commit 519d7bda8decc81f71d7c2e38dbf4742257423bb Author: meareabc <74286633+meareabc@users.noreply.github.com> Date: Wed Oct 28 09:03:12 2026 +0800 Add MiniMax H3 spatial guides and position editor diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..c235f5c --- /dev/null +++ b/.gitignore @@ -0,0 +1,7 @@ +__pycache__/ +*.py[cod] +.pytest_cache/ +*.egg-info/ +dist/ +build/ +.env diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..f288702 --- /dev/null +++ b/LICENSE @@ -0,0 +1,674 @@ + GNU GENERAL PUBLIC LICENSE + Version 3, 29 June 2007 + + Copyright (C) 2007 Free Software Foundation, Inc. + Everyone is permitted to copy and distribute verbatim copies + of this license document, but changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. 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If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/README.md b/README.md new file mode 100644 index 0000000..815714c --- /dev/null +++ b/README.md @@ -0,0 +1,48 @@ +# MiniMax H3 Spatial Guide + +Native-size image/video guides and a drag-to-position editor for ComfyUI's native MiniMax H3 model. No additional Python dependencies. + +![Drag the guide rectangle to choose its position](docs/position-editor.png) + +## Install + +Place this repository in `ComfyUI/custom_nodes/ComfyUI-MiniMaxH3-SpatialGuide`, restart ComfyUI, and refresh the browser. Requires a ComfyUI version with native MiniMax H3 support. If installing by URL through Manager, use this repository's Git URL. + +```bash +cd ComfyUI/custom_nodes +git clone https://github.com/meareabc/ComfyUI-MiniMaxH3-SpatialGuide.git +``` + +## Nodes + +**Add Spatial Guide for MiniMax H3** + +- Connect H3 `model`, `positive`, video `vae`, target AV `latent`, and guide frames `image`. +- The guide keeps its input dimensions. `x` and `y` locate its **top-left corner** in target pixels: positive x moves right, positive y moves down. +- Connect **both output MODEL and positive** to the sampler/guider. Connect the target latent directly to the sampler. +- For audio, chain a native Add Guide after this node with only its audio inputs connected. + +**MiniMax H3 Guide Position** + +- Set `guide_width`, `guide_height`, `canvas_width`, and `canvas_height`, or connect their INT inputs. +- Drag the blue guide rectangle; its size stays fixed. Hold Shift to snap movement to 32 pixels. Center and Origin buttons provide quick alignment. +- Connect its `x` and `y` outputs to Add Spatial Guide's corresponding inputs. Coordinates save with the workflow and can also be edited numerically. +- Linked Primitive values update the preview immediately. Dimensions computed by other backend nodes synchronize after execution; before the first run the preview uses the saved dimensions. Enter sizes directly for an exact preview before running. + +For a 640×480 guide on a 960×480 canvas, `x=0,y=0` leaves 320 pixels to the right; `x=160,y=0` centers it. For a 480×640 guide on a 480×960 canvas, use `x=0,y=160` to center it vertically. + +## Behavior and validation + +Video guides follow native Add Guide's valid lengths: 5, 22, 39… frames; batches below 5 frames use the first image. Nonmultiples of 32 are padded at the right/bottom with replicated edges, without scaling. This is positional conditioning, so generated pixels can change inside the guide region. + +CPU tests cover native-size coordinates, mixed guides/audio/references, clone isolation, registration, and a small native H3 forward. Full pretrained outpainting quality has not been validated. + +```bash +python -m unittest discover -s custom_nodes/ComfyUI-MiniMaxH3-SpatialGuide/tests -v +``` + +## 中文使用说明 + +重启并刷新后搜索 **MiniMax H3 Guide Position**，输入参考宽高和目标画布宽高，在预览里拖动蓝框。输出的 `x/y` 接到 **Add Spatial Guide for MiniMax H3**；表示参考区域左上角坐标，原点在目标画布左上角。按住 Shift 拖动可按 32 像素对齐，也可点击居中或左上归零。 + +Spatial Guide 的 **MODEL 和 positive 两个输出都要连接到采样器**，目标 latent 直接接采样器。音频可用原生 Add Guide 单独添加。 diff --git a/__init__.py b/__init__.py new file mode 100644 index 0000000..a02adfe --- /dev/null +++ b/__init__.py @@ -0,0 +1,158 @@ +import copy +import math + +import torch +import torch.nn.functional as F + +import comfy.conds +import comfy.patcher_extension +import nodes +from comfy.ldm.minimax.model import FRAME_PER_TOKEN +from comfy_api.latest import ComfyExtension, io + + +GUIDE_POSITION = "minimax_h3_spatial_guide" +WEB_DIRECTORY = "./web" + + +def spatial_guide_layout(native, keyframes): + _, _, height, width, _ = native.signature + frame_rows = (height // 2) * (width // 2) + spacing = 64.0 / math.sqrt(height * width) + guides = iter(kf for kf in keyframes if kf.get("latent") is not None) + position_parts, segments = [], [] + img_pos, img_update, audio_pos, audio_update = [], [], [], [] + cursor = 0 + for start, stop, kind in native.segments: + positions = native.position_ids[start:stop] + if kind == "cond": + guide = next(guides) + if GUIDE_POSITION in guide: + x, y = guide[GUIDE_POSITION] + _, _, time, h, w = guide["latent"].shape + grid = positions.new_empty(time, h // 2, w // 2, 3) + grid[..., 0] = positions[::frame_rows, 0][:, None, None] + hh = torch.arange(h // 2, dtype=positions.dtype, device=positions.device) + ww = torch.arange(w // 2, dtype=positions.dtype, device=positions.device) + grid[..., 1] = positions[0, 1] + (hh[:, None] + y / 32.0) * spacing + grid[..., 2] = positions[0, 2] + (ww[None, :] + x / 32.0) * spacing + positions = grid.reshape(-1, 3) + count = positions.shape[0] + position_parts.append(positions) + segments.append((cursor, cursor + count, kind)) + if kind in ("cond", "ref_img", "video"): + img_pos.append(torch.arange(cursor, cursor + count)) + img_update.append(torch.full((count,), kind == "video", dtype=torch.bool)) + elif kind in ("cond_audio", "ref_audio", "audio"): + audio_pos.append(torch.arange(cursor, cursor + count)) + audio_update.append(torch.full((count,), kind == "audio", dtype=torch.bool)) + cursor += count + + layout = copy.copy(native) + layout.position_ids = torch.cat(position_parts) + layout.segments = segments + layout.seq_len = cursor + layout.img_pos = torch.cat(img_pos) + layout.img_update = torch.cat(img_update) + layout.audio_pos = torch.cat(audio_pos) + layout.audio_update = torch.cat(audio_update) + return layout + + +def spatial_guide_sample(executor, model_wrap, *args, **kwargs): + for conditions in model_wrap.conds.values(): + for condition in conditions: + model_conds = condition["model_conds"] + payload = model_conds["minimax_payload"].cond + keyframes = payload.get("keyframes", []) + if any(GUIDE_POSITION in kf for kf in keyframes): + payload = dict(payload, layout=spatial_guide_layout(payload["layout"], keyframes)) + model_conds["minimax_payload"] = comfy.conds.CONDConstant(payload) + return executor(model_wrap, *args, **kwargs) + + +def patch_spatial_guides(model): + patched = model.clone() + wrapper_type = comfy.patcher_extension.WrappersMP.SAMPLER_SAMPLE + if not patched.get_wrappers(wrapper_type, GUIDE_POSITION): + patched.add_wrapper_with_key(wrapper_type, GUIDE_POSITION, spatial_guide_sample) + return patched + + +class MiniMaxH3AddSpatialGuide(io.ComfyNode): + @classmethod + def define_schema(cls): + return io.Schema( + node_id="MiniMaxH3AddSpatialGuide", + display_name="Add Spatial Guide for MiniMax H3", + category="model/conditioning/minimax", + description="Place an image or video guide at its original size within the target canvas. Connect both MODEL and positive outputs to the sampler.", + inputs=[ + io.Model.Input("model"), + io.Conditioning.Input("positive"), + io.Vae.Input("vae"), + io.Latent.Input("latent"), + io.Image.Input("image", tooltip="Guide frames at their original size. Video uses 5, 22, 39... frames, matching the native Add Guide node."), + io.Int.Input("frame_idx", default=0, min=-9999, max=9999), + io.Int.Input("x", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, + tooltip="Guide's left edge in target pixels. Use half the width difference to center it."), + io.Int.Input("y", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, + tooltip="Guide's top edge in target pixels. Use half the height difference to center it."), + ], + outputs=[io.Model.Output(), io.Conditioning.Output(display_name="positive")], + ) + + @classmethod + def execute(cls, model, positive, vae, latent, image, frame_idx=0, x=0, y=0) -> io.NodeOutput: + samples = latent["samples"] + if not samples.is_nested or len(samples.tensors) != 2 or samples.tensors[0].ndim != 5 or samples.tensors[0].shape[1] != 24: + raise ValueError("MiniMaxH3AddSpatialGuide expects a MiniMax H3 AV latent") + frame_count = sum(FRAME_PER_TOKEN[k % 5] for k in range(samples.tensors[0].shape[2])) + guide_frames = image.shape[0] + guide_frames = 1 if guide_frames < 5 else guide_frames - (guide_frames - 5) % 17 + resolved = frame_idx if frame_idx >= 0 else frame_count + frame_idx + if resolved < 0 or resolved + guide_frames > frame_count: + raise ValueError("a {} frame guide at frame_idx {} does not fit in the video's {} frames".format(guide_frames, frame_idx, frame_count)) + + frames = image[:guide_frames, ..., :3] + height, width = frames.shape[1:3] + # Complete VAE/DiT patches without scaling or cropping the source. + if height % 32 or width % 32: + frames = F.pad(frames.movedim(-1, 1), (0, -width % 32, 0, -height % 32), mode="replicate").movedim(1, -1) + keyframe = {"resolved_frame_index": resolved, "latent": vae.encode(frames), GUIDE_POSITION: (x, y)} + positive = [[cond, {**options, "minimax_keyframes": list(options.get("minimax_keyframes", [])) + [keyframe]}] + for cond, options in positive] + return io.NodeOutput(patch_spatial_guides(model), positive) + + +class MiniMaxH3GuidePosition(io.ComfyNode): + @classmethod + def define_schema(cls): + return io.Schema( + node_id="MiniMaxH3GuidePosition", + display_name="MiniMax H3 Guide Position", + category="model/conditioning/minimax", + description="Drag the guide rectangle inside the target canvas. Outputs the guide's top-left x/y in target pixels.", + inputs=[ + io.Int.Input("guide_width", default=640, min=1, max=nodes.MAX_RESOLUTION), + io.Int.Input("guide_height", default=480, min=1, max=nodes.MAX_RESOLUTION), + io.Int.Input("canvas_width", default=960, min=1, max=nodes.MAX_RESOLUTION), + io.Int.Input("canvas_height", default=480, min=1, max=nodes.MAX_RESOLUTION), + io.Int.Input("x", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, socketless=True), + io.Int.Input("y", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, socketless=True), + ], + outputs=[io.Int.Output(display_name="x"), io.Int.Output(display_name="y")], + ) + + @classmethod + def execute(cls, guide_width, guide_height, canvas_width, canvas_height, x, y) -> io.NodeOutput: + return io.NodeOutput(x, y, ui={"guide_size": [guide_width, guide_height], "canvas_size": [canvas_width, canvas_height]}) + + +class MiniMaxH3SpatialGuideExtension(ComfyExtension): + async def get_node_list(self): + return [MiniMaxH3AddSpatialGuide, MiniMaxH3GuidePosition] + + +async def comfy_entrypoint(): + return MiniMaxH3SpatialGuideExtension() diff --git a/docs/position-editor.png b/docs/position-editor.png new file mode 100644 index 0000000..53f9579 Binary files /dev/null and b/docs/position-editor.png differ diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..d87458a --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,14 @@ +[project] +name = "minimax-h3-spatial-guide" +version = "0.1.0" +description = "Native-size spatial guides and drag positioning for MiniMax H3 in ComfyUI" +readme = "README.md" +license = { file = "LICENSE" } +requires-python = ">=3.10" +dependencies = [] + +[project.urls] +Repository = "https://github.com/meareabc/ComfyUI-MiniMaxH3-SpatialGuide" + +[tool.comfy] +DisplayName = "MiniMax H3 Spatial Guide" diff --git a/tests/test_spatial_guide.py b/tests/test_spatial_guide.py new file mode 100644 index 0000000..4ce36d4 --- /dev/null +++ b/tests/test_spatial_guide.py @@ -0,0 +1,147 @@ +import asyncio +import importlib.util +import math +from pathlib import Path +from types import SimpleNamespace +import unittest +from unittest.mock import patch + +import torch + +import comfy.cli_args +comfy.cli_args.args.cpu = True + +import comfy.conds +from comfy.ldm.minimax.model import MiniMaxH3Model, PackedLayout, patchify_video +from comfy.model_patcher import ModelPatcher +from comfy.nested_tensor import NestedTensor + + +spec = importlib.util.spec_from_file_location("h3_spatial_guide", Path(__file__).resolve().parents[1] / "__init__.py") +guide = importlib.util.module_from_spec(spec) +spec.loader.exec_module(guide) + + +def segment_positions(layout, kind): + return [layout.position_ids[a:b] for a, b, k in layout.segments if k == kind] + + +class SpatialGuideTests(unittest.TestCase): + def test_native_size_and_offsets_match_target_region(self): + for x in (0, 160, 320): + keyframes = [{"resolved_frame_index": 0, "latent": torch.empty(1, 24, 7, 30, 40), guide.GUIDE_POSITION: (x, 0)}] + native = PackedLayout(8, 12, 30, 60, 65, keyframes=keyframes) + result = guide.spatial_guide_layout(native, keyframes) + target = segment_positions(native, "video")[0].reshape(12, 15, 30, 3) + expected = target[:7, :, x // 32:x // 32 + 20].reshape(-1, 3) + torch.testing.assert_close(segment_positions(result, "cond")[0], expected, rtol=0, atol=1e-13) + self.assertEqual(segment_positions(result, "cond")[0].shape[0], patchify_video(keyframes[0]["latent"]).shape[0]) + for kind in ("text", "audio", "video"): + torch.testing.assert_close(segment_positions(result, kind)[0], segment_positions(native, kind)[0], rtol=0, atol=0) + + def test_same_size_is_native_equivalent(self): + keyframes = [{"resolved_frame_index": 3, "latent": torch.empty(1, 24, 2, 6, 10), guide.GUIDE_POSITION: (0, 0)}] + native = PackedLayout(4, 7, 6, 10, 37, keyframes=keyframes) + result = guide.spatial_guide_layout(native, keyframes) + self.assertEqual(result.segments, native.segments) + self.assertEqual(result.signature, native.signature) + for name in ("position_ids", "img_pos", "img_update", "audio_pos", "audio_update"): + torch.testing.assert_close(getattr(result, name), getattr(native, name), rtol=0, atol=1e-13) + + def test_mixed_guides_audio_references_and_fractional_offsets(self): + keyframes = [ + {"resolved_frame_index": 0, "latent": torch.empty(1, 24, 2, 4, 6), guide.GUIDE_POSITION: (17, 3), "audio_latent": torch.empty(1, 32, 2, 8)}, + {"resolved_frame_index": 5, "latent": torch.empty(1, 24, 1, 6, 10)}, + {"resolved_frame_index": 7, "latent": torch.empty(1, 24, 1, 8, 12), guide.GUIDE_POSITION: (-4, 9)}, + ] + refs = [{"kind": "image", "latent_h": 4, "latent_w": 4}] + native = PackedLayout(4, 7, 6, 10, 37, keyframes=keyframes, refs=refs) + before = native.position_ids.clone() + result = guide.spatial_guide_layout(native, keyframes) + for original, changed in zip(native.segments, result.segments): + if original[2] != "cond": + torch.testing.assert_close(native.position_ids[original[0]:original[1]], result.position_ids[changed[0]:changed[1]], rtol=0, atol=0) + original_guides = segment_positions(native, "cond") + new_guides = segment_positions(result, "cond") + torch.testing.assert_close(new_guides[1], original_guides[1], rtol=0, atol=0) + expected_offset = torch.tensor([3, 17], dtype=torch.float64) * 2 / math.sqrt(6 * 10) + torch.testing.assert_close(new_guides[0][0, 1:] - original_guides[0][0, 1:], expected_offset) + self.assertEqual([p.shape[0] for p in new_guides], [12, 15, 24]) + self.assertEqual(result.img_update.sum().item(), 7 * 15) + self.assertEqual(result.img_pos.numel() + result.audio_pos.numel() + 4, result.seq_len) + torch.testing.assert_close(native.position_ids, before, rtol=0, atol=0) + + def test_node_preserves_pixels_and_model_patches_are_scoped(self): + model = ModelPatcher(torch.nn.Module(), load_device=torch.device("cpu"), offload_device=torch.device("cpu")) + images = torch.rand(24, 48, 65, 3) + encoded = [] + + def encode(frames): + encoded.append(frames) + return torch.zeros(1, 24, 7, frames.shape[1] // 16, frames.shape[2] // 16) + + positive = [[torch.zeros(1, 2, 8), {}], [torch.zeros(1, 3, 8), {"minimax_keyframes": [{"resolved_frame_index": 0}]}]] + latent = {"samples": NestedTensor([torch.zeros(1, 24, 12, 6, 10), torch.zeros(1, 32, 2, 65)])} + patched, output = guide.MiniMaxH3AddSpatialGuide.execute(model, positive, SimpleNamespace(encode=encode), latent, images, frame_idx=-39, x=17, y=3) + self.assertEqual(encoded[0].shape, (22, 64, 96, 3)) + torch.testing.assert_close(encoded[0][:, :48, :65], images[:22], rtol=0, atol=0) + torch.testing.assert_close(encoded[0][:, :48, 65:], images[:22, :, -1:].expand(-1, -1, 31, -1), rtol=0, atol=0) + self.assertNotIn("minimax_keyframes", positive[0][1]) + self.assertEqual(len(positive[1][1]["minimax_keyframes"]), 1) + self.assertEqual([len(c[1]["minimax_keyframes"]) for c in output], [1, 2]) + self.assertNotIn("noise_mask", latent) + self.assertEqual(model.wrappers, {}) + chained = guide.patch_spatial_guides(patched) + wrapper_type = comfy.patcher_extension.WrappersMP.SAMPLER_SAMPLE + self.assertEqual(len(chained.get_wrappers(wrapper_type, guide.GUIDE_POSITION)), 1) + keyframes = output[0][1]["minimax_keyframes"] + native = PackedLayout(2, 12, 6, 10, 65, keyframes=keyframes) + payload = {"keyframes": keyframes, "layout": native} + negative = {"layout": native} + sampler_model = SimpleNamespace(conds={ + "positive": [{"model_conds": {"minimax_payload": comfy.conds.CONDConstant(payload)}}], + "negative": [{"model_conds": {"minimax_payload": comfy.conds.CONDConstant(negative)}}], + }) + executor = comfy.patcher_extension.WrapperExecutor.new_executor( + lambda wrapped, value: value, chained.get_wrappers(wrapper_type, guide.GUIDE_POSITION)) + self.assertEqual(executor.execute(sampler_model, 123), 123) + result = sampler_model.conds["positive"][0]["model_conds"]["minimax_payload"].cond["layout"] + self.assertEqual(segment_positions(result, "cond")[0].shape[0], 7 * 2 * 3) + self.assertIs(payload["layout"], native) + self.assertIs(sampler_model.conds["negative"][0]["model_conds"]["minimax_payload"].cond, negative) + + def test_small_native_model_accepts_local_guide(self): + torch.manual_seed(3) + model = MiniMaxH3Model(hidden_size=8, num_layers=1, token_refiner_num_layers=0, + num_attention_heads=1, attention_head_dim=8, ffn_hidden_size=16, + timestep_input_dim=4, time_embed_hidden_size=8, time_embed_dim=4, + text_dim=8, rope_inv_freq_len=1, dtype=torch.float32, + device=torch.device("cpu"), operations=torch.nn) + model.rope.inv_freq.fill_(1.0) + video = torch.randn(1, 24, 2, 4, 6) + audio = torch.randn(1, 32, 2, 5) + context = torch.randn(1, 3, 8) + keyframes = [{"resolved_frame_index": 0, "latent": torch.randn(1, 24, 2, 2, 4), guide.GUIDE_POSITION: (32, 16)}] + native = PackedLayout(3, 2, 4, 6, 5, keyframes=keyframes) + payload = {"layout": guide.spatial_guide_layout(native, keyframes), "cond_video_latents": [keyframes[0]["latent"]]} + with patch("comfy.model_management.in_training", True): + result = model._forward([video, audio], torch.tensor([500.0]), context, minimax_payload=payload) + for actual, original in zip(result, (video, audio)): + self.assertEqual(actual.shape, original.shape) + self.assertTrue(torch.isfinite(actual).all()) + + def test_extension_registers_v3_node(self): + extension = asyncio.run(guide.comfy_entrypoint()) + self.assertEqual(asyncio.run(extension.get_node_list()), [guide.MiniMaxH3AddSpatialGuide, guide.MiniMaxH3GuidePosition]) + self.assertEqual(guide.MiniMaxH3AddSpatialGuide.define_schema().node_id, "MiniMaxH3AddSpatialGuide") + + def test_position_outputs_pixel_coordinates_unchanged(self): + result = guide.MiniMaxH3GuidePosition.execute(640, 480, 960, 480, 160, -17) + self.assertEqual(result.result, (160, -17)) + self.assertEqual(result.ui, {"guide_size": [640, 480], "canvas_size": [960, 480]}) + schema = guide.MiniMaxH3GuidePosition.define_schema() + self.assertEqual([output.display_name for output in schema.outputs], ["x", "y"]) + + +if __name__ == "__main__": + unittest.main() diff --git a/web/guide_position.js b/web/guide_position.js new file mode 100644 index 0000000..b5588a0 --- /dev/null +++ b/web/guide_position.js @@ -0,0 +1,259 @@ +import { app } from "../../scripts/app.js"; + +const DIMENSIONS = ["guide_width", "guide_height", "canvas_width", "canvas_height"]; +const HEIGHT = 290; + +function widget(node, name) { + return node.widgets?.find((item) => item.name === name); +} + +function inputValue(node, name, visited = new Set()) { + if (visited.has(node)) return undefined; + visited = new Set(visited).add(node); + const slot = node.inputs?.findIndex((input) => input.name === name) ?? -1; + if (slot < 0 || node.inputs[slot].link == null) return widget(node, name)?.value; + const source = node.getInputNode(slot); + const link = node.getInputLink(slot); + if (!source || !link) return undefined; + const type = source.comfyClass || source.type; + if (type === "ComfySwitchNode") { + const selected = inputValue(source, "switch", visited); + return selected == null ? undefined : inputValue(source, selected ? "on_true" : "on_false", visited); + } + if (type === "Reroute") return inputValue(source, source.inputs[0].name, visited); + if (["PrimitiveInt", "PrimitiveBoolean", "PrimitiveNode", "easy int"].includes(type)) { + return inputValue(source, "value", visited); + } + return undefined; +} + +function createPositionEditor(node) { + const root = document.createElement("div"); + root.className = "h3-guide-position"; + root.style.cssText = "width:100%;height:290px;display:flex;flex-direction:column;gap:6px;box-sizing:border-box;padding:6px;color:#dce5ef;font:12px sans-serif;"; + const canvas = document.createElement("canvas"); + canvas.style.cssText = "width:100%;height:218px;flex:1;min-height:100px;border:1px solid #435066;border-radius:5px;box-sizing:border-box;touch-action:none;cursor:grab;"; + canvas.setAttribute("aria-label", "Drag guide position / 拖动参考区域"); + const row = document.createElement("div"); + row.style.cssText = "display:flex;gap:6px;align-items:center;"; + const status = document.createElement("div"); + status.style.cssText = "white-space:nowrap;font-size:11px;color:#a9b8cb;min-height:14px;"; + const coordinates = document.createElement("span"); + coordinates.style.marginLeft = "auto"; + const context = canvas.getContext("2d"); + let view; + let drag; + let liveKey; + let frame; + let removed = false; + + function dimensions() { + const values = DIMENSIONS.map((name, index) => { + const linked = inputValue(node, name); + const stored = node.properties?.h3GuideSize?.[index]; + return Number(linked ?? stored ?? widget(node, name)?.value); + }); + return values.every((value) => Number.isFinite(value) && value > 0) ? values : null; + } + + function position() { + return [Number(widget(node, "x").value), Number(widget(node, "y").value)]; + } + + function setPosition(x, y) { + for (const [name, value] of [["x", x], ["y", y]]) { + const target = widget(node, name); + target.value = Math.max(target.options?.min ?? -16384, Math.min(target.options?.max ?? 16384, Math.round(value))); + target.callback?.(target.value); + } + node.graph?.setDirtyCanvas(true, true); + draw(); + } + + function draw() { + if (removed) return; + const bounds = canvas.getBoundingClientRect(); + if (!bounds.width || !bounds.height) return; + const dpr = window.devicePixelRatio || 1; + const width = Math.round(bounds.width * dpr); + const height = Math.round(bounds.height * dpr); + if (canvas.width !== width || canvas.height !== height) { + canvas.width = width; + canvas.height = height; + } + context.setTransform(dpr, 0, 0, dpr, 0, 0); + context.fillStyle = "#111923"; + context.fillRect(0, 0, bounds.width, bounds.height); + const sizes = dimensions(); + if (!sizes) { + status.textContent = "请填写参考宽高和画布宽高 / Enter dimensions"; + return; + } + const [gw, gh, cw, ch] = sizes; + const [x, y] = position(); + if (!drag) { + const left = Math.min(0, x), top = Math.min(0, y); + const right = Math.max(cw, x + gw), bottom = Math.max(ch, y + gh); + const scale = Math.min((bounds.width - 36) / (right - left), (bounds.height - 36) / (bottom - top)); + view = { scale, ox: (bounds.width - (right - left) * scale) / 2 - left * scale, + oy: (bounds.height - (bottom - top) * scale) / 2 - top * scale }; + } + const { scale, ox, oy } = view; + context.fillStyle = "#233247"; + context.fillRect(ox, oy, cw * scale, ch * scale); + context.strokeStyle = "#7d8fa8"; + context.lineWidth = 1; + context.strokeRect(ox, oy, cw * scale, ch * scale); + context.save(); + context.beginPath(); + context.rect(ox, oy, cw * scale, ch * scale); + context.clip(); + context.strokeStyle = "#384b62"; + for (let i = 1; i < 3; i++) { + context.beginPath(); + context.moveTo(ox + cw * scale * i / 3, oy); + context.lineTo(ox + cw * scale * i / 3, oy + ch * scale); + context.moveTo(ox, oy + ch * scale * i / 3); + context.lineTo(ox + cw * scale, oy + ch * scale * i / 3); + context.stroke(); + } + context.restore(); + context.fillStyle = "rgba(64, 164, 217, 0.35)"; + context.fillRect(ox + x * scale, oy + y * scale, gw * scale, gh * scale); + context.strokeStyle = "#65d5ff"; + context.lineWidth = 2; + context.strokeRect(ox + x * scale, oy + y * scale, gw * scale, gh * scale); + context.fillStyle = "#d2f5ff"; + context.font = "12px sans-serif"; + context.textAlign = "center"; + context.fillText("Guide", ox + (x + gw / 2) * scale, oy + (y + gh / 2) * scale + 4); + coordinates.textContent = `x ${x} · y ${y}`; + const unresolved = DIMENSIONS.some((name) => inputValue(node, name) == null); + status.textContent = `Guide ${gw}×${gh} → ${cw}×${ch}${unresolved ? " · 连线尺寸运行后同步" : ""}`; + } + + function button(label, action) { + const element = document.createElement("button"); + element.type = "button"; + element.textContent = label; + element.style.cssText = "background:#26364b;color:#e1efff;border:1px solid #506783;border-radius:4px;padding:4px 8px;cursor:pointer;"; + element.addEventListener("click", () => { + const sizes = dimensions(); + if (!sizes) return; + node.graph?.beforeChange(); + action(sizes); + node.graph?.afterChange(); + }); + row.appendChild(element); + } + button("居中 / Center", ([gw, gh, cw, ch]) => setPosition((cw - gw) / 2, (ch - gh) / 2)); + button("左上 / Origin", () => setPosition(0, 0)); + row.appendChild(coordinates); + root.append(canvas, row, status); + root.title = "拖动蓝框调整左上角坐标；按住 Shift 以 32 像素对齐。"; + for (const type of ["pointerdown", "pointerup", "mousedown", "mouseup", "click", "dblclick"]) { + root.addEventListener(type, (event) => event.stopPropagation()); + } + canvas.addEventListener("pointerdown", (event) => { + if (event.button !== 0 || !view || !dimensions()) return; + const bounds = canvas.getBoundingClientRect(); + const [x, y] = position(); + const [gw, gh] = dimensions(); + const px = (event.clientX - bounds.left - view.ox) / view.scale; + const py = (event.clientY - bounds.top - view.oy) / view.scale; + if (px < x || py < y || px > x + gw || py > y + gh) return; + event.preventDefault(); + node.graph?.beforeChange(); + drag = { id: event.pointerId, x, y, px: event.clientX, py: event.clientY }; + canvas.setPointerCapture(event.pointerId); + canvas.style.cursor = "grabbing"; + }); + canvas.addEventListener("pointermove", (event) => { + if (!drag || event.pointerId !== drag.id) return; + const step = event.shiftKey ? 32 : 1; + setPosition(Math.round((drag.x + (event.clientX - drag.px) / view.scale) / step) * step, + Math.round((drag.y + (event.clientY - drag.py) / view.scale) / step) * step); + }); + function endDrag() { + if (!drag) return; + drag = null; + canvas.style.cursor = "grab"; + node.graph?.afterChange(); + draw(); + } + canvas.addEventListener("lostpointercapture", endDrag); + canvas.addEventListener("pointerup", endDrag); + canvas.addEventListener("pointercancel", endDrag); + + const domWidget = node.addDOMWidget("guide_position_preview", "div", root, { + serialize: false, hideOnZoom: false, + getMinHeight: () => HEIGHT, getMaxHeight: () => HEIGHT, getHeight: () => HEIGHT, + }); + domWidget.computeSize = (width) => [width, HEIGHT]; + const observer = new ResizeObserver(draw); + observer.observe(canvas); + for (const name of [...DIMENSIONS, "x", "y"]) { + const target = widget(node, name); + const original = target.callback; + target.callback = function (...args) { + const result = original?.apply(this, args); + draw(); + return result; + }; + } + // Linked primitives may change without calling this node's widget callbacks. + function refresh() { + if (removed) return; + const bounds = canvas.getBoundingClientRect(); + const key = JSON.stringify([dimensions(), position(), bounds.width, bounds.height]); + if (key !== liveKey) { + liveKey = key; + draw(); + } + frame = requestAnimationFrame(refresh); + } + frame = requestAnimationFrame(refresh); + node.setSize([Math.max(node.size[0], 390), Math.max(node.size[1], node.computeSize()[1])]); + return { + draw, + remove() { + removed = true; + cancelAnimationFrame(frame); + observer.disconnect(); + }, + }; +} + +app.registerExtension({ + name: "MiniMaxH3.SpatialGuidePosition", + async beforeRegisterNodeDef(nodeType, nodeData) { + if (nodeData.name !== "MiniMaxH3GuidePosition") return; + const created = nodeType.prototype.onNodeCreated; + nodeType.prototype.onNodeCreated = function (...args) { + const result = created?.apply(this, args); + this.h3PositionEditor = createPositionEditor(this); + return result; + }; + const configured = nodeType.prototype.onConfigure; + nodeType.prototype.onConfigure = function (...args) { + const result = configured?.apply(this, args); + requestAnimationFrame(() => this.h3PositionEditor?.draw()); + return result; + }; + const executed = nodeType.prototype.onExecuted; + nodeType.prototype.onExecuted = function (message, ...args) { + const result = executed?.call(this, message, ...args); + if (message.guide_size && message.canvas_size) { + this.properties ??= {}; + this.properties.h3GuideSize = [...message.guide_size, ...message.canvas_size]; + this.h3PositionEditor?.draw(); + } + return result; + }; + const removed = nodeType.prototype.onRemoved; + nodeType.prototype.onRemoved = function (...args) { + this.h3PositionEditor?.remove(); + return removed?.apply(this, args); + }; + }, +});