa(grad_x, grad_y, progress_callback=None):
 def normals_to_height(normals_img, seamless, progress_callback):
     """Computes a height map from the given normal map. 'normals_img' must be a numpy array
     in C,H,W format (with C as RGB). 'seamless' is a bool that should indicates if 'normals_img'
-    is seamless.
+    is seamless."""
-    """
+
     # Flip height axis
     flip_img = np.flip(normals_img, axis=1)
 
@@ -289,9 +265,7 @@ def normals_to_height(normals_img, seamless, progress_callback):
         grad_x, grad_y = copy_flip(grad_x, grad_y)
 
     # Compute height
-    pred_img = frankot_chellappa(
+    pred_img = frankot_chellappa(-grad_x, grad_y, progress_callback=progress_callback)
-        -grad_x, grad_y, progress_callback=progress_callback
-    )
 
     # Cut to valid part if gradients were expanded
     if not seamless:
@@ -312,11 +286,7 @@ class DeepBump:
             "required": {
                 "image": ("IMAGE",),
                 "mode": (
-                    [
+                    ["Color to Normals", "Normals to Curvature", "Normals to Height"],
-                        "Color to Normals",
-                        "Normals to Curvature",
-                        "Normals to Height",
-                    ],
                 ),
                 "color_to_normals_overlap": (["SMALL", "MEDIUM", "LARGE"],),
                 "normals_to_curvature_blur_radius": (
@@ -341,7 +311,6 @@ class DeepBump:
 
     def apply(
         self,
-        *,
         image,
         mode="Color to Normals",
         color_to_normals_overlap="SMALL",
@@ -360,17 +329,13 @@ class DeepBump:
 
             # Apply processing
             if mode == "Color to Normals":
-                out_img = color_to_normals(
+                out_img = color_to_normals(in_img, color_to_normals_overlap, None)
-                    in_img, color_to_normals_overlap, None
-                )
             if mode == "Normals to Curvature":
                 out_img = normals_to_curvature(
                     in_img, normals_to_curvature_blur_radius, None
                 )
             if mode == "Normals to Height":
-                out_img = normals_to_height(
+                out_img = normals_to_height(in_img, normals_to_height_seamless, None)
-                    in_img, normals_to_height_seamless, None
-                )
 
             if out_img is not None:
                 log.debug(f"Output image shape: {out_img.shape}")

nodes/faceenhance.py

@@ -40,12 +40,12 @@ class LoadFaceEnhanceModel:
             log.warning("Face restoration models not found.")
             return []
         if not fr_models_path.exists():
-            # log.warning(
+            log.warning(
-            #     f"No Face Restore checkpoints found at {fr_models_path} (if you've used mtb before these checkpoints were saved in upscale_models before)"
+                f"No Face Restore checkpoints found at {fr_models_path} (if you've used mtb before these checkpoints were saved in upscale_models before)"
-            # )
+            )
-            # log.warning(
+            log.warning(
-            #     "For now we fallback to upscale_models but this will be removed in a future version"
+                "For now we fallback to upscale_models but this will be removed in a future version"
-            # )
+            )
             if um_models_path.exists():
                 return [
                     x
@@ -98,9 +98,7 @@ class LoadFaceEnhanceModel:
                 (fr_root if fr_root.exists() else um_root) / model_name
             ).as_posix(),
             upscale=upscale,
-            arch="clean"
+            arch="clean" if basic else "RestoreFormer",  # or original for v1.0 only
-            if basic
-            else "RestoreFormer",  # or original for v1.0 only
             channel_multiplier=2,  # 1 for v1.0 only
             bg_upsampler=bg_upsampler,
         )
@@ -124,11 +122,7 @@ class BGUpscaleWrapper:
         imgt = imgt.movedim(-1, -3).to(device)
 
         steps = imgt.shape[0] * comfy.utils.get_tiled_scale_steps(
-            imgt.shape[3],
+            imgt.shape[3], imgt.shape[2], tile_x=tile, tile_y=tile, overlap=overlap
-            imgt.shape[2],
-            tile_x=tile,
-            tile_y=tile,
-            overlap=overlap,
         )
 
         log.debug(f"Steps: {steps}")
@@ -205,14 +199,10 @@ class RestoreFace:
         log.warning(f"Weight value has no effect for now. (value: {weight})")
 
         if save_tmp_steps:
-            self.save_intermediate_images(
+            self.save_intermediate_images(cropped_faces, restored_faces, height, width)
-                cropped_faces, restored_faces, height, width
-            )
         output = None
         if restored_img is not None:
-            output = Image.fromarray(
+            output = Image.fromarray(cv2.cvtColor(restored_img, cv2.COLOR_BGR2RGB))
-                cv2.cvtColor(restored_img, cv2.COLOR_BGR2RGB)
-            )
             # imwrite(restored_img, save_restore_path)
 
         return pil2tensor(output)
@@ -228,12 +218,7 @@ class RestoreFace:
     ) -> Tuple[torch.Tensor]:
         out = [
             self.do_restore(
-                image[i],
+                image[i], model, aligned, only_center_face, weight, save_tmp_steps
-                model,
-                aligned,
-                only_center_face,
-                weight,
-                save_tmp_steps,
             )
             for i in range(image.size(0))
         ]
@@ -255,9 +240,7 @@ class RestoreFace:
 
         return os.path.join(full_output_folder, file)
 
-    def save_intermediate_images(
+    def save_intermediate_images(self, cropped_faces, restored_faces, height, width):
-        self, cropped_faces, restored_faces, height, width
-    ):
         for idx, (cropped_face, restored_face) in enumerate(
             zip(cropped_faces, restored_faces)
         ):

nodes/filter.py

@@ -1,69 +0,0 @@
-import torch
-
-
-class MTB_FilterZ:
-    """Filters an image based on a depth map"""
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "image": ("IMAGE",),
-                "depth": ("IMAGE",),
-                "to_black": ("BOOLEAN", {"default": True}),
-                "threshold": (
-                    "FLOAT",
-                    {"default": 0.5, "step": 0.01, "min": 0.0, "max": 1.0},
-                ),
-                "invert": ("BOOLEAN", {"default": True}),
-            },
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    FUNCTION = "filter"
-    CATEGORY = "mtb/filters"
-
-    def filter(
-        self,
-        image: torch.Tensor,
-        depth: torch.Tensor,
-        to_black,
-        threshold: float,
-        invert,
-    ):
-        # Normalize depth map to be in range [0, 1]
-        depth_normalized = (depth - depth.min()) / (depth.max() - depth.min())
-
-        # Calculate the difference from the threshold
-        diff_from_threshold = torch.abs(depth_normalized - threshold)
-
-        out_img = None
-
-        if to_black:
-            if invert:
-                soft_mask = diff_from_threshold >= threshold
-            else:
-                soft_mask = diff_from_threshold <= threshold
-
-            out_img = image.clone()
-            out_img[soft_mask] = 0
-            return (out_img,)
-        else:
-            alpha_channel = 1 - diff_from_threshold / threshold
-            alpha_channel = torch.clamp(alpha_channel, 0, 1)
-
-            if invert:
-                # Invert the alpha channel
-                alpha_channel = 1 - alpha_channel
-
-            # Ensure alpha_channel has the correct shape
-            # It should have the shape [batch_size, height, width, 1]
-            alpha_channel = alpha_channel.unsqueeze(-1)
-
-            # Combine RGB channels with alpha channel
-            out_img = torch.cat((image, alpha_channel), dim=-1)
-
-        return (out_img,)
-
-
-__nodes__ = [MTB_FilterZ]

nodes/generate.py

@@ -1,8 +1,9 @@
 import qrcode
+from ..utils import pil2tensor
+from ..utils import comfy_dir
+from typing import cast
 from PIL import Image
-
 from ..log import log
-from ..utils import comfy_dir, font_path, pil2tensor
 
 # class MtbExamples:
 #     """MTB Example Images"""
@@ -59,18 +60,9 @@ class UnsplashImage:
     def INPUT_TYPES(cls):
         return {
             "required": {
-                "width": (
+                "width": ("INT", {"default": 512, "max": 8096, "min": 0, "step": 1}),
-                    "INT",
+                "height": ("INT", {"default": 512, "max": 8096, "min": 0, "step": 1}),
-                    {"default": 512, "max": 8096, "min": 0, "step": 1},
+                "random_seed": ("INT", {"default": 0, "max": 1e5, "min": 0, "step": 1}),
-                ),
-                "height": (
-                    "INT",
-                    {"default": 512, "max": 8096, "min": 0, "step": 1},
-                ),
-                "random_seed": (
-                    "INT",
-                    {"default": 0, "max": 1e5, "min": 0, "step": 1},
-                ),
             },
             "optional": {
                 "keyword": ("STRING", {"default": "nature"}),
@@ -82,9 +74,8 @@ class UnsplashImage:
     CATEGORY = "mtb/generate"
 
     def do_unsplash_image(self, width, height, random_seed, keyword=None):
-        import io
-
         import requests
+        import io
 
         base_url = "https://source.unsplash.com/random/"
 
@@ -130,14 +121,8 @@ class QrCode:
                     {"default": 256, "max": 8096, "min": 0, "step": 1},
                 ),
                 "error_correct": (("L", "M", "Q", "H"), {"default": "L"}),
-                "box_size": (
+                "box_size": ("INT", {"default": 10, "max": 8096, "min": 0, "step": 1}),
-                    "INT",
+                "border": ("INT", {"default": 4, "max": 8096, "min": 0, "step": 1}),
-                    {"default": 10, "max": 8096, "min": 0, "step": 1},
-                ),
-                "border": (
-                    "INT",
-                    {"default": 4, "max": 8096, "min": 0, "step": 1},
-                ),
                 "invert": (("BOOLEAN",), {"default": False}),
             }
         }
@@ -146,9 +131,7 @@ class QrCode:
     FUNCTION = "do_qr"
     CATEGORY = "mtb/generate"
 
-    def do_qr(
+    def do_qr(self, url, width, height, error_correct, box_size, border, invert):
-        self, url, width, height, error_correct, box_size, border, invert
-    ):
         log.warning(
             "This node will soon be deprecated, there are much better alternatives like https://github.com/coreyryanhanson/comfy-qr"
         )
@@ -173,9 +156,7 @@ class QrCode:
         back_color = (255, 255, 255) if invert else (0, 0, 0)
         fill_color = (0, 0, 0) if invert else (255, 255, 255)
 
-        code = img = qr.make_image(
+        code = img = qr.make_image(back_color=back_color, fill_color=fill_color)
-            back_color=back_color, fill_color=fill_color
-        )
 
         # that we now resize without filtering
         code = code.resize((width, height), Image.NEAREST)
@@ -190,11 +171,9 @@ def bbox_dim(bbox):
     return width, height
 
 
-# TODO: Auto install the base font to ComfyUI/fonts
-
-
 class TextToImage:
-    """Utils to convert text to image using a font.
+    """Utils to convert text to image using a font
+
 
     The tool looks for any .ttf file in the Comfy folder hierarchy.
     """
@@ -202,27 +181,27 @@ class TextToImage:
     fonts = {}
 
     def __init__(self):
-        # - This is executed when the graph is executed,
+        # - This is executed when the graph is executed, we could conditionaly reload fonts there
-        # - we could conditionaly reload fonts there
         pass
 
     @classmethod
     def CACHE_FONTS(cls):
         font_extensions = ["*.ttf", "*.otf", "*.woff", "*.woff2", "*.eot"]
-        fonts = [font_path]
+        fonts = []
 
         for extension in font_extensions:
-            try:
+            fonts.extend(comfy_dir.glob(f"**/{extension}"))
-                if comfy_dir.exists():
+
-                    fonts.extend(comfy_dir.glob(f"fonts/**/{extension}"))
+        if not fonts:
-                else:
+            log.warn(
-                    log.warn(f"Directory {comfy_dir} does not exist.")
+                "> No fonts found in the comfy folder, place at least one font file somewhere in ComfyUI's hierarchy"
-            except Exception as e:
+            )
-                log.error(f"Error during font caching: {e}")
+        else:
+            log.debug(f"> Found {len(fonts)} fonts")
 
         for font in fonts:
             log.debug(f"Adding font {font}")
-            TextToImage.fonts[font.stem] = font.as_posix()
+            cls.fonts[font.stem] = font.as_posix()
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -237,15 +216,13 @@ class TextToImage:
                     {"default": "Hello world!"},
                 ),
                 "font": ((sorted(cls.fonts.keys())),),
-                "wrap": ("BOOLEAN", {"default": True}),
+                "wrap": (
-                "trim": ("BOOLEAN", {"default": True}),
+                    "INT",
-                "line_height": (
+                    {"default": 120, "min": 0, "max": 8096, "step": 1},
-                    "FLOAT",
-                    {"default": 1.0, "min": 0, "step": 0.1},
                 ),
                 "font_size": (
                     "INT",
-                    {"default": 32, "min": 1, "max": 2500, "step": 1},
+                    {"default": 12, "min": 1, "max": 2500, "step": 1},
                 ),
                 "width": (
                     "INT",
@@ -255,6 +232,7 @@ class TextToImage:
                     "INT",
                     {"default": 512, "min": 1, "max": 8096, "step": 1},
                 ),
+                # "position": (["INT"], {"default": 0, "min": 0, "max": 100, "step": 1}),
                 "color": (
                     "COLOR",
                     {"default": "black"},
@@ -263,20 +241,6 @@ class TextToImage:
                     "COLOR",
                     {"default": "white"},
                 ),
-                "h_align": (("left", "center", "right"), {"default": "left"}),
-                "v_align": (("top", "center", "bottom"), {"default": "top"}),
-                "h_offset": (
-                    "INT",
-                    {"default": 0, "min": 0, "max": 8096, "step": 1},
-                ),
-                "v_offset": (
-                    "INT",
-                    {"default": 0, "min": 0, "max": 8096, "step": 1},
-                ),
-                "h_coverage": (
-                    "INT",
-                    {"default": 100, "min": 1, "max": 100, "step": 1},
-                ),
             }
         }
 
@@ -286,79 +250,37 @@ class TextToImage:
     CATEGORY = "mtb/generate"
 
     def text_to_image(
-        self,
+        self, text, font, wrap, font_size, width, height, color, background
-        text: str,
-        font,
-        wrap,
-        trim,
-        line_height,
-        font_size,
-        width,
-        height,
-        color,
-        background,
-        h_align="left",
-        v_align="top",
-        h_offset=0,
-        v_offset=0,
-        h_coverage=100,
     ):
+        from PIL import Image, ImageDraw, ImageFont
         import textwrap
 
-        from PIL import Image, ImageDraw, ImageFont
+        font = self.fonts[font]
-
+        font = cast(ImageFont.FreeTypeFont, ImageFont.truetype(font, font_size))
-        font_path = self.fonts[font]
+        if wrap == 0:
-
+            wrap = width / font_size
-        text = (
+        lines = textwrap.wrap(text, width=wrap)
-            text.encode("ascii", "ignore").decode().strip() if trim else text
-        )
-        # Handle word wrapping
-        if wrap:
-            wrap_width = (((width / 100) * h_coverage) / font_size) * 2
-            lines = textwrap.wrap(text, width=wrap_width)
-        else:
-            lines = [text]
-        font = ImageFont.truetype(font_path, size=font_size)
         log.debug(f"Lines: {lines}")
-        img = Image.new("RGBA", (width, height), background)
+        line_height = bbox_dim(font.getbbox("hg"))[1]
+        img_height = height  # line_height * len(lines)
+        img_width = width  # max(font.getsize(line)[0] for line in lines)
+
+        img = Image.new("RGBA", (img_width, img_height), background)
         draw = ImageDraw.Draw(img)
-
+        y_text = 0
-        line_height_px = line_height * font_size
+        # - bbox is [left, upper, right, lower]
-
-        # Vertical alignment
-        if v_align == "top":
-            y_text = v_offset
-        elif v_align == "center":
-            y_text = ((height - (line_height_px * len(lines))) // 2) + v_offset
-        else:  # bottom
-            y_text = (height - (line_height_px * len(lines))) - v_offset
-
-        def get_width(line):
-            if hasattr(font, "getsize"):
-                return font.getsize(line)[0]
-            else:
-                return font.getlength(line)
-
-        # Draw each line of text
         for line in lines:
-            line_width = get_width(line)
+            width, height = bbox_dim(font.getbbox(line))
-            # Horizontal alignment
+            draw.text((0, y_text), line, color, font=font)
-            if h_align == "left":
+            y_text += height
-                x_text = h_offset
-            elif h_align == "center":
-                x_text = ((width - line_width) // 2) + h_offset
-            else:  # right
-                x_text = (width - line_width) - h_offset
-
-            draw.text((x_text, y_text), line, fill=color, font=font)
-            y_text += line_height_px
 
+        # img.save(os.path.join(folder_paths.base_path, f'{str(uuid.uuid4())}.png'))
         return (pil2tensor(img),)
 
 
 __nodes__ = [
     QrCode,
     UnsplashImage,
-    TextToImage,
+    TextToImage
     #  MtbExamples,
 ]

nodes/graph_utils.py

@@ -1,5 +1,7 @@
-from typing import Optional
+import io
-import io, json, urllib.parse, urllib.request
+import json
+import urllib.parse
+import urllib.request
 
 import numpy as np
 import torch
@@ -23,82 +25,10 @@ def get_image(filename, subfolder, folder_type):
         return io.BytesIO(response.read())
 
 
-class MTB_ToDevice:
-    """Send a image or mask tensor to the given device."""
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        devices = ["cpu"]
-        if torch.backends.mps.is_available():
-            devices.append("mps")
-        if torch.cuda.is_available():
-            for i in range(torch.cuda.device_count()):
-                devices.append(f"cuda{i}")
-
-        return {
-            "required": {
-                "ignore_errors": ("BOOLEAN", {"default": False}),
-                "device": (devices, {"default": "cpu"}),
-            },
-            "optional": {
-                "image": ("IMAGE",),
-                "mask": ("MASK",),
-            },
-        }
-
-    RETURN_TYPES = ("IMAGE", "MASK")
-    RETURN_NAMES = ("images", "masks")
-    CATEGORY = "mtb/utils"
-    FUNCTION = "to_device"
-
-    def to_device(
-        self,
-        *,
-        ignore_errors=False,
-        device="cuda",
-        image: Optional[torch.Tensor] = None,
-        mask: Optional[torch.Tensor] = None,
-    ):
-        if not ignore_errors and image is None and mask is None:
-            raise ValueError(
-                "You must either provide an image or a mask,"
-                " use ignore_error to passthrough"
-            )
-        if image is not None:
-            image = image.to(device)
-        if mask is not None:
-            mask = mask.to(device)
-        return (image, mask)
-
-
-# class MTB_ApplyTextTemplate:
-class MTB_ApplyTextTemplate:
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "template": ("STRING", {"default": "", "multiline": True}),
-            },
-        }
-
-    RETURN_TYPES = ("STRING",)
-    RETURN_NAMES = ("string",)
-    CATEGORY = "mtb/utils"
-    FUNCTION = "execute"
-
-    def execute(self, *, template: str, **kwargs):
-        res = f"{template}"
-        for k, v in kwargs.items():
-            res = res.replace(f"{{{k}}}", f"{v}")
-
-        return (res,)
-
-
 class GetBatchFromHistory:
     """Very experimental node to load images from the history of the server.
 
-    Queue items without output are ignored in the count.
+    Queue items without output are ignored in the count."""
-    """
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -121,7 +51,6 @@ class GetBatchFromHistory:
 
     def load_from_history(
         self,
-        *,
         enable=True,
         count=0,
         offset=0,
@@ -159,9 +88,7 @@ class GetBatchFromHistory:
                 if "images" in node_output:
                     for image in node_output["images"]:
                         image_data = get_image(
-                            image["filename"],
+                            image["filename"], image["subfolder"], image["type"]
-                            image["subfolder"],
-                            image["type"],
                         )
                         output_images.append(image_data)
 
@@ -184,7 +111,7 @@ class GetBatchFromHistory:
 
 
 class AnyToString:
-    """Tries to take any input and convert it to a string."""
+    """Tries to take any input and convert it to a string"""
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -204,14 +131,10 @@ class AnyToString:
         elif isinstance(input, Image.Image):
             return (f"PIL Image of size {input.size} and mode {input.mode}",)
         elif isinstance(input, np.ndarray):
-            return (
+            return (f"Numpy array of shape {input.shape} and dtype {input.dtype}",)
-                f"Numpy array of shape {input.shape} and dtype {input.dtype}",
-            )
 
         elif isinstance(input, dict):
-            return (
+            return (f"Dictionary of {len(input)} items, with keys {input.keys()}",)
-                f"Dictionary of {len(input)} items, with keys {input.keys()}",
-            )
 
         else:
             log.debug(f"Falling back to string conversion of {input}")
@@ -219,7 +142,7 @@ class AnyToString:
 
 
 class StringReplace:
-    """Basic string replacement."""
+    """Basic string replacement"""
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -262,9 +185,7 @@ class MTB_MathExpression:
     RETURN_TYPES = ("FLOAT", "INT")
     RETURN_NAMES = ("result (float)", "result (int)")
     CATEGORY = "mtb/math"
-    DESCRIPTION = (
+    DESCRIPTION = "evaluate a simple math expression string (!! Fallsback to eval)"
-        "evaluate a simple math expression string (!! Fallsback to eval)"
-    )
 
     def eval_expression(self, expression, **kwargs):
         import math
@@ -369,7 +290,7 @@ class FitNumber:
 
 
 class ConcatImages:
-    """Add images to batch."""
+    """Add images to batch"""
 
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "concatenate_tensors"
@@ -402,6 +323,4 @@ __nodes__ = [
     AnyToString,
     ConcatImages,
     MTB_MathExpression,
-    MTB_ToDevice,
-    MTB_ApplyTextTemplate,
 ]

nodes/image_processing.py

@@ -3,11 +3,12 @@ import json
 import math
 import os
 
+import cv2
 import folder_paths
 import numpy as np
 import torch
 import torch.nn.functional as F
-from PIL import Image, ImageOps
+from PIL import Image
 from PIL.PngImagePlugin import PngInfo
 from skimage.filters import gaussian
 from skimage.util import compare_images
@@ -21,9 +22,7 @@ from ..utils import pil2tensor, tensor2np, tensor2pil
 #     log.warning("cv2.ximgproc.guidedFilter not found, use opencv-contrib-python")
 
 
-def gaussian_kernel(
+def gaussian_kernel(kernel_size: int, sigma_x: float, sigma_y: float, device=None):
-    kernel_size: int, sigma_x: float, sigma_y: float, device=None
-):
     x, y = torch.meshgrid(
         torch.linspace(-1, 1, kernel_size, device=device),
         torch.linspace(-1, 1, kernel_size, device=device),
@@ -116,9 +115,7 @@ class ColorCorrect:
         return pil2tensor(out)
 
     @staticmethod
-    def hsv_adjustment_tensor_not_working(
+    def hsv_adjustment_tensor_not_working(image: torch.Tensor, hue, saturation, value):
-        image: torch.Tensor, hue, saturation, value
-    ):
         """Abandonning for now"""
         image = image.squeeze(0).permute(2, 0, 1)
 
@@ -254,7 +251,6 @@ class LoadImageFromUrl_:
     def load(self, url):
         # get the image from the url
         image = Image.open(requests.get(url, stream=True).raw)
-        image = ImageOps.exif_transpose(image)
         return (pil2tensor(image),)
 
 
@@ -348,16 +344,11 @@ class Sharpen_:
             (sharpen_radius, sharpen_radius, sharpen_radius, sharpen_radius),
             "reflect",
         )
-        sharpened = F.conv2d(
+        sharpened = F.conv2d(tensor_image, kernel, padding=center, groups=channels)
-            tensor_image, kernel, padding=center, groups=channels
-        )
 
         # Remove padding
         sharpened = sharpened[
-            :,
+            :, :, sharpen_radius:-sharpen_radius, sharpen_radius:-sharpen_radius
-            :,
-            sharpen_radius:-sharpen_radius,
-            sharpen_radius:-sharpen_radius,
         ]
 
         sharpened = sharpened.permute(0, 2, 3, 1)
@@ -417,9 +408,7 @@ class MaskToImage:
         for m in masks:
             _mask = Image.fromarray(m).convert("L")
 
-            log.debug(
+            log.debug(f"Converted mask to PIL Image format, size: {_mask.size}")
-                f"Converted mask to PIL Image format, size: {_mask.size}"
-            )
 
             image = Image.new("RGBA", _mask.size, color=color)
             # apply the mask
@@ -436,11 +425,8 @@ class MaskToImage:
         return (pil2tensor(images),)
 
 
-from typing import Optional
-
-
 class ColoredImage:
-    """Constant color image of given size."""
+    """Constant color image of given size"""
 
     def __init__(self) -> None:
         pass
@@ -465,87 +451,42 @@ class ColoredImage:
 
     FUNCTION = "render_img"
 
-    def resize_and_crop(self, img, target_size):
-        # Calculate scaling factors for both dimensions
-        scale_x = target_size[0] / img.width
-        scale_y = target_size[1] / img.height
-
-        # Use the smaller scaling factor to maintain aspect ratio
-        scale = max(scale_x, scale_y)
-
-        # Resize the image based on calculated scale
-        new_size = (int(img.width * scale), int(img.height * scale))
-        img = img.resize(new_size, Image.LANCZOS)
-
-        # Calculate cropping coordinates
-        left = (img.width - target_size[0]) / 2
-        top = (img.height - target_size[1]) / 2
-        right = (img.width + target_size[0]) / 2
-        bottom = (img.height + target_size[1]) / 2
-
-        # Crop and return the image
-        return img.crop((left, top, right, bottom))
-
-    def resize_and_crop_thumbnails(self, img, target_size):
-        img.thumbnail(target_size, Image.LANCZOS)
-        left = (img.width - target_size[0]) / 2
-        top = (img.height - target_size[1]) / 2
-        right = (img.width + target_size[0]) / 2
-        bottom = (img.height + target_size[1]) / 2
-        return img.crop((left, top, right, bottom))
-
     def render_img(
-        self,
+        self, color, width, height, foreground_image=None, foreground_mask=None
-        color,
-        width,
-        height,
-        foreground_image: Optional[torch.Tensor] = None,
-        foreground_mask: Optional[torch.Tensor] = None,
     ):
         image = Image.new("RGBA", (width, height), color=color)
         output = []
         if foreground_image is not None:
-            fg_images = tensor2pil(foreground_image)
+            if foreground_mask is None:
-            fg_masks = [None] * len(
+                fg_images = tensor2pil(foreground_image)
-                fg_images
+                for img in fg_images:
-            )  # Default to None for each foreground image
+                    if image.size != img.size:
-
-            if foreground_mask is not None:
-                if foreground_image.size()[0] != foreground_mask.size()[0]:
-                    raise ValueError(
-                        "Foreground image and mask must have same batch size"
-                    )
-                fg_masks = tensor2pil(foreground_mask.unsqueeze(-1))
-
-            for fg_image, fg_mask in zip(fg_images, fg_masks):
-                # Resize and crop if dimensions mismatch
-                if fg_image.size != image.size:
-                    fg_image = self.resize_and_crop(fg_image, image.size)
-                    if fg_mask:
-                        fg_mask = self.resize_and_crop(fg_mask, image.size)
-
-                if fg_mask:
-                    output.append(
-                        Image.composite(
-                            fg_image.convert("RGBA"),
-                            image,
-                            fg_mask,
-                        ).convert("RGB")
-                    )
-                else:
-                    if fg_image.mode != "RGBA":
                         raise ValueError(
-                            "Foreground image must be in 'RGBA' mode "
+                            f"Dimension mismatch: image {image.size}, img {img.size}"
-                            f"when no mask is provided, got {fg_image.mode}"
                         )
-                    output.append(
-                        Image.alpha_composite(image, fg_image).convert("RGB")
-                    )
 
-        else:
+                    if img.mode != "RGBA":
-            if foreground_mask is not None:
+                        raise ValueError(
-                log.warn("Mask ignored because no foreground image is given")
+                            f"Foreground image must be in 'RGBA' mode when no mask is provided, got {img.mode}"
-            output.append(image.convert("RGB"))
+                        )
+
+                    output.append(Image.alpha_composite(image, img).convert("RGB"))
+
+            elif foreground_image.size[0] != foreground_mask.size[0]:
+                raise ValueError("Foreground image and mask must have same batch size")
+            else:
+                fg_images = tensor2pil(foreground_image)
+                fg_masks = tensor2pil(foreground_mask)
+                output.extend(
+                    Image.composite(
+                        fg_image.convert("RGBA"),
+                        image,
+                        fg_mask,
+                    ).convert("RGB")
+                    for fg_image, fg_mask in zip(fg_images, fg_masks)
+                )
+        elif foreground_mask is not None:
+            log.warn("Mask ignored because no foreground image is given")
 
         output = pil2tensor(output)
 
@@ -636,9 +577,7 @@ class ImageResizeFactor:
     ):
         # Check if the tensor has the correct dimension
         if len(image.shape) not in [3, 4]:  # HxWxC or BxHxWxC
-            raise ValueError(
+            raise ValueError("Expected image tensor of shape (H, W, C) or (B, H, W, C)")
-                "Expected image tensor of shape (H, W, C) or (B, H, W, C)"
-            )
 
         # Transpose to CxHxW or BxCxHxW for PyTorch
         if len(image.shape) == 3:
@@ -750,10 +689,7 @@ class SaveImageGrid_:
             subfolder,
             filename_prefix,
         ) = folder_paths.get_save_image_path(
-            filename_prefix,
+            filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
-            self.output_dir,
-            images[0].shape[1],
-            images[0].shape[0],
         )
         image_list = []
         batch_counter = counter
@@ -783,14 +719,10 @@ class SaveImageGrid_:
         file = f"{filename}_{counter:05}_.png"
         grid = self.create_image_grid(image_list)
         grid.save(
-            os.path.join(full_output_folder, file),
+            os.path.join(full_output_folder, file), pnginfo=metadata, compress_level=4
-            pnginfo=metadata,
-            compress_level=4,
         )
 
-        results = [
+        results = [{"filename": file, "subfolder": subfolder, "type": self.type}]
-            {"filename": file, "subfolder": subfolder, "type": self.type}
-        ]
         return {"ui": {"images": results}}
 
 

nodes/image_utils.py

@@ -1,9 +1,10 @@
 import torch
+
 from ..log import log
 
 
 class StackImages:
-    """Stack the input images horizontally or vertically."""
+    """Stack the input images horizontally or vertically"""
 
     @classmethod
     def INPUT_TYPES(cls):
@@ -19,91 +20,22 @@ class StackImages:
 
         tensors = list(kwargs.values())
         log.debug(
-            f"Stacking {len(tensors)} tensors "
+            f"Stacking {len(tensors)} tensors {'vertically' if vertical else 'horizontally'}"
-            f"{'vertically' if vertical else 'horizontally'}"
         )
+        log.debug(list(kwargs.keys()))
 
-        normalized_tensors = [
+        ref_shape = tensors[0].shape
-            self.normalize_to_rgba(tensor) for tensor in tensors
+        for tensor in tensors[1:]:
-        ]
+            if tensor.shape[1:] != ref_shape[1:]:
-
-        if vertical:
-            width = normalized_tensors[0].shape[2]
-            if any(tensor.shape[2] != width for tensor in normalized_tensors):
                 raise ValueError(
-                    "All tensors must have the same width "
+                    "All tensors must have the same dimensions except for the stacking dimension."
-                    "for vertical stacking."
                 )
-            dim = 1
-        else:
-            height = normalized_tensors[0].shape[1]
-            if any(tensor.shape[1] != height for tensor in normalized_tensors):
-                raise ValueError(
-                    "All tensors must have the same height "
-                    "for horizontal stacking."
-                )
-            dim = 2
 
-        stacked_tensor = torch.cat(normalized_tensors, dim=dim)
+        dim = 1 if vertical else 2
+
+        stacked_tensor = torch.cat(tensors, dim=dim)
 
         return (stacked_tensor,)
 
-    def normalize_to_rgba(self, tensor):
-        """Normalize tensor to have 4 channels (RGBA)."""
-        _, _, _, channels = tensor.shape
-        # already RGBA
-        if channels == 4:
-            return tensor
-        # RGB to RGBA
-        elif channels == 3:
-            alpha_channel = torch.ones(
-                tensor.shape[:-1] + (1,), device=tensor.device
-            )  # Add an alpha channel
-            return torch.cat((tensor, alpha_channel), dim=-1)
-        else:
-            raise ValueError(
-                "Tensor has an unsupported number of channels: "
-                "expected 3 (RGB) or 4 (RGBA)."
-            )
 
-
+__nodes__ = [StackImages]
-class PickFromBatch:
-    """Pick a specific number of images from a batch.
-
-    either from the start or end.
-    """
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "image": ("IMAGE",),
-                "from_direction": (["end", "start"], {"default": "start"}),
-                "count": ("INT", {"default": 1}),
-            }
-        }
-
-    RETURN_TYPES = ("IMAGE",)
-    FUNCTION = "pick_from_batch"
-    CATEGORY = "mtb/image utils"
-
-    def pick_from_batch(self, image, from_direction, count):
-        batch_size = image.size(0)
-
-        # Limit count to the available number of images in the batch
-        count = min(count, batch_size)
-        if count < batch_size:
-            log.warning(
-                f"Requested {count} images, "
-                f"but only {batch_size} are available."
-            )
-
-        if from_direction == "end":
-            selected_tensors = image[-count:]
-        else:
-            selected_tensors = image[:count]
-
-        return (selected_tensors,)
-
-
-__nodes__ = [StackImages, PickFromBatch]

nodes/io.py

@@ -8,112 +8,42 @@ import comfy.model_management as model_management
 import folder_paths
 import numpy as np
 import torch
+from comfy.model_management import get_torch_device
 from PIL import Image
 
 from ..log import log
-from ..utils import PIL_FILTER_MAP, output_dir, session_id, tensor2np
+from ..utils import PIL_FILTER_MAP, audioInputDir, tensor2np
+
+try:
+    import librosa
+except ImportError:
+    log.warning("librosa not installed. I/O Audio features will not be available.")
 
 
-def get_playlist_path(playlist_name: str, persistant_playlist=False):
+class LoadAudio_:
-    if persistant_playlist:
+    """Load an audio file from the input folder (supports upload)"""
-        return output_dir / "playlists" / f"{playlist_name}.json"
-
-    return output_dir / "playlists" / session_id / f"{playlist_name}.json"
-
-
-class ReadPlaylist:
-    """Read a playlist"""
 
     @classmethod
     def INPUT_TYPES(cls):
         return {
             "required": {
-                "enable": ("BOOLEAN", {"default": True}),
+                "audio": ("AUDIO_UPLOAD",),
-                "persistant_playlist": ("BOOLEAN", {"default": False}),
+                "sample_rate": ("INT", {"default": 44100}),
-                "playlist_name": (
-                    "STRING",
-                    {"default": "playlist_{index:04d}"},
-                ),
-                "index": ("INT", {"default": 0, "min": 0}),
             }
         }
 
-    RETURN_TYPES = ("PLAYLIST",)
+    RETURN_TYPES = ("AUDIO",)
-    FUNCTION = "read_playlist"
+    RETURN_NAMES = ("audio",)
-    CATEGORY = "mtb/IO"
+    FUNCTION = "load_audio"
+    CATEGORY = "mtb/audio"
 
-    def read_playlist(
+    def load_audio(self, audio: str, sample_rate: int):
-        self,
+        log.debug(f"Audio file: {audio}")
-        enable: bool,
+        audio_file_path = audioInputDir / audio
-        persistant_playlist: bool,
+        log.debug(f"Loading audio file: {audio_file_path}")
-        playlist_name: str,
+        audio_data, _ = librosa.load(audio_file_path.as_posix(), sr=sample_rate)
-        index: int,
+        audio_tensor = torch.from_numpy(audio_data).to(get_torch_device())
-    ):
+        return (audio_tensor.unsqueeze(0).float(),)
-        playlist_name = playlist_name.format(index=index)
-        playlist_path = get_playlist_path(playlist_name, persistant_playlist)
-        if not enable:
-            return (None,)
-
-        if not playlist_path.exists():
-            log.warning(f"Playlist {playlist_path} does not exist, skipping")
-            return (None,)
-
-        log.debug(f"Reading playlist {playlist_path}")
-        return (json.loads(playlist_path.read_text(encoding="utf-8")),)
-
-
-class AddToPlaylist:
-    """Add a video to the playlist"""
-
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {
-                "relative_paths": ("BOOLEAN", {"default": False}),
-                "persistant_playlist": ("BOOLEAN", {"default": False}),
-                "playlist_name": (
-                    "STRING",
-                    {"default": "playlist_{index:04d}"},
-                ),
-                "index": ("INT", {"default": 0, "min": 0}),
-            }
-        }
-
-    RETURN_TYPES = ()
-    OUTPUT_NODE = True
-    FUNCTION = "add_to_playlist"
-    CATEGORY = "mtb/IO"
-
-    def add_to_playlist(
-        self,
-        relative_paths: bool,
-        persistant_playlist: bool,
-        playlist_name: str,
-        index: int,
-        **kwargs,
-    ):
-        playlist_name = playlist_name.format(index=index)
-        playlist_path = get_playlist_path(playlist_name, persistant_playlist)
-
-        if not playlist_path.parent.exists():
-            playlist_path.parent.mkdir(parents=True, exist_ok=True)
-
-        playlist = []
-        if not playlist_path.exists():
-            playlist_path.write_text("[]")
-        else:
-            playlist = json.loads(playlist_path.read_text())
-        log.debug(f"Playlist {playlist_path} has {len(playlist)} items")
-        for video in kwargs.values():
-            if relative_paths:
-                video = Path(video).relative_to(output_dir).as_posix()
-
-            log.debug(f"Adding {video} to playlist")
-            playlist.append(video)
-
-        log.debug(f"Writing playlist {playlist_path}")
-        playlist_path.write_text(json.dumps(playlist), encoding="utf-8")
-        return ()
 
 
 class ExportWithFfmpeg:
@@ -122,22 +52,18 @@ class ExportWithFfmpeg:
     @classmethod
     def INPUT_TYPES(cls):
         return {
-            "optional": {
-                "images": ("IMAGE",),
-                "playlist": ("PLAYLIST",),
-            },
             "required": {
+                "images": ("IMAGE",),
+                # "frames": ("FRAMES",),
                 "fps": ("FLOAT", {"default": 24, "min": 1}),
                 "prefix": ("STRING", {"default": "export"}),
-                "format": (
+                "format": (["mov", "mp4", "mkv", "avi"], {"default": "mov"}),
-                    ["mov", "mp4", "mkv", "gif", "avi"],
-                    {"default": "mov"},
-                ),
                 "codec": (
-                    ["prores_ks", "libx264", "libx265", "gif"],
+                    ["prores_ks", "libx264", "libx265"],
                     {"default": "prores_ks"},
                 ),
             },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
         }
 
     RETURN_TYPES = ("VIDEO",)
@@ -147,99 +73,52 @@ class ExportWithFfmpeg:
 
     def export_prores(
         self,
+        images: torch.Tensor,
         fps: float,
         prefix: str,
         format: str,
         codec: str,
-        images: Optional[torch.Tensor] = None,
+        prompt=None,
-        playlist: Optional[List[str]] = None,
+        extra_pnginfo=None,
     ):
+        metadata = {}
+        if images.size(0) == 0:
+            return ("",)
+
+        if extra_pnginfo is not None:
+            metadata["extra"] = {}
+            for x in extra_pnginfo:
+                metadata["extra"][x] = json.dumps(extra_pnginfo[x])
+
+        if prompt is not None:
+            metadata["prompt"] = json.dumps(prompt)
+
+        output_dir = Path(folder_paths.get_output_directory())
         pix_fmt = "rgb48le" if codec == "prores_ks" else "yuv420p"
         file_ext = format
         file_id = f"{prefix}_{uuid.uuid4()}.{file_ext}"
 
-        if playlist is not None and images is not None:
+        log.debug(f"Exporting to {output_dir / file_id}")
-            log.info(f"Exporting to {output_dir / file_id}")
-
-        if playlist is not None:
-            if len(playlist) == 0:
-                log.debug("Playlist is empty, skipping")
-                return ("",)
-
-            temp_playlist_path = (
-                output_dir / f"temp_playlist_{uuid.uuid4()}.txt"
-            )
-            log.debug(
-                f"Create a temporary file to list the videos for concatenation to {temp_playlist_path}"
-            )
-
-            with open(temp_playlist_path, "w") as f:
-                for video_path in playlist:
-                    f.write(f"file '{video_path}'\n")
-
-            out_path = (output_dir / file_id).as_posix()
-
-            # Prepare the FFmpeg command for concatenating videos from the playlist
-            command = [
-                "ffmpeg",
-                "-f",
-                "concat",
-                "-safe",
-                "0",
-                "-i",
-                temp_playlist_path.as_posix(),
-                "-c",
-                "copy",
-                "-y",
-                out_path,
-            ]
-            log.debug(f"Executing {command}")
-            subprocess.run(command)
-
-            temp_playlist_path.unlink()
-
-            return (out_path,)
-
-        if (
-            images is None or images.size(0) == 0
-        ):  # the is None check is just for the type checker
-            return ("",)
 
         frames = tensor2np(images)
         log.debug(f"Frames type {type(frames[0])}")
         log.debug(f"Exporting {len(frames)} frames")
 
-        if codec == "gif":
+        frames = [frame.astype(np.uint16) * 257 for frame in frames]
-            out_path = (output_dir / file_id).as_posix()
-            command = [
-                "ffmpeg",
-                "-f",
-                "image2pipe",
-                "-vcodec",
-                "png",
-                "-r",
-                str(fps),
-                "-i",
-                "-",
-                "-vcodec",
-                "gif",
-                "-y",
-                out_path,
-            ]
-            process = subprocess.Popen(command, stdin=subprocess.PIPE)
-            for frame in frames:
-                model_management.throw_exception_if_processing_interrupted()
-                Image.fromarray(frame).save(process.stdin, "PNG")
-
-            process.stdin.close()
-            process.wait()
-        else:
-            frames = [frame.astype(np.uint16) * 257 for frame in frames]
 
         height, width, _ = frames[0].shape
 
         out_path = (output_dir / file_id).as_posix()
 
+        metadata_cmd = []
+
+        if metadata:
+            for k, v in metadata.items():
+                metadata_cmd += [
+                    "-metadata:s:v",
+                    f"{k}='{v if isinstance(v,str) else json.dumps(v)}'",
+                ]
+
         # Prepare the FFmpeg command
         command = [
             "ffmpeg",
@@ -258,6 +137,7 @@ class ExportWithFfmpeg:
             "-",
             "-c:v",
             codec,
+            *metadata_cmd,
             "-r",
             str(fps),
             "-y",
@@ -319,8 +199,9 @@ class SaveGif:
                 "resize_by": ("FLOAT", {"default": 1.0, "min": 0.1}),
                 "optimize": ("BOOLEAN", {"default": False}),
                 "pingpong": ("BOOLEAN", {"default": False}),
+            },
+            "optional": {
                 "resample_filter": (list(PIL_FILTER_MAP.keys()),),
-                "use_ffmpeg": ("BOOLEAN", {"default": False}),
             },
         }
 
@@ -337,7 +218,6 @@ class SaveGif:
         optimize=False,
         pingpong=False,
         resample_filter=None,
-        use_ffmpeg=False,
     ):
         if image.size(0) == 0:
             return ("",)
@@ -356,43 +236,18 @@ class SaveGif:
         ruuid = ruuid.hex[:10]
         out_path = f"{folder_paths.output_directory}/{ruuid}.gif"
 
-        if use_ffmpeg:
+        # Create the GIF from PIL images
-            # Use FFmpeg to create the GIF from PIL images
+        pil_images[0].save(
-            command = [
+            out_path,
-                "ffmpeg",
+            save_all=True,
-                "-f",
+            append_images=pil_images[1:],
-                "image2pipe",
+            optimize=optimize,
-                "-vcodec",
+            duration=int(1000 / fps),
-                "png",
+            loop=0,
-                "-r",
+        )
-                str(fps),
-                "-i",
-                "-",
-                "-vcodec",
-                "gif",
-                "-y",
-                out_path,
-            ]
-            process = subprocess.Popen(command, stdin=subprocess.PIPE)
-            for image in pil_images:
-                model_management.throw_exception_if_processing_interrupted()
-                image.save(process.stdin, "PNG")
-            process.stdin.close()
-            process.wait()
 
-        else:
+        results = [{"filename": f"{ruuid}.gif", "subfolder": "", "type": "output"}]
-            pil_images[0].save(
-                out_path,
-                save_all=True,
-                append_images=pil_images[1:],
-                optimize=optimize,
-                duration=int(1000 / fps),
-                loop=0,
-            )
-        results = [
-            {"filename": f"{ruuid}.gif", "subfolder": "", "type": "output"}
-        ]
         return {"ui": {"gif": results}}
 
 
-__nodes__ = [SaveGif, ExportWithFfmpeg, AddToPlaylist, ReadPlaylist]
+__nodes__ = [SaveGif, ExportWithFfmpeg, LoadAudio_]

nodes/video.py

@@ -1,11 +1,13 @@
-import hashlib, json, os, re
+import os
-from pathlib import Path
+import re
-
-import folder_paths
-import numpy as np
 import torch
+import numpy as np
+import hashlib
 from PIL import Image, ImageOps
 from PIL.PngImagePlugin import PngInfo
+import folder_paths
+from pathlib import Path
+import json
 
 from ..log import log
 
@@ -171,10 +173,7 @@ class SaveImageSequence:
             "required": {
                 "images": ("IMAGE",),
                 "filename_prefix": ("STRING", {"default": "Sequence"}),
-                "current_frame": (
+                "current_frame": ("INT", {"default": 0, "min": 0, "max": 9999999}),
-                    "INT",
-                    {"default": 0, "min": 0, "max": 9999999},
-                ),
             },
             "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
         }
@@ -221,14 +220,10 @@ class SaveImageSequence:
         resolved_path = Path(self.output_dir) / filename_prefix
         resolved_path.mkdir(parents=True, exist_ok=True)
 
-        resolved_img = (
+        resolved_img = resolved_path / f"{filename_prefix}_{current_frame:05}.png"
-            resolved_path / f"{filename_prefix}_{current_frame:05}.png"
-        )
 
         output_image = images[0].cpu().numpy()
-        img = Image.fromarray(
+        img = Image.fromarray(np.clip(output_image * 255.0, 0, 255).astype(np.uint8))
-            np.clip(output_image * 255.0, 0, 255).astype(np.uint8)
-        )
         metadata = PngInfo()
         if prompt is not None:
             metadata.add_text("prompt", json.dumps(prompt))

pyproject.toml

@@ -1,114 +0,0 @@
-[tool.poetry]
-name = "comfy-mtb"
-version = "0.4.0"
-description = "Animation oriented nodes pack for ComfyUI."
-license = "MIT"
-readme = "README.md"
-repository = "https://github.com/melMass/comfy_mtb"
-authors = ["Mel Massadian"]
-packages = [{ include = "comfy-mtb" }]
-classifiers = [
-  "License :: OSI Approved :: MIT License",
-  "Operating System :: OS Independent",
-  "Programming Language :: Python",
-  "Programming Language :: Python :: 3",
-  "Programming Language :: Python :: 3.10",
-  "Programming Language :: Python :: 3.11",
-  "Intended Audience :: Developers",
-]
-
-[tool.poetry.urls]
-"Bug Tracker" = "https://github.com/melMass/comfy_mtb/issues"
-"Changelog" = "https://github.com/melMass/comfy_mtb/releases"
-
-[tool.poetry.dependencies]
-python = "^3.10"
-
-[tool.poetry.group.dev.dependencies]
-black = { extras = ["jupyter"], version = "^23.7.0" }
-codespell = "^2.2.5"
-mypy = "^1.5.1"
-pre-commit = "^3.3.3"
-pytest = "^7.4.0"
-pytest-cov = "^4.1.0"
-pytest-random-order = "^1.1.0"
-ruff = "^0.0.285"
-
-[tool.poetry.group.docs]
-optional = true
-
-[tool.poetry.group.docs.dependencies]
-docutils = "0.17.1"
-jupyter-book = "^0.15.1"
-sphinx-autobuild = "^2021.3.14"
-
-[tool.pytest.ini_options]
-log_level = "DEBUG"
-log_cli = true
-markers = [
-  "wip: tests that aren't fully finished yet",
-  "heavy: marks tests as heavy (deselect with '-m \"not heavy\"')",
-
-]
-filterwarnings = ["ignore::UserWarning", 'ignore::DeprecationWarning']
-
-[tool.isort]
-profile = "black"
-line_length = 88
-auto_identify_namespace_packages = false
-# NOTE:
-# pyright doesn't like implicit namespace + single line (related to https://github.com/microsoft/pyright/issues/2882?) but it's horible so I'll live with it
-force_single_line = false
-known_first_party = ["mtb"]
-extend_skip = ["archives"]
-combine_straight_imports = true
-
-[tool.coverage.run]
-parallel = true
-source = ["docs", "tests", "comfy-mtb"]
-
-[tool.coverage.report]
-fail_under = 90
-show_missing = true
-
-[tool.coverage.html]
-show_contexts = true
-
-[tool.ruff]
-line-length = 79
-select = ["A", "B", "C", "D", "E", "F", "FBT", "I", "N", "S", "SIM", "UP", "W"]
-# NOTE: 
-# D102 - undocumented-public-method (noisy)
-# D103 - undocumented-public-function (noisy)
-# D100 - undocumented-public-module (noisy)
-# N802 - invalid-function-name (forced by comfy's arch)
-ignore = ["D103", "D102", "D100", "N802"]
-# exclude auto generated file
-extend-exclude = ["./docs/conf.py"]
-
-[tool.ruff.per-file-ignores]
-# imported but unused
-"__init__.py" = ["F401"]
-# use of assert detected
-"tests/*" = ["S101"]
-
-[tool.ruff.pydocstyle]
-convention = "numpy"
-
-[tool.mypy]
-pretty = true
-ignore_missing_imports = true
-# exclude auto generated file
-exclude = ["docs/conf.py"]
-
-[tool.codespell]
-# exclude auto generated file
-skip = "./docs/conf.py,poetry.lock"
-check-filenames = true
-
-[tool.poetry-version-plugin]
-source = "git-tag"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"

requirements.txt

@@ -6,5 +6,5 @@ rembg
 imageio_ffmpeg
 rich
 rich_argparse
-matplotlib
+librosa
-pillow
+torchaudio

scripts/update_changelog.nu

@@ -1,2 +0,0 @@
-$env.GITHUB_TOKEN = (gh auth token) 
-git cliff --tag main | save -f CHANGELOG.md

tests/setup_test.py

@@ -1,38 +0,0 @@
-# NOTE: this file must be used in all test_* files to setup the test env.
-
-import importlib
-import logging
-import sys
-from pathlib import Path
-
-
-def setup_test():
-    mod_path = Path(__file__).parent.parent
-
-    # add custom_nodes to path
-    sys.path.append(mod_path.parent.as_posix())
-    print(f"Appended: {mod_path.parent.as_posix()}")
-
-    # add comfy root to path
-    sys.path.append(mod_path.parent.parent.as_posix())
-    print(f"Appended: {mod_path.parent.parent.as_posix()}")
-
-    # import mtb
-    module = importlib.import_module(mod_path.name)
-
-    # add the module to globals
-    globals()[mod_path.name] = module
-
-    # set the logging level for third-party libraries
-    logging.getLogger("xformers").setLevel(logging.WARNING)
-    logging.getLogger("tensorflow").setLevel(logging.ERROR)
-    logging.getLogger("h5py._conv").setLevel(logging.ERROR)
-    logging.getLogger("numexpr.utils").setLevel(logging.ERROR)
-    logging.getLogger("matplotlib").setLevel(logging.ERROR)
-    logging.getLogger("torchaudio._extension").setLevel(logging.ERROR)
-    logging.getLogger("torch.utils.tensorboard").setLevel(logging.ERROR)
-    logging.getLogger("torchvision.transforms.functional_tensor").setLevel(
-        logging.ERROR
-    )
-    logging.getLogger("basicsr.metrics.niqe").setLevel(logging.ERROR)
-

tests/test_utils.py

@@ -1,116 +0,0 @@
-import pytest
-from setup_test import setup_test
-
-setup_test()
-
-from comfy_mtb_utils.nodes.graph_utils import FitNumber
-from comfy_mtb_utils.utils import apply_easing
-
-
-# - apply_easing
-@pytest.mark.parametrize(
-    "value, easing_type, expected",
-    [
-        (0.5, "Linear", 0.5),
-        (0, "Linear", 0),
-        (1, "Linear", 1),
-        (0.5, "Sine In", 0.2928932188134524),
-    ],
-)
-def test_apply_easing(value: float, easing_type: str, expected: float):
-    assert apply_easing(value, easing_type) == pytest.approx(
-        expected
-    ), "Easing function did not return expected value"
-
-
-@pytest.mark.parametrize(
-    "val, easing_type",
-    [
-        (0.5, "NonExistentEasing"),
-    ],
-)
-def test_apply_easing_error_handling(val, easing_type):
-    with pytest.raises(ValueError):
-        apply_easing(val, easing_type)
-
-
-@pytest.mark.parametrize(
-    "val, easing_type, expected",
-    [
-        (0, "Linear", 0),
-        (1, "Linear", 1),
-        (0.5, "Linear", 0.5),
-    ],
-)
-def test_apply_easing_corner_cases(val, easing_type, expected):
-    assert apply_easing(val, easing_type) == expected
-
-
-# - FitNumber
-@pytest.fixture
-def fit_number_instance():
-    return FitNumber()
-
-
-@pytest.mark.parametrize(
-    "value, clamp, source_min, source_max, target_min, target_max, easing, expected",
-    [
-        (0.5, False, 0, 1, 0, 1, "Linear", (0.5,)),
-    ],
-)
-def test_fit_number_set_range(
-    fit_number_instance,
-    value,
-    clamp,
-    source_min,
-    source_max,
-    target_min,
-    target_max,
-    easing,
-    expected,
-):
-    assert (
-        fit_number_instance.set_range(
-            value=value,
-            clamp=clamp,
-            source_min=source_min,
-            source_max=source_max,
-            target_min=target_min,
-            target_max=target_max,
-            easing=easing,
-        )
-        == expected
-    ), "Set range method did not return expected value"
-
-
-@pytest.mark.parametrize(
-    "value, clamp, source_min, source_max, target_min, target_max, easing, expected",
-    [
-        (0.5, False, 0, 1, 0, 1, "Linear", (0.5,)),
-        (0.4, False, 1.0, 0.4, 0.4, 0.7, "Linear", (0.7,)),
-        # Add more test cases covering various scenarios, edge cases, and easing types
-    ],
-)
-def test_fit_number_inverted_ranges(
-    fit_number_instance,
-    value,
-    clamp,
-    source_min,
-    source_max,
-    target_min,
-    target_max,
-    easing,
-    expected,
-):
-    assert (
-        fit_number_instance.set_range(
-            value=value,
-            clamp=clamp,
-            source_min=source_min,
-            source_max=source_max,
-            target_min=target_min,
-            target_max=target_max,
-            easing=easing,
-        )
-        == expected
-    ), "Set range method did not return expected value"

utils.py

@@ -86,9 +86,7 @@ def get_server_info():
     base_url = args.listen
     if base_url == "0.0.0.0":
         log.debug("Server set to 0.0.0.0, we will try to resolve the host IP")
-        base_url = ip_checker.get_working_ip(
+        base_url = ip_checker.get_working_ip(f"http://{{}}:{args.port}/history")
-            f"http://{{}}:{args.port}/history"
-        )
         log.debug(f"Setting ip to {base_url}")
     return (base_url, args.port)
 
@@ -168,9 +166,7 @@ def run_command(cmd, ignored_lines_start=None):
     try:
         _run_command(shell_cmd, ignored_lines_start)
     except subprocess.CalledProcessError as e:
-        print(
+        print(f"Command failed with return code: {e.returncode}", file=sys.stderr)
-            f"Command failed with return code: {e.returncode}", file=sys.stderr
-        )
         print(e.stderr.strip(), file=sys.stderr)
 
     except KeyboardInterrupt:
@@ -218,13 +214,7 @@ def import_install(package_name):
 
     except Exception:  # (ImportError, ModuleNotFoundError):
         run_command(
-            [
+            [Path(sys.executable).as_posix(), "-m", "pip", "install", package_spec]
-                Path(sys.executable).as_posix(),
-                "-m",
-                "pip",
-                "install",
-                package_spec,
-            ]
         )
         importlib.import_module(package_name)
 
@@ -248,11 +238,11 @@ here = Path(__file__).parent.absolute()
 # - Construct the absolute path to the ComfyUI directory
 comfy_dir = Path(folder_paths.base_path)
 models_dir = Path(folder_paths.models_dir)
-output_dir = Path(folder_paths.output_directory)
 styles_dir = comfy_dir / "styles"
-session_id = str(uuid.uuid4())
+audioInputDir = comfy_dir / "input" / "audio"
+
 # - Construct the path to the font file
-font_path = here / "data" / "font.ttf"
+font_path = here / "font.ttf"
 
 # - Add extern folder to path
 extern_root = here / "extern"
@@ -263,7 +253,7 @@ for pth in extern_root.iterdir():
 
 # - Add the ComfyUI directory and custom nodes path to the sys.path list
 add_path(comfy_dir)
-add_path(comfy_dir / "custom_nodes")
+add_path((comfy_dir / "custom_nodes"))
 
 PIL_FILTER_MAP = {
     "nearest": Image.Resampling.NEAREST,
@@ -287,9 +277,7 @@ def tensor2pil(image: torch.Tensor) -> List[Image.Image]:
 
     return [
         Image.fromarray(
-            np.clip(255.0 * image.cpu().numpy().squeeze(), 0, 255).astype(
+            np.clip(255.0 * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8)
-                np.uint8
-            )
         )
     ]
 
@@ -298,9 +286,7 @@ def pil2tensor(image: Union[Image.Image, List[Image.Image]]) -> torch.Tensor:
     if isinstance(image, list):
         return torch.cat([pil2tensor(img) for img in image], dim=0)
 
-    return torch.from_numpy(
+    return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
-        np.array(image).astype(np.float32) / 255.0
-    ).unsqueeze(0)
 
 
 def np2tensor(img_np: Union[np.ndarray, List[np.ndarray]]) -> torch.Tensor:
@@ -318,31 +304,23 @@ def tensor2np(tensor: torch.Tensor) -> List[np.ndarray]:
             out.extend(tensor2np(tensor[i]))
         return out
 
-    return [
+    return [np.clip(255.0 * tensor.cpu().numpy().squeeze(), 0, 255).astype(np.uint8)]
-        np.clip(255.0 * tensor.cpu().numpy().squeeze(), 0, 255).astype(
-            np.uint8
-        )
-    ]
 
 
 def pad(img, left, right, top, bottom):
     pad_width = np.array(((0, 0), (top, bottom), (left, right)))
-    print(
+    print(f"pad_width: {pad_width}, shape: {pad_width.shape}")  # Debugging line
-        f"pad_width: {pad_width}, shape: {pad_width.shape}"
-    )  # Debugging line
     return np.pad(img, pad_width, mode="wrap")
 
 
 def tiles_infer(tiles, ort_session, progress_callback=None):
     """Infer each tile with the given model. progress_callback will be called with
     arguments : current tile idx and total tiles amount (used to show progress on
-    cursor in Blender).
+    cursor in Blender)."""
-    """
+
     out_channels = 3  # normal map RGB channels
     tiles_nb = tiles.shape[0]
-    pred_tiles = np.empty(
+    pred_tiles = np.empty((tiles_nb, out_channels, tiles.shape[2], tiles.shape[3]))
-        (tiles_nb, out_channels, tiles.shape[2], tiles.shape[3])
-    )
 
     for i in range(tiles_nb):
         if progress_callback != None:
@@ -356,6 +334,7 @@ def tiles_infer(tiles, ort_session, progress_callback=None):
 
 def generate_mask(tile_size, stride_size):
     """Generates a pyramidal-like mask. Used for mixing overlapping predicted tiles."""
+
     tile_h, tile_w = tile_size
     stride_h, stride_w = stride_size
     ramp_h = tile_h - stride_h
@@ -394,8 +373,8 @@ def generate_mask(tile_size, stride_size):
 
 def corner_mask(side_length):
     """Generates the corner part of the pyramidal-like mask.
-    Currently, only for square shapes.
+    Currently, only for square shapes."""
-    """
+
     corner = np.zeros([side_length, side_length])
 
     for h in range(0, side_length):
@@ -431,8 +410,8 @@ def scaling_mask(side_length):
 
 def tiles_merge(tiles, stride_size, img_size, paddings):
     """Merges the list of tiles into one image. img_size is the original size, before
-    padding.
+    padding."""
-    """
+
     _, tile_h, tile_w = tiles[0].shape
     pad_left, pad_right, pad_top, pad_bottom = paddings
     height = img_size[1] + pad_top + pad_bottom
@@ -465,8 +444,7 @@ def tiles_merge(tiles, stride_size, img_size, paddings):
 
 def tiles_split(img, tile_size, stride_size):
     """Returns list of tiles from the given image and the padding used to fit the tiles
-    in it. Input image must have dimension C,H,W.
+    in it. Input image must have dimension C,H,W."""
-    """
     log.debug(f"Splitting img: tile {tile_size}, stride {stride_size} ")
     tile_h, tile_w = tile_size
     stride_h, stride_w = stride_size
@@ -523,9 +501,7 @@ def tiles_split(img, tile_size, stride_size):
 
 # region MODEL Utilities
 def download_antelopev2():
-    antelopev2_url = (
+    antelopev2_url = "https://drive.google.com/uc?id=18wEUfMNohBJ4K3Ly5wpTejPfDzp-8fI8"
-        "https://drive.google.com/uc?id=18wEUfMNohBJ4K3Ly5wpTejPfDzp-8fI8"
-    )
 
     try:
         import gdown
@@ -636,10 +612,7 @@ def apply_easing(value, easing_type):
             return 1
         p = 0.3
         s = p / 4
-        return -(
+        return -(math.pow(2, 10 * (t - 1)) * math.sin((t - 1 - s) * (2 * math.pi) / p))
-            math.pow(2, 10 * (t - 1))
-            * math.sin((t - 1 - s) * (2 * math.pi) / p)
-        )
 
     def easeOutElastic(t):
         if t == 0:
@@ -660,13 +633,10 @@ def apply_easing(value, easing_type):
         t = t * 2
         if t < 1:
             return -0.5 * (
-                math.pow(2, 10 * (t - 1))
+                math.pow(2, 10 * (t - 1)) * math.sin((t - 1 - s) * (2 * math.pi) / p)
-                * math.sin((t - 1 - s) * (2 * math.pi) / p)
             )
         return (
-            0.5
+            0.5 * math.pow(2, -10 * (t - 1)) * math.sin((t - 1 - s) * (2 * math.pi) / p)
-            * math.pow(2, -10 * (t - 1))
-            * math.sin((t - 1 - s) * (2 * math.pi) / p)
             + 1
         )
 

web/README.md

@@ -13,10 +13,6 @@ data otherwise:
 ![debug](https://github.com/melMass/comfy_mtb/assets/7041726/1f4393e4-1c3d-4807-9501-fe8888bfae25)
 
 
-**note +**
-A basic HTML note mainly to add better looking notes/instructions for workflow makers:
-![image](https://github.com/melMass/comfy_mtb/assets/7041726/2ba1f832-0044-4bad-974c-e6387981af57)
-
 
 ## Standalone
 These scripts can be taken and placed independently of `comfy_mtb` or any other files, mimicking what pythongosss did for their 

web/comfy_shared.js

@@ -9,67 +9,6 @@
 
 import { app } from '../../scripts/app.js'
 
-// - crude uuid
-export function makeUUID() {
-  let dt = new Date().getTime()
-  const uuid = 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (c) => {
-    const r = (dt + Math.random() * 16) % 16 | 0
-    dt = Math.floor(dt / 16)
-    return (c === 'x' ? r : (r & 0x3) | 0x8).toString(16)
-  })
-  return uuid
-}
-
-//- local storage manager
-export class LocalStorageManager {
-  constructor(namespace) {
-    this.namespace = namespace
-  }
-
-  _namespacedKey(key) {
-    return `${this.namespace}:${key}`
-  }
-
-  set(key, value) {
-    const serializedValue = JSON.stringify(value)
-    localStorage.setItem(this._namespacedKey(key), serializedValue)
-  }
-
-  get(key, default_val = null) {
-    const value = localStorage.getItem(this._namespacedKey(key))
-    return value ? JSON.parse(value) : default_val
-  }
-
-  remove(key) {
-    localStorage.removeItem(this._namespacedKey(key))
-  }
-
-  clear() {
-    Object.keys(localStorage)
-      .filter((k) => k.startsWith(this.namespace + ':'))
-      .forEach((k) => localStorage.removeItem(k))
-  }
-}
-
-// - log utilities
-
-function createLogger(emoji, color, consoleMethod = 'log') {
-  return function (message, ...args) {
-    if (window.MTB?.DEBUG) {
-      console[consoleMethod](
-        `%c${emoji} ${message}`,
-        `color: ${color};`,
-        ...args,
-      )
-    }
-  }
-}
-
-export const infoLogger = createLogger('ℹ️', 'yellow')
-export const warnLogger = createLogger('⚠️', 'orange', 'warn')
-export const errorLogger = createLogger('🔥', 'red', 'error')
-export const successLogger = createLogger('✅', 'green')
-
 export const log = (...args) => {
   if (window.MTB?.DEBUG) {
     console.debug(...args)
@@ -109,14 +48,14 @@ export function offsetDOMWidget(
   node,
   widgetWidth,
   widgetY,
-  height,
+  height
 ) {
   const margin = 10
   const elRect = ctx.canvas.getBoundingClientRect()
   const transform = new DOMMatrix()
     .scaleSelf(
       elRect.width / ctx.canvas.width,
-      elRect.height / ctx.canvas.height,
+      elRect.height / ctx.canvas.height
     )
     .multiplySelf(ctx.getTransform())
     .translateSelf(margin, margin + widgetY)
@@ -166,7 +105,7 @@ export const setupDynamicConnections = (nodeType, prefix, inputType) => {
     type,
     index,
     connected,
-    link_info,
+    link_info
   ) {
     const r = onConnectionsChange
       ? onConnectionsChange.apply(this, arguments)
@@ -180,11 +119,8 @@ export const dynamic_connection = (
   connected,
   connectionPrefix = 'input_',
   connectionType = 'PSDLAYER',
-  nameArray = [],
+  nameArray = []
 ) => {
-  if (!node.inputs[index].name.startsWith(connectionPrefix)) {
-    return
-  }
   // remove all non connected inputs
   if (!connected && node.inputs.length > 1) {
     log(`Removing input ${index} (${node.inputs[index].name})`)
@@ -220,25 +156,6 @@ export const dynamic_connection = (
   }
 }
 
-export function calculateTotalChildrenHeight(parentElement) {
-  let totalHeight = 0
-
-  for (const child of parentElement.children) {
-    const style = window.getComputedStyle(child)
-
-    // Get height as an integer (without 'px')
-    const height = parseInt(style.height, 10)
-
-    // Get vertical margin as integers
-    const marginTop = parseInt(style.marginTop, 10)
-    const marginBottom = parseInt(style.marginBottom, 10)
-
-    // Sum up height and vertical margins
-    totalHeight += height + marginTop + marginBottom
-  }
-
-  return totalHeight
-}
 /**
  * Appends a callback to the extra menu options of a given node type.
  * @param {*} nodeType
@@ -409,48 +326,11 @@ function getBrightness(rgbObj) {
     (parseInt(rgbObj[0]) * 299 +
       parseInt(rgbObj[1]) * 587 +
       parseInt(rgbObj[2]) * 114) /
-      1000,
+      1000
   )
 }
 
 //- HTML / CSS UTILS
-export const loadScript = (
-  FILE_URL,
-  async = true,
-  type = 'text/javascript',
-) => {
-  return new Promise((resolve, reject) => {
-    try {
-      // Check if the script already exists
-      const existingScript = document.querySelector(`script[src="${FILE_URL}"]`)
-      if (existingScript) {
-        resolve({ status: true, message: 'Script already loaded' })
-        return
-      }
-
-      const scriptEle = document.createElement('script')
-      scriptEle.type = type
-      scriptEle.async = async
-      scriptEle.src = FILE_URL
-
-      scriptEle.addEventListener('load', (ev) => {
-        resolve({ status: true })
-      })
-
-      scriptEle.addEventListener('error', (ev) => {
-        reject({
-          status: false,
-          message: `Failed to load the script ＄{FILE_URL}`,
-        })
-      })
-
-      document.body.appendChild(scriptEle)
-    } catch (error) {
-      reject(error)
-    }
-  })
-}
-
 export function defineClass(className, classStyles) {
   const styleSheets = document.styleSheets
 
@@ -483,20 +363,3 @@ export function defineClass(className, classStyles) {
     }
   }
 }
-
-/** Prefixes the node title with '[DEPRECATED]' and log the deprecation reason to the console.*/
-export const addDeprecation = (nodeType, reason) => {
-  const title = nodeType.title
-  nodeType.title = '[DEPRECATED] ' + title
-  // console.log(nodeType)
-
-  const styles = {
-    title: 'font-size:1.3em;font-weight:900;color:yellow; background: black',
-    reason: 'font-size:1.2em',
-  }
-  console.log(
-    `%c⚠️  ${title} is deprecated:%c ${reason}`,
-    styles.title,
-    styles.reason,
-  )
-}

web/curve_widget.js

@@ -1,187 +0,0 @@
-
-import { app } from '../../scripts/app.js'
-
-function B0(t) { return (1 - t) ** 3 / 6; }
-function B1(t) { return (3 * t ** 3 - 6 * t ** 2 + 4) / 6; }
-function B2(t) { return (-3 * t ** 3 + 3 * t ** 2 + 3 * t + 1) / 6; }
-function B3(t) { return t ** 3 / 6; }
-
-class CurveWidget {
-    constructor(inputName, defaultValue) {
-        this.name = inputName || "Curve";
-        this._value = defaultValue || [{ x: 0, y: 0 }, { x: 1, y: 1 }];
-        this.type = "FLOAT_CURVE";
-        this.selectedPointIndex = null;
-        this.resize
-    }
-
-    drawBSpline(ctx, width, height, posY) {
-        const n = this._value.length - 1;
-        const numSegments = n - 2;
-        const numPoints = this._value.length;
-        if (numPoints < 4) {
-            this.drawLinear(ctx, width, height, posY);
-        } else {
-            for (let j = 0; j <= numSegments; j++) {
-                for (let t = 0; t <= 1; t += 0.01) {
-                    let pt = this.getBSplinePoint(j, t);
-                    let x = pt.x * width;
-                    let y = posY + height - pt.y * height;
-
-                    if (t === 0) ctx.moveTo(x, y);
-                    else ctx.lineTo(x, y);
-                }
-            }
-            ctx.stroke();
-        }
-    }
-
-    drawLinear(ctx, width, height, posY) {
-        for (let i = 0; i < this._value.length - 1; i++) {
-            let p1 = this._value[i];
-            let p2 = this._value[i + 1];
-            ctx.moveTo(p1.x * width, posY + height - p1.y * height);
-            ctx.lineTo(p2.x * width, posY + height - p2.y * height);
-        }
-        ctx.stroke();
-    }
-
-    getBSplinePoint(i, t) {
-        // Control points for this segment
-        const p0 = this._value[i];
-        const p1 = this._value[i + 1];
-        const p2 = this._value[i + 2];
-        const p3 = this._value[i + 3];
-
-        const x = B0(t) * p0.x + B1(t) * p1.x + B2(t) * p2.x + B3(t) * p3.x;
-        const y = B0(t) * p0.y + B1(t) * p1.y + B2(t) * p2.y + B3(t) * p3.y;
-
-        return { x, y };
-    }
-
-    draw(ctx, node, width, posY, height) {
-        const [cw, ch] = this.computeSize(width)
-
-        ctx.beginPath();
-        ctx.fillStyle = "#000";
-        //ctx.fillRect(0, posY, cw, ch);
-        ctx.strokeStyle = "#fff";
-        ctx.lineWidth = 2;
-
-        // normalized coordinates -> canvas coordinates
-        for (let i = 0; i < this._value.length - 1; i++) {
-            let p1 = this._value[i];
-            let p2 = this._value[i + 1];
-            ctx.moveTo(p1.x * cw, posY + ch - p1.y * ch);
-            ctx.lineTo(p2.x * cw, posY + ch - p2.y * ch);
-        }
-        ctx.stroke();
-        // this.drawBSpline(ctx, width, height, posY);
-
-        // points
-        this._value.forEach(point => {
-            ctx.beginPath();
-            ctx.arc(point.x * cw, posY + ch - point.y * ch, 5, 0, 2 * Math.PI);
-            ctx.fill();
-        });
-    }
-
-    mouse(event, pos, node) {
-        // console.debug(event.type, pos, node)
-        let x = pos[0] - node.pos[0]
-        let y = pos[1] - node.pos[1]
-        let width = node.size[0]
-        const height = 300; // TODO: compute
-        const posY = node.pos[1];
-
-        const localPos = { x: pos[0], y: pos[1] - LiteGraph.NODE_WIDGET_HEIGHT };
-
-        if (event.type === LiteGraph.pointerevents_method + "down") {
-            console.debug("Checking if a point was clicked");
-            const clickedPointIndex = this.detectPoint(localPos, width, height);
-            if (clickedPointIndex !== null) {
-                this.selectedPointIndex = clickedPointIndex;
-            } else {
-                this.addPoint(localPos, width, height);
-            }
-            return true;
-        } else if (event.type === LiteGraph.pointerevents_method + "move" && this.selectedPointIndex !== null) {
-            this.movePoint(this.selectedPointIndex, localPos, width, height);
-            return true;
-        } else if (event.type === LiteGraph.pointerevents_method + "up" && this.selectedPointIndex !== null) {
-            this.selectedPointIndex = null;
-            return true;
-        }
-        return false;
-    }
-
-
-    detectPoint(localPos, width, height) {
-        const threshold = 20; // TODO: extract
-        for (let i = 0; i < this._value.length; i++) {
-            const p = this._value[i];
-            const px = p.x * width;
-            const py = height - p.y * height;
-            if (Math.abs(localPos.x - px) < threshold && Math.abs(localPos.y - py) < threshold) {
-                return i;
-            }
-        }
-        return null;
-    }
-
-    addPoint(localPos, width, height) {
-        // add a new point based on click position
-        const normalizedPoint = { x: localPos.x / width, y: 1 - localPos.y / height };
-        this._value.push(normalizedPoint);
-        this._value.sort((a, b) => a.x - b.x);
-        this.value = JSON.stringify(this._value);
-    }
-
-    movePoint(index, localPos, width, height) {
-        const point = this._value[index];
-        point.x = Math.max(0, Math.min(1, localPos.x / width));
-        point.y = Math.max(0, Math.min(1, 1 - localPos.y / height));
-
-        this._value[index] = point;
-        this.value = JSON.stringify(this._value);
-    }
-
-    computeSize(width) {
-        return [width, 300];
-    }
-
-    configure(data) {
-        console.log(data)
-    }
-
-    value() {
-        console.debug('Returning value', this._value)
-        return this._value
-    }
-    setValue(value) {
-        console.debug('Setting value', value)
-        this._value = value
-    }
-}
-
-app.registerExtension({
-    name: 'mtb.curves',
-    getCustomWidgets: function () {
-        return {
-            FLOAT_CURVE: (node, inputName, inputData, app) => {
-                console.debug('Registering float curve widget');
-
-                return {
-                    widget: node.addCustomWidget(
-                        new CurveWidget(inputName, inputData[1]?.default)
-                    ),
-                    minWidth: 150,
-                    minHeight: 30,
-                }
-            },
-
-
-        }
-    },
-
-})

web/debug.js

@@ -41,7 +41,7 @@ app.registerExtension({
         type,
         index,
         connected,
-        link_info,
+        link_info
       ) {
         const r = onConnectionsChange
           ? onConnectionsChange.apply(this, arguments)
@@ -52,7 +52,7 @@ app.registerExtension({
         //- infer type
         if (link_info) {
           const fromNode = this.graph._nodes.find(
-            (otherNode) => otherNode.id == link_info.origin_id,
+            (otherNode) => otherNode.id == link_info.origin_id
           )
           const type = fromNode.outputs[link_info.origin_slot].type
           this.inputs[index].type = type
@@ -63,7 +63,6 @@ app.registerExtension({
           this.inputs[index].type = '*'
           this.inputs[index].label = `anything_${index + 1}`
         }
-        return r
       }
 
       const onExecuted = nodeType.prototype.onExecuted
@@ -87,7 +86,7 @@ app.registerExtension({
         if (message.text) {
           for (const txt of message.text) {
             const w = this.addCustomWidget(
-              MtbWidgets.DEBUG_STRING(`${prefix}_${widgetI}`, escapeHtml(txt)),
+              MtbWidgets.DEBUG_STRING(`${prefix}_${widgetI}`, escapeHtml(txt))
             )
             w.parent = this
             widgetI++
@@ -96,7 +95,7 @@ app.registerExtension({
         if (message.b64_images) {
           for (const img of message.b64_images) {
             const w = this.addCustomWidget(
-              MtbWidgets.DEBUG_IMG(`${prefix}_${widgetI}`, img),
+              MtbWidgets.DEBUG_IMG(`${prefix}_${widgetI}`, img)
             )
             w.parent = this
             widgetI++

web/imageFeed.js

@@ -11,7 +11,7 @@
 
 import { api } from '../../scripts/api.js'
 import { app } from '../../scripts/app.js'
-import { LocalStorageManager } from "./comfy_shared.js"
+
 const styles = {
   lighbox: {
     position: 'fixed',
@@ -53,31 +53,11 @@ let currentImageIndex = 0
 const imageUrls = []
 
 let image_menu = null
-const storage = new LocalStorageManager('mtb');
+let activated = true
-
-let activated = storage.get("image_feed", true)
 
 app.registerExtension({
   name: 'mtb.ImageFeed',
-  setup: () => {
-    app.ui.settings.addSetting({
-      id: 'mtb.imageFeed.enabled',
-      name: '[⚡mtb] Enable image feed',
-      type: 'boolean',
-      defaultValue: true,
-      attrs: {
-        style: {
-          fontFamily: 'monospace',
-        },
-      },
-      async onChange(value) {
-        storage.set("image_feed", value)
-        activated = value
-      },
-    })
-  },
   init: async () => {
-    if (!activated) { return }
     const pythongossFeed = app.extensions.find(
       (e) => e.name == 'pysssss.ImageFeed'
     )
@@ -250,8 +230,9 @@ app.registerExtension({
         objectFit: 'cover',
       })
 
-      img.src = `/view?filename=${encodeURIComponent(src.filename)}&type=${src.type
+      img.src = `/view?filename=${encodeURIComponent(src.filename)}&type=${
-        }&subfolder=${encodeURIComponent(src.subfolder)}`
+        src.type
+      }&subfolder=${encodeURIComponent(src.subfolder)}`
 
       imageUrls.push(img.src)
 

web/mtb_widgets.js

@@ -7,8 +7,6 @@
  *
  */
 
-// TODO: Use the builtin addDOMWidget everywhere appropriate
-
 import { app } from '../../scripts/app.js'
 import { api } from '../../scripts/api.js'
 
@@ -16,13 +14,7 @@ import parseCss from './extern/parse-css.js'
 import * as shared from './comfy_shared.js'
 import { log } from './comfy_shared.js'
 
-// NOTE: new widget types registered by MTB Widgets
+const newTypes = [, /*'BOOL'*/ 'COLOR', 'BBOX', 'AUDIO_UPLOAD']
-const newTypes = [, /*'BOOL'*/ 'COLOR', 'BBOX']
-
-const deprecated_nodes = {
-  //  'Animation Builder':
-  //    'Kept to avoid breaking older script but replaced by TimeEngine',
-}
 
 const withFont = (ctx, font, cb) => {
   const oldFont = ctx.font
@@ -49,10 +41,58 @@ const calculateTextDimensions = (ctx, value, width, fontSize = 16) => {
   const textHeight = (lines.length + 1) * fontSize
   const maxLineWidth = lines.reduce(
     (maxWidth, line) => Math.max(maxWidth, ctx.measureText(line).width),
-    0,
+    0
   )
   return { textHeight, maxLineWidth }
 }
+function addPlaybackWidget(node, name, url) {
+  let isTick = true
+  const audio = new Audio(url)
+  const slider = node.addWidget(
+    'slider',
+    'loading',
+    0,
+    (v) => {
+      if (!isTick) {
+        audio.currentTime = v
+      }
+      isTick = false
+    },
+    {
+      min: 0,
+      max: 0,
+    }
+  )
+
+  const button = node.addWidget('button', `Play ${name}`, 'play', () => {
+    try {
+      if (audio.paused) {
+        audio.play()
+        button.name = `Pause ${name}`
+      } else {
+        audio.pause()
+        button.name = `Play ${name}`
+      }
+    } catch (error) {
+      alert(error)
+    }
+    app.canvas.setDirty(true)
+  })
+  audio.addEventListener('timeupdate', () => {
+    isTick = true
+    slider.value = audio.currentTime
+    app.canvas.setDirty(true)
+  })
+  audio.addEventListener('ended', () => {
+    button.name = `Play ${name}`
+    app.canvas.setDirty(true)
+  })
+  audio.addEventListener('loadedmetadata', () => {
+    slider.options.max = audio.duration
+    slider.name = `(${audio.duration})`
+    app.canvas.setDirty(true)
+  })
+}
 
 export const MtbWidgets = {
   BBOX: (key, val) => {
@@ -112,7 +152,7 @@ export const MtbWidgets = {
             ctx.fillText(
               this.label || this.name,
               margin * 2 + 5,
-              currentY + H * 0.7,
+              currentY + H * 0.7
             )
             ctx.fillStyle = text_color
             ctx.textAlign = 'right'
@@ -121,10 +161,10 @@ export const MtbWidgets = {
               Number(this.value).toFixed(
                 this.options?.precision !== undefined
                   ? this.options.precision
-                  : 3,
+                  : 3
               ),
               widget_width - margin * 2 - 20,
-              currentY + H * 0.7,
+              currentY + H * 0.7
             )
           }
         }
@@ -206,7 +246,7 @@ export const MtbWidgets = {
                   this.value = Number(v)
                   shared.inner_value_change(this, this.value, event)
                 }.bind(w),
-                event,
+                event
               )
             }
           }
@@ -216,7 +256,7 @@ export const MtbWidgets = {
               function () {
                 shared.inner_value_change(this, this.value, event)
               }.bind(this),
-              20,
+              20
             )
 
           app.canvas.setDirty(true)
@@ -265,7 +305,7 @@ export const MtbWidgets = {
         border,
         widgetY + border,
         widgetWidth - border * 2,
-        height - border * 2,
+        height - border * 2
       )
       const color = parseCss(this.value.default || this.value)
       if (!color) {
@@ -368,7 +408,7 @@ export const MtbWidgets = {
         })
         const widgetWidth = Math.max(
           width || this.width || 32,
-          dimensions.maxLineWidth,
+          dimensions.maxLineWidth
         )
         const widgetHeight = dimensions.textHeight * 1.5
         return [widgetWidth, widgetHeight]
@@ -392,7 +432,7 @@ export const MtbWidgets = {
       text-align: center;
       font-size: ${fontSize}px;
       color: var(--input-text);
-      line-height: 1em;
+      line-height: 0;
       font-family: monospace;
     `
     w.value = val
@@ -400,6 +440,119 @@ export const MtbWidgets = {
 
     return w
   },
+
+  AUDIO_UPLOAD: function (name, val) {
+    const w = {
+      name,
+      type: 'audio_upload',
+      value: val,
+      draw: function (ctx, node, widgetWidth, widgetY, height) {
+        const [cw, ch] = this.computeSize(widgetWidth)
+        shared.offsetDOMWidget(this, ctx, node, widgetWidth, widgetY, ch)
+      },
+      computeSize: function (width) {
+        if (width) {
+          return [width, 64]
+        }
+        return [128, 128]
+      },
+      onRemoved: function () {
+        if (this.inputEl) {
+          this.inputEl.remove()
+        }
+      },
+    }
+
+    const uploadFile = async (file, node) => {
+      try {
+        const body = new FormData()
+        body.append('name', 'loadAudio')
+        body.append('args', file)
+        const loadAudio = await api.fetchApi('/mtb/actions', {
+          method: 'POST',
+          body,
+        })
+
+        if (loadAudio.status === 200) {
+          const { result } = await loadAudio.json()
+          console.log('received from server', result)
+          console.log(
+            `Getting file /mtb/audio?filename=${encodeURIComponent(
+              result.name
+            )}`
+          )
+
+          w.value = result.name
+          addPlaybackWidget(
+            node,
+            result.name,
+            `/mtb/audio?filename=${encodeURIComponent(result.name)}`
+          )
+        } else {
+          alert(loadAudio.status + ' -' + loadAudio.statusText)
+        }
+        // if (resp.status === 200) {
+        //   const { name } = await resp.json()
+        //   pathWidget.value = name
+        //   addPlaybackWidget(
+        //     node,
+        //     name,
+        //     `/samplediffusion/audio?filename=${encodeURIComponent(name)}`
+        //   )
+        // } else {
+        //   alert(resp.status + ' - ' + resp.statusText)
+        // }
+      } catch (error) {
+        alert(error)
+        throw error
+      }
+    }
+
+    w.inputEl = document.createElement('div')
+    const hidden_input = document.createElement('input')
+    const label = document.createElement('label')
+
+    const uniqueId = 'input_' + Date.now()
+    Object.assign(hidden_input, {
+      type: 'file',
+      accept: 'audio/mpeg,audio/wav,audio/x-wav',
+      id: uniqueId,
+      style: `
+      width: 0.1px;
+      height: 0.1px;
+      opacity: 0;
+      overflow: hidden;
+      position: absolute;
+      z-index: -1;
+
+      `,
+      onchange: async () => {
+        if (hidden_input.files.length) {
+          console.log(hidden_input.files[0])
+          await uploadFile(hidden_input.files[0], this)
+        }
+      },
+    })
+
+    Object.assign(label, {
+      htmlFor: uniqueId,
+    })
+    label.textContent = 'Upload Audio File'
+    label.style = `
+    font-size: 1.25em;
+    font-weight: 700;
+    font-family: monospace;
+    padding:0.5em;
+    border-radius: 5px;
+    color: white;
+    background-color: #1e1e1e;
+    display: inline-block;
+    `
+    document.body.appendChild(w.inputEl)
+    w.inputEl.appendChild(hidden_input)
+    w.inputEl.appendChild(label)
+    return w
+  },
 }
 
 /**
@@ -425,7 +578,7 @@ const mtb_widgets = {
   setup: () => {
     app.ui.settings.addSetting({
       id: 'mtb.Debug.enabled',
-      name: '[⚡mtb] Enable Debug (py and js)',
+      name: '[mtb] Enable Debug (py and js)',
       type: 'boolean',
       defaultValue: false,
 
@@ -466,7 +619,7 @@ const mtb_widgets = {
 
         return {
           widget: node.addCustomWidget(
-            MtbWidgets.BOOL(inputName, inputData[1]?.default || false),
+            MtbWidgets.BOOL(inputName, inputData[1]?.default || false)
           ),
           minWidth: 150,
           minHeight: 30,
@@ -477,12 +630,26 @@ const mtb_widgets = {
         console.debug('Registering color')
         return {
           widget: node.addCustomWidget(
-            MtbWidgets.COLOR(inputName, inputData[1]?.default || '#ff0000'),
+            MtbWidgets.COLOR(inputName, inputData[1]?.default || '#ff0000')
           ),
           minWidth: 150,
           minHeight: 30,
         }
       },
+      AUDIO_UPLOAD: (node, inputName, inputData, app) => {
+        console.debug('Registering audio')
+        return {
+          widget: node.addCustomWidget(
+            MtbWidgets.AUDIO_UPLOAD.bind(node)(
+              inputName,
+              inputData[1]?.default || ''
+            )
+          ),
+          minWidth: 150,
+          minHeight: 30,
+        }
+      },
+
       // BBOX: (node, inputName, inputData, app) => {
       //     console.debug("Registering bbox")
       //     return {
@@ -502,6 +669,10 @@ const mtb_widgets = {
   async beforeRegisterNodeDef(nodeType, nodeData, app) {
     // const rinputs = nodeData.input?.required
 
+    if (!nodeData.name.endsWith('(mtb)')) {
+      return
+    }
+
     let has_custom = false
     if (nodeData.input && nodeData.input.required) {
       for (const i of Object.keys(nodeData.input.required)) {
@@ -569,14 +740,6 @@ const mtb_widgets = {
       }
     }
 
-    if (!nodeData.name.endsWith('(mtb)')) {
-      return
-    }
-    const deprecation = deprecated_nodes[nodeData.name.replace(' (mtb)', '')]
-
-    if (deprecation) {
-      shared.addDeprecation(nodeType, deprecation)
-    }
     //- Extending Python Nodes
     switch (nodeData.name) {
       case 'Psd Save (mtb)': {
@@ -585,7 +748,7 @@ const mtb_widgets = {
           type,
           index,
           connected,
-          link_info,
+          link_info
         ) {
           const r = onConnectionsChange
             ? onConnectionsChange.apply(this, arguments)
@@ -603,7 +766,7 @@ const mtb_widgets = {
             ? onNodeCreated.apply(this, arguments)
             : undefined
           const internal_count = this.widgets.find(
-            (w) => w.name === 'internal_count',
+            (w) => w.name === 'internal_count'
           )
           shared.hideWidgetForGood(this, internal_count)
           internal_count.afterQueued = function () {
@@ -643,24 +806,24 @@ const mtb_widgets = {
                 imgURLs = imgURLs.concat(
                   message.gif.map((params) => {
                     return api.apiURL(
-                      '/view?' + new URLSearchParams(params).toString(),
+                      '/view?' + new URLSearchParams(params).toString()
                     )
-                  }),
+                  })
                 )
               }
               if (message.apng) {
                 imgURLs = imgURLs.concat(
                   message.apng.map((params) => {
                     return api.apiURL(
-                      '/view?' + new URLSearchParams(params).toString(),
+                      '/view?' + new URLSearchParams(params).toString()
                     )
-                  }),
+                  })
                 )
               }
               let i = 0
               for (const img of imgURLs) {
                 const w = this.addCustomWidget(
-                  MtbWidgets.DEBUG_IMG(`${prefix}_${i}`, img),
+                  MtbWidgets.DEBUG_IMG(`${prefix}_${i}`, img)
                 )
                 w.parent = this
                 i++
@@ -688,12 +851,12 @@ const mtb_widgets = {
           this.changeMode(LiteGraph.ALWAYS)
 
           const raw_iteration = this.widgets.find(
-            (w) => w.name === 'raw_iteration',
+            (w) => w.name === 'raw_iteration'
           )
           const raw_loop = this.widgets.find((w) => w.name === 'raw_loop')
 
           const total_frames = this.widgets.find(
-            (w) => w.name === 'total_frames',
+            (w) => w.name === 'total_frames'
           )
           const loop_count = this.widgets.find((w) => w.name === 'loop_count')
 
@@ -703,12 +866,12 @@ const mtb_widgets = {
           raw_iteration._value = 0
 
           const value_preview = this.addCustomWidget(
-            MtbWidgets['DEBUG_STRING']('value_preview', 'Idle'),
+            MtbWidgets['DEBUG_STRING']('value_preview', 'Idle')
           )
           value_preview.parent = this
 
           const loop_preview = this.addCustomWidget(
-            MtbWidgets['DEBUG_STRING']('loop_preview', 'Iteration: Idle'),
+            MtbWidgets['DEBUG_STRING']('loop_preview', 'Iteration: Idle')
           )
           loop_preview.parent = this
 
@@ -726,7 +889,7 @@ const mtb_widgets = {
             'button',
             `Reset`,
             'reset',
-            onReset,
+            onReset
           )
 
           const run_button = this.addWidget('button', `Queue`, 'queue', () => {
@@ -736,7 +899,7 @@ const mtb_widgets = {
               `Started a queue of ${total_frames.value} frames (for ${
                 loop_count.value
               } loop, so ${total_frames.value * loop_count.value})`,
-              5000,
+              5000
             )
           })
 
@@ -773,7 +936,7 @@ const mtb_widgets = {
           type,
           index,
           connected,
-          link_info,
+          link_info
         ) {
           const r = onConnectionsChange
             ? onConnectionsChange.apply(this, arguments)
@@ -794,7 +957,7 @@ const mtb_widgets = {
             const input = this.addInput(
               `replacement_${this.widgets.length}`,
               'STRING',
-              '',
+              ''
             )
             console.log(input)
             this.addWidget('STRING', `replacement_${this.widgets.length}`, '')
@@ -811,7 +974,7 @@ const mtb_widgets = {
             'remove',
             function (value, widget, node) {
               console.log(`Button clicked: ${value}`, widget, node)
-            },
+            }
           )
 
           return r
@@ -852,7 +1015,7 @@ const mtb_widgets = {
                 if (style && style.length >= 1) {
                   if (style[0]) {
                     window.MTB?.notify?.(
-                      `Extracted positive from ${this.widgets[0].value}`,
+                      `Extracted positive from ${this.widgets[0].value}`
                     )
                     const tn = LiteGraph.createNode('Text box')
                     app.graph.add(tn)
@@ -860,7 +1023,7 @@ const mtb_widgets = {
                     tn.widgets[0].value = style[0]
                   } else {
                     window.MTB?.notify?.(
-                      `No positive to extract for ${this.widgets[0].value}`,
+                      `No positive to extract for ${this.widgets[0].value}`
                     )
                   }
                 }
@@ -873,7 +1036,7 @@ const mtb_widgets = {
                 if (style && style.length >= 2) {
                   if (style[1]) {
                     window.MTB?.notify?.(
-                      `Extracted negative from ${this.widgets[0].value}`,
+                      `Extracted negative from ${this.widgets[0].value}`
                     )
                     const tn = LiteGraph.createNode('Text box')
                     app.graph.add(tn)
@@ -881,7 +1044,7 @@ const mtb_widgets = {
                     tn.widgets[0].value = style[1]
                   } else {
                     window.MTB.notify(
-                      `No negative to extract for ${this.widgets[0].value}`,
+                      `No negative to extract for ${this.widgets[0].value}`
                     )
                   }
                 }
@@ -893,14 +1056,6 @@ const mtb_widgets = {
 
         break
       }
-      case 'Apply Text Template (mtb)': {
-        shared.setupDynamicConnections(nodeType, 'var', '*')
-        break
-      }
-      case 'Add To Playlist (mtb)': {
-        shared.setupDynamicConnections(nodeType, 'video', 'VIDEO')
-        break
-      }
       case 'Stack Images (mtb)':
       case 'Concat Images (mtb)': {
         shared.setupDynamicConnections(nodeType, 'image', 'IMAGE')
@@ -917,7 +1072,6 @@ const mtb_widgets = {
 
         break
       }
-      // TODO: remove this, recommend pythongoss's version that is much better
       case 'Math Expression (mtb)': {
         const onNodeCreated = nodeType.prototype.onNodeCreated
         nodeType.prototype.onNodeCreated = function () {
@@ -933,7 +1087,7 @@ const mtb_widgets = {
           type,
           index,
           connected,
-          link_info,
+          link_info
         ) {
           const r = onConnectionsChange
             ? onConnectionsChange.apply(this, arguments)
@@ -947,7 +1101,7 @@ const mtb_widgets = {
           //- infer type
           if (link_info) {
             const fromNode = this.graph._nodes.find(
-              (otherNode) => otherNode.id == link_info.origin_id,
+              (otherNode) => otherNode.id == link_info.origin_id
             )
             const type = fromNode.outputs[link_info.origin_slot].type
             this.inputs[index].type = type

web/note_plus.js

@@ -1,697 +0,0 @@
-import { app } from '../../scripts/app.js'
-import * as shared from './comfy_shared.js'
-import { infoLogger, successLogger, errorLogger } from './comfy_shared.js'
-
-const DEFAULT_CSS = ''
-const DEFAULT_HTML = `<p style='color:red;font-family:monospace'>
-    Note+
-</p>`
-const DEFAULT_MD = '## Note+'
-const DEFAULT_MODE = 'markdown'
-const DEFAULT_THEME = 'one_dark'
-
-const CSS_RESET = `
-* {
-  font-family: monospace;
-  line-height: 1.25em;
-}
-
-h1, h2, h3, h4, h5, h6 {
-  margin: 0;
-  padding: 0;
-  font-weight: normal;
-}
-
-p, ul, ol, dl, blockquote {
-  margin: 0.3em;
-  padding: 0;
-}
-
-
-ul, ol {
-  
-  padding-left: 1em;
-  
-}
-
-a {
-  color: inherit;
-  text-decoration: none;
-  pointer-events: all;
-  color: cyan;
-}
-
-img {
-  padding: 1em 0;
-  max-width: 100%;
-}
-
-iframe {
-  width: 100%;
-  height: auto;
-  border:none;
-  pointer-events:all;
-}
-
-blockquote {
-  border-left: 4px solid #ccc;
-  padding-left: 1em;
-  margin-left: 0;
-  font-style: italic;
-}
-
-pre, code {
-  font-family: monospace;
-}
-
-table {
-  border-collapse: collapse;
-  width: 100%;
-  border-bottom: 1px solid #000;
-  margin: 1em 0;
-}
-
-th, td {
-  border-left: 1px solid #000;
-  border-right: 1px solid #000;
-  padding: 8px;
-  text-align: left;
-}
-
-th {
-  border: 1px solid #000;
-
-  background-color: rgba(0,0,0,0.5);
-}
-
-input[type="checkbox"] {
-  margin-right: 10px;
-}
-
-`
-
-const themes = [
-  'ambiance',
-  'chaos',
-  'chrome',
-  'cloud9_day',
-  'cloud9_night',
-  'cloud9_night_low_color',
-  'cloud_editor',
-  'cloud_editor_dark',
-  'clouds',
-  'clouds_midnight',
-  'cobalt',
-  'crimson_editor',
-  'dawn',
-  'dracula',
-  'dreamweaver',
-  'eclipse',
-  'github',
-  'github_dark',
-  'gob',
-  'gruvbox',
-  'gruvbox_dark_hard',
-  'gruvbox_light_hard',
-  'idle_fingers',
-  'iplastic',
-  'katzenmilch',
-  'kr_theme',
-  'kuroir',
-  'merbivore',
-  'merbivore_soft',
-  'mono_industrial',
-  'monokai',
-  'nord_dark',
-  'one_dark',
-  'pastel_on_dark',
-  'solarized_dark',
-  'solarized_light',
-  'sqlserver',
-  'terminal',
-  'textmate',
-  'tomorrow',
-  'tomorrow_night',
-  'tomorrow_night_blue',
-  'tomorrow_night_bright',
-  'tomorrow_night_eighties',
-  'twilight',
-  'vibrant_ink',
-  'vscode',
-]
-class NotePlus extends LiteGraph.LGraphNode {
-  title = 'Note+ (mtb)'
-  category = 'mtb/utils'
-
-  // same values as the comfy note
-  color = LGraphCanvas.node_colors.yellow.color
-  bgcolor = LGraphCanvas.node_colors.yellow.bgcolor
-  groupcolor = LGraphCanvas.node_colors.yellow.groupcolor
-
-  constructor() {
-    super()
-    this.uuid = shared.makeUUID()
-
-    infoLogger('Constructing Note+ instance')
-    // - litegraph settings
-    this.collapsable = true
-    this.isVirtualNode = true
-    this.shape = LiteGraph.BOX_SHAPE
-    this.serialize_widgets = true
-
-    // - default values, serialization is done through widgets
-    this._raw_html = DEFAULT_MODE === 'html' ? DEFAULT_HTML : DEFAULT_MD
-
-    // - mardown converter
-    this.markdownConverter = new showdown.Converter({
-      tables: true,
-      strikethrough: true,
-      emoji: true,
-      ghCodeBlocks: true,
-      tasklists: true,
-      ghMentions: true,
-      smoothLivePreview: true,
-      simplifiedAutoLink: true,
-      parseImgDimensions: true,
-      openLinksInNewWindow: true,
-    })
-
-    // - state
-    this.live = true
-    this.calculated_height = 0
-
-    // - add widgets
-    const inner = document.createElement('div')
-    inner.style.margin = '0'
-    inner.style.padding = '0'
-    inner.style.pointerEvents = 'none'
-    this.html_widget = this.addDOMWidget('HTML', 'html', inner, {
-      setValue: (val) => {
-        this._raw_html = val
-      },
-      getValue: () => this._raw_html,
-      getMinHeight: () => this.calculated_height, // (the edit button),
-      hideOnZoom: false,
-    })
-
-    this.setupSerializationWidgets()
-    this.setupDialog()
-    this.loadAceEditor()
-  }
-
-  /**
-   *
-   * @param {CanvasRenderingContext2D} ctx
-   * @param {LGraphCanvas} graphcanvas
-   * @returns
-   */
-
-  onDrawForeground(ctx, _graphcanvas) {
-    if (this.flags.collapsed) return
-
-    // Define the size and position of the icon
-    const iconSize = 14 // Size of the icon
-    const iconMargin = 8 // Margin from the edges
-    const x = this.size[0] - iconSize - iconMargin
-    const y = iconMargin * 1.5
-
-    // Create a new Path2D object from SVG path data
-    const pencilPath = new Path2D(
-      'M21.28 6.4l-9.54 9.54c-.95.95-3.77 1.39-4.4.76-.63-.63-.2-3.45.75-4.4l9.55-9.55a2.58 2.58 0 1 1 3.64 3.65z',
-    )
-    const folderPath = new Path2D(
-      'M11 4H6a4 4 0 0 0-4 4v10a4 4 0 0 0 4 4h11c2.21 0 3-1.8 3-4v-5',
-    )
-
-    // Draw the paths
-    ctx.save()
-    ctx.translate(x, y) // Position the icon on the canvas
-    ctx.scale(iconSize / 32, iconSize / 32) // Scale the icon to the desired size
-    ctx.strokeStyle = 'rgba(255,255,255,0.3)'
-
-    ctx.lineCap = 'round'
-    ctx.lineJoin = 'round'
-
-    ctx.lineWidth = 2.4
-    ctx.stroke(pencilPath)
-    ctx.stroke(folderPath)
-    ctx.restore()
-  }
-  onMouseDown(_e, localPos, _graphcanvas) {
-    // Check if the click is within the pencil icon bounds
-    const iconSize = 14
-    const iconMargin = 8
-    const iconX = this.size[0] - iconSize - iconMargin
-    const iconY = iconMargin * 1.5
-
-    if (
-      localPos[0] > iconX &&
-      localPos[0] < iconX + iconSize &&
-      localPos[1] > iconY &&
-      localPos[1] < iconY + iconSize
-    ) {
-      // Pencil icon was clicked, open the editor
-      this.openEditorDialog()
-      return true // Return true to indicate the event was handled
-    }
-
-    return false // Return false to let the event propagate
-  }
-
-  setupSerializationWidgets() {
-    infoLogger('Setup Serializing widgets')
-
-    this.edit_mode_widget = this.addWidget(
-      'combo',
-      'Mode',
-      DEFAULT_MODE,
-      (me) => successLogger('Updating edit_mode', me),
-      {
-        values: ['html', 'markdown', 'raw'],
-      },
-    )
-    this.css_widget = this.addWidget('text', 'CSS', DEFAULT_CSS, (val) => {
-      successLogger(`Updating css ${val}`)
-    })
-    this.theme_widget = this.addWidget(
-      'text',
-      'Theme',
-      DEFAULT_THEME,
-      (val) => {
-        successLogger(`Setting theme ${val}`)
-      },
-    )
-
-    shared.hideWidgetForGood(this, this.edit_mode_widget)
-    shared.hideWidgetForGood(this, this.css_widget)
-    shared.hideWidgetForGood(this, this.theme_widget)
-  }
-  setupDialog() {
-    infoLogger('Setup dialog')
-    // this.addWidget('button', 'Edit', 'Edit', this.openEditorDialog.bind(this))
-
-    this.dialog = new app.ui.dialog.constructor()
-    this.dialog.element.classList.add('comfy-settings')
-
-    const closeButton = this.dialog.element.querySelector('button')
-    closeButton.textContent = 'CANCEL'
-    const saveButton = document.createElement('button')
-    saveButton.textContent = 'SAVE'
-    saveButton.onclick = () => {
-      this.closeEditorDialog(true)
-    }
-    closeButton.onclick = () => {
-      this.closeEditorDialog(false)
-    }
-    closeButton.before(saveButton)
-  }
-
-  teardownEditors() {
-    this.css_editor.destroy()
-    this.css_editor.container.remove()
-
-    this.html_editor.destroy()
-    this.html_editor.container.remove()
-  }
-
-  closeEditorDialog(accept) {
-    infoLogger('Closing editor dialog', accept)
-    if (accept) {
-      this.updateHTML(this.html_editor.getValue())
-      this.updateCSS(this.css_editor.getValue())
-    }
-    this.teardownEditors()
-    this.dialog.close()
-  }
-
-  openEditorDialog() {
-    infoLogger(`Current edit mode ${this.edit_mode_widget.value}`)
-    const container = document.createElement('div')
-
-    Object.assign(container.style, {
-      display: 'flex',
-      gap: '10px',
-      flexDirection: 'column',
-    })
-
-    const editorsContainer = document.createElement('div')
-    Object.assign(editorsContainer.style, {
-      display: 'flex',
-      gap: '10px',
-      flexDirection: 'row',
-    })
-
-    container.append(editorsContainer)
-
-    this.dialog.show('')
-    this.dialog.textElement.append(container)
-
-    const aceHTML = document.createElement('div')
-    aceHTML.id = 'noteplus-html-editor'
-    Object.assign(aceHTML.style, {
-      width: '300px',
-      height: '300px',
-      // backgroundColor: 'rgb(30,30,30)',
-      // color: 'whitesmoke',
-    })
-
-    editorsContainer.append(aceHTML)
-
-    const aceCSS = document.createElement('div')
-    aceCSS.id = 'noteplus-css-editor'
-    Object.assign(aceCSS.style, {
-      width: '300px',
-      height: '300px',
-      // backgroundColor: 'rgb(30,30,30)',
-      // color: 'whitesmoke',
-    })
-
-    editorsContainer.append(aceCSS)
-
-    const live_edit = document.createElement('input')
-    live_edit.type = 'checkbox'
-    live_edit.checked = this.live
-    live_edit.onchange = () => {
-      this.live = live_edit.checked
-    }
-
-    //- "Dynamic" elements
-    const firstButton = this.dialog.element.querySelector('button')
-    const syncUI = () => {
-      let convert_to_html =
-        this.dialog.element.querySelector('#convert-to-html')
-      if (this.edit_mode_widget.value === 'markdown') {
-        if (convert_to_html == null) {
-          convert_to_html = document.createElement('button')
-          convert_to_html.textContent = 'Convert to HTML (NO UNDO!)'
-          convert_to_html.id = 'convert-to-html'
-          convert_to_html.onclick = () => {
-            const select_mode = this.dialog.element.querySelector('#edit_mode')
-
-            const md = this.html_editor.getValue()
-            this.edit_mode_widget.value = 'html'
-            select_mode.value = 'html'
-            const html = this.markdownConverter.makeHtml(md)
-            this.html_widget.value = html
-            this.html_editor.setValue(html)
-            this.html_editor.session.setMode('ace/mode/html')
-            this.updateHTML(this.html_widget.value)
-
-            convert_to_html.remove()
-          }
-
-          firstButton.before(convert_to_html)
-        }
-      } else {
-        if (convert_to_html != null) {
-          convert_to_html.remove()
-          convert_to_html = null
-        }
-      }
-      select_mode.value = this.edit_mode_widget.value
-    }
-    //- combobox
-    let theme_select = this.dialog.element.querySelector('#theme_select')
-    if (!theme_select) {
-      infoLogger('Creating combobox for select')
-      theme_select = document.createElement('select')
-      theme_select.name = 'theme'
-      theme_select.id = 'theme_select'
-
-      const addOption = (label) => {
-        const option = document.createElement('option')
-        option.value = label
-        option.textContent = label
-        theme_select.append(option)
-      }
-      for (const t of themes) {
-        addOption(t)
-      }
-
-      theme_select.addEventListener('change', (event) => {
-        const val = event.target.value
-        this.setTheme(val)
-      })
-
-      container.prepend(theme_select)
-    }
-
-    theme_select.value = this.theme_widget.value
-
-    let select_mode = this.dialog.element.querySelector('#edit_mode')
-
-    if (!select_mode) {
-      infoLogger('Creating combobox for select')
-      select_mode = document.createElement('select')
-      select_mode.name = 'mode'
-      select_mode.id = 'edit_mode'
-
-      const addOption = (label) => {
-        const option = document.createElement('option')
-        option.value = label
-        option.textContent = label
-        select_mode.append(option)
-      }
-      addOption('markdown')
-      addOption('html')
-
-      select_mode.addEventListener('change', (event) => {
-        const val = event.target.value
-        this.edit_mode_widget.value = val
-        if (this.html_editor) {
-          this.html_editor.session.setMode(`ace/mode/${val}`)
-          this.updateHTML(this.html_editor.getValue())
-
-          syncUI()
-        }
-      })
-
-      container.append(select_mode)
-    }
-    select_mode.value = this.edit_mode_widget.value
-
-    syncUI()
-
-    const live_edit_label = document.createElement('label')
-    live_edit_label.textContent = 'Live Edit'
-
-    // add a tooltip
-    live_edit_label.title =
-      'When this is on, the editor will update the note+ whenever you change the text.'
-
-    live_edit_label.append(live_edit)
-
-    // select_mode.before(live_edit_label)
-    container.append(live_edit_label)
-
-    this.setupEditors()
-  }
-  loadAceEditor() {
-    shared
-      .loadScript(
-        'https://cdn.jsdelivr.net/npm/ace-builds@1.16.0/src-min-noconflict/ace.min.js',
-      )
-      .catch((e) => {
-        errorLogger(e)
-      })
-  }
-  onCreate() {
-    errorLogger('NotePlus onCreate')
-  }
-  configure(info) {
-    super.configure(info)
-    infoLogger('Restoring serialized values', info)
-    // - update view from serialzed data
-    this.html_widget.element.id = `note-plus-${this.uuid}`
-    this.setMode(this.edit_mode_widget.value)
-    this.setTheme(this.theme_widget.value)
-    this.updateHTML(this.html_widget.value)
-    this.updateCSS(this.css_widget.value)
-    this.setSize(info.size)
-  }
-  onNodeCreated() {
-    infoLogger('Node created', this.uuid)
-    this.html_widget.element.id = `note-plus-${this.uuid}`
-    this.setMode(this.edit_mode_widget.value)
-    this.setTheme(this.theme_widget.value)
-    this.updateHTML(this.html_widget.value) // widget is populated here since we called super
-    this.updateCSS(this.css_widget.value)
-  }
-  onRemoved() {
-    infoLogger('Node removed', this.uuid)
-  }
-  getExtraMenuOptions() {
-    const options = []
-    // {
-    //       content: string;
-    //       callback?: ContextMenuEventListener;
-    //       /** Used as innerHTML for extra child element */
-    //       title?: string;
-    //       disabled?: boolean;
-    //       has_submenu?: boolean;
-    //       submenu?: {
-    //           options: ContextMenuItem[];
-    //       } & IContextMenuOptions;
-    //       className?: string;
-    //   }
-    options.push({
-      content: `Set to ${
-        this.edit_mode_widget.value === 'html' ? 'markdown' : 'html'
-      }`,
-      callback: () => {
-        this.edit_mode_widget.value =
-          this.edit_mode_widget.value === 'html' ? 'markdown' : 'html'
-        this.updateHTML(this.html_widget.value)
-      },
-    })
-
-    return options
-  }
-
-  _setupEditor(editor) {
-    this.setTheme(this.theme_widget.value)
-
-    editor.setShowPrintMargin(false)
-    editor.session.setUseWrapMode(true)
-    editor.renderer.setShowGutter(false)
-    editor.session.setTabSize(4)
-    editor.session.setUseSoftTabs(true)
-    editor.setFontSize(14)
-    editor.setReadOnly(false)
-    editor.setHighlightActiveLine(false)
-    editor.setShowFoldWidgets(true)
-    return editor
-  }
-
-  setTheme(theme) {
-    this.theme_widget.value = theme
-    if (this.html_editor) {
-      this.html_editor.setTheme(`ace/theme/${theme}`)
-    }
-    if (this.css_editor) {
-      this.css_editor.setTheme(`ace/theme/${theme}`)
-    }
-  }
-
-  setMode(mode) {
-    this.edit_mode_widget.value = mode
-    if (this.html_editor) {
-      this.html_editor.session.setMode(`ace/mode/${mode}`)
-    }
-
-    this.updateHTML(this.html_widget.value)
-  }
-  setupEditors() {
-    infoLogger('NotePlus setupEditor')
-
-    this.html_editor = ace.edit('noteplus-html-editor')
-
-    this.css_editor = ace.edit('noteplus-css-editor')
-    this.css_editor.session.setMode('ace/mode/css')
-
-    this.setMode(DEFAULT_MODE)
-
-    this._setupEditor(this.html_editor)
-    this._setupEditor(this.css_editor)
-
-    this.css_editor.session.on('change', (_delta) => {
-      // delta.start, delta.end, delta.lines, delta.action
-      if (this.live) {
-        this.updateCSS(this.css_editor.getValue())
-      }
-    })
-
-    this.html_editor.session.on('change', (_delta) => {
-      // delta.start, delta.end, delta.lines, delta.action
-      if (this.live) {
-        this.updateHTML(this.html_editor.getValue())
-      }
-    })
-
-    this.html_editor.setValue(this.html_widget.value)
-    this.css_editor.setValue(this.css_widget.value)
-  }
-
-  scopeCss(css, scopeId) {
-    return css
-      .split('}')
-      .map((rule) => {
-        if (rule.trim() === '') {
-          return ''
-        }
-        const scopedRule = rule
-          .split('{')
-          .map((segment, index) => {
-            if (index === 0) {
-              return `#${scopeId} ${segment.trim()}`
-            }
-            return `{${segment.trim()}`
-          })
-          .join(' ')
-        return `${scopedRule}}`
-      })
-      .join('\n')
-  }
-  getCssDom() {
-    const styleTagId = `note-plus-stylesheet-${this.uuid}`
-
-    let styleTag = document.head.querySelector(`#${styleTagId}`)
-
-    if (!styleTag) {
-      styleTag = document.createElement('style')
-      styleTag.type = 'text/css'
-      styleTag.id = styleTagId
-      document.head.appendChild(styleTag)
-      infoLogger(`Creating note-plus-stylesheet-${this.uuid}`, styleTag)
-    }
-
-    return styleTag
-  }
-  calculateHeight() {
-    this.calculated_height = shared.calculateTotalChildrenHeight(
-      this.html_widget.element,
-    )
-    this.setDirtyCanvas(true, true)
-  }
-  updateCSS(css) {
-    infoLogger('NotePlus updateCSS')
-    // this.html_widget.element.style = css
-    const scopedCss = this.scopeCss(
-      `${CSS_RESET}\n${css}`,
-      `note-plus-${this.uuid}`,
-    )
-
-    const cssDom = this.getCssDom()
-    cssDom.innerHTML = scopedCss
-
-    this.css_widget.value = css
-    this.calculateHeight()
-    infoLogger('NotePlus updateCSS', this.calculated_height)
-    // this.setSize(this.computeSize())
-  }
-
-  updateHTML(val) {
-    const cleanHTML = DOMPurify.sanitize(val, { ADD_TAGS: ['iframe'] })
-    this.html_widget.value = cleanHTML
-
-    // update our widget preview
-    if (this.edit_mode_widget.value === 'html') {
-      this.html_widget.element.innerHTML = cleanHTML
-    } else if (this.edit_mode_widget.value === 'markdown') {
-      this.html_widget.element.innerHTML =
-        this.markdownConverter.makeHtml(cleanHTML)
-    }
-    this.calculateHeight()
-    // this.setSize(this.computeSize())
-  }
-}
-
-app.registerExtension({
-  name: 'mtb.noteplus',
-
-  registerCustomNodes() {
-    LiteGraph.registerNodeType('Note Plus (mtb)', NotePlus)
-
-    NotePlus.title_mode = LiteGraph.NO_TITLE
-  },
-})