diff --git a/README.en.md b/README.en.md index ecfe974..5d4ee02 100644 --- a/README.en.md +++ b/README.en.md @@ -47,6 +47,7 @@ you need to run `pip install -r requirements.txt` to install python dependencies **v1.1.1 (2024/3/16)** +- Adjust all widget names named seed_num to seed - Remove forced **control_before_generate** settings。 If you want to use control_before_generate, change widget_value_control_mode to before in system settings - Added `easy imageRemBg` - The default is BriaAI's RMBG-1.4 model, which removes the background effect more and faster diff --git a/README.md b/README.md index 2ccb90f..723537f 100644 --- a/README.md +++ b/README.md @@ -36,6 +36,7 @@ **v1.1.1 (2024/3/16)** +- 将所有 **seed_num** 调整回 **seed** - 修补官方BUG: 当control_mode为before 在首次加载页面时未修改节点中widget名称为 control_before_generate - 去除强制**control_before_generate**设定 - 增加 `easy imageRemBg` - 默认为BriaAI的RMBG-1.4模型, 移除背景效果更加，速度更快 diff --git a/py/easyNodes.py b/py/easyNodes.py index aff6403..1fd92bd 100644 --- a/py/easyNodes.py +++ b/py/easyNodes.py @@ -10,7 +10,7 @@ from urllib.request import urlopen from PIL import Image from server import PromptServer -from nodes import MAX_RESOLUTION, LatentFromBatch, RepeatLatentBatch, NODE_CLASS_MAPPINGS as ALL_NODE_CLASS_MAPPINGS, ConditioningSetMask, ConditioningConcat, CLIPTextEncode +from nodes import MAX_RESOLUTION, LatentFromBatch, RepeatLatentBatch, NODE_CLASS_MAPPINGS as ALL_NODE_CLASS_MAPPINGS, ConditioningSetMask, ConditioningConcat, CLIPTextEncode, VAEEncodeForInpaint from .config import MAX_SEED_NUM, BASE_RESOLUTIONS, RESOURCES_DIR, INPAINT_DIR, FOOOCUS_STYLES_DIR, FOOOCUS_INPAINT_HEAD, FOOOCUS_INPAINT_PATCH from .log import log_node_info, log_node_error, log_node_warn from .wildcards import process_with_loras, get_wildcard_list, process @@ -78,7 +78,7 @@ class wildcardsPrompt: "text": ("STRING", {"default": "", "multiline": True, "dynamicPrompts": False, "placeholder": "(Support Lora Block Weight and wildcard)"}), "Select to add LoRA": (["Select the LoRA to add to the text"] + folder_paths.get_filename_list("loras"),), "Select to add Wildcard": (["Select the Wildcard to add to the text"] + wildcard_list,), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO", "my_unique_id": "UNIQUE_ID"}, } @@ -93,15 +93,15 @@ class wildcardsPrompt: @staticmethod def main(*args, **kwargs): prompt = kwargs["prompt"] if "prompt" in kwargs else None - seed_num = kwargs["seed_num"] + seed = kwargs["seed"] # Clean loaded_objects if prompt: easyCache.update_loaded_objects(prompt) text = kwargs['text'] - populated_text = process(text, seed_num) - return {"ui": {"value": [seed_num]}, "result": (text, populated_text)} + populated_text = process(text, seed) + return {"ui": {"value": [seed]}, "result": (text, populated_text)} # 负面提示词 class negativePrompt: @@ -455,7 +455,7 @@ class latentNoisy: "start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}), "end_at_step": ("INT", {"default": 10000, "min": 1, "max": 10000}), "source": (["CPU", "GPU"],), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": 0xffffffffffffffff}), + "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}), }, "optional": { "pipe": ("PIPE_LINE",), @@ -469,7 +469,7 @@ class latentNoisy: CATEGORY = "EasyUse/Latent" - def run(self, sampler_name, scheduler, steps, start_at_step, end_at_step, source, seed_num, pipe=None, optional_model=None, optional_latent=None): + def run(self, sampler_name, scheduler, steps, start_at_step, end_at_step, source, seed, pipe=None, optional_model=None, optional_latent=None): model = optional_model if optional_model is not None else pipe["model"] batch_size = pipe["loader_settings"]["batch_size"] empty_latent_height = pipe["loader_settings"]["empty_latent_height"] @@ -478,7 +478,7 @@ class latentNoisy: if optional_latent is not None: samples = optional_latent else: - torch.manual_seed(seed_num) + torch.manual_seed(seed) if source == "CPU": device = "cpu" else: @@ -596,21 +596,21 @@ class easySeed: def INPUT_TYPES(s): return { "required": { - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO", "my_unique_id": "UNIQUE_ID"}, } - RETURN_TYPES = ("INT:seed",) - RETURN_NAMES = ("seed_num",) + RETURN_TYPES = ("INT",) + RETURN_NAMES = ("seed",) FUNCTION = "doit" CATEGORY = "EasyUse/Seed" OUTPUT_NODE = True - def doit(self, seed_num=0, prompt=None, extra_pnginfo=None, my_unique_id=None): - return seed_num, + def doit(self, seed=0, prompt=None, extra_pnginfo=None, my_unique_id=None): + return seed, # 全局随机种 class globalSeed: @@ -1744,7 +1744,7 @@ class samplerSettings: "sampler_name": (comfy.samplers.KSampler.SAMPLERS,), "scheduler": (comfy.samplers.KSampler.SCHEDULERS,), "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional": { "image_to_latent": ("IMAGE",), @@ -1761,7 +1761,7 @@ class samplerSettings: FUNCTION = "settings" CATEGORY = "EasyUse/PreSampling" - def settings(self, pipe, steps, cfg, sampler_name, scheduler, denoise, seed_num, image_to_latent=None, latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, steps, cfg, sampler_name, scheduler, denoise, seed, image_to_latent=None, latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): # 图生图转换 vae = pipe["vae"] batch_size = pipe["loader_settings"]["batch_size"] if "batch_size" in pipe["loader_settings"] else 1 @@ -1785,7 +1785,7 @@ class samplerSettings: "samples": samples, "images": images, - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -1800,7 +1800,7 @@ class samplerSettings: del pipe - return {"ui": {"value": [seed_num]}, "result": (new_pipe,)} + return {"ui": {"value": [seed]}, "result": (new_pipe,)} # 预采样设置（高级） class samplerSettingsAdvanced: @@ -1819,7 +1819,7 @@ class samplerSettingsAdvanced: "start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}), "end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000}), "add_noise": (["enable", "disable"],), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional": { "image_to_latent": ("IMAGE",), @@ -1836,7 +1836,7 @@ class samplerSettingsAdvanced: FUNCTION = "settings" CATEGORY = "EasyUse/PreSampling" - def settings(self, pipe, steps, cfg, sampler_name, scheduler, start_at_step, end_at_step, add_noise, seed_num, image_to_latent=None, latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, steps, cfg, sampler_name, scheduler, start_at_step, end_at_step, add_noise, seed, image_to_latent=None, latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): # 图生图转换 vae = pipe["vae"] batch_size = pipe["loader_settings"]["batch_size"] if "batch_size" in pipe["loader_settings"] else 1 @@ -1860,7 +1860,7 @@ class samplerSettingsAdvanced: "samples": samples, "images": images, - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -1877,7 +1877,7 @@ class samplerSettingsAdvanced: del pipe - return {"ui": {"value": [seed_num]}, "result": (new_pipe,)} + return {"ui": {"value": [seed]}, "result": (new_pipe,)} # 预采样设置（噪声注入） class samplerSettingsNoiseIn: @@ -1895,7 +1895,7 @@ class samplerSettingsNoiseIn: "sampler_name": (comfy.samplers.KSampler.SAMPLERS,), "scheduler": (comfy.samplers.KSampler.SCHEDULERS,), "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional": { "optional_noise_seed": ("INT",{"forceInput": True}), @@ -1964,18 +1964,18 @@ class samplerSettingsNoiseIn: except: return None - def settings(self, pipe, factor, steps, cfg, sampler_name, scheduler, denoise, seed_num, optional_noise_seed=None, optional_latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, factor, steps, cfg, sampler_name, scheduler, denoise, seed, optional_noise_seed=None, optional_latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): latent = optional_latent if optional_latent is not None else pipe["samples"] model = pipe["model"] # generate base noise batch_size, _, height, width = latent["samples"].shape - generator = torch.manual_seed(seed_num) + generator = torch.manual_seed(seed) base_noise = torch.randn((1, 4, height, width), dtype=torch.float32, device="cpu", generator=generator).repeat(batch_size, 1, 1, 1).cpu() # generate variation noise - if optional_noise_seed is None or optional_noise_seed == seed_num: - optional_noise_seed = seed_num+1 + if optional_noise_seed is None or optional_noise_seed == seed: + optional_noise_seed = seed+1 generator = torch.manual_seed(optional_noise_seed) variation_noise = torch.randn((batch_size, 4, height, width), dtype=torch.float32, device="cpu", generator=generator).cpu() @@ -2015,7 +2015,7 @@ class samplerSettingsNoiseIn: "samples": work_latent, "images": pipe['images'], - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -2052,7 +2052,7 @@ class sdTurboSettings: "unsharp_kernel_size": ("INT", {"default": 3, "min": 1, "max": 21, "step": 1}), "unsharp_sigma": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 10.0, "step": 0.01, "round": False}), "unsharp_strength": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 10.0, "step": 0.01, "round": False}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO", "my_unique_id": "UNIQUE_ID"}, } @@ -2064,7 +2064,7 @@ class sdTurboSettings: FUNCTION = "settings" CATEGORY = "EasyUse/PreSampling" - def settings(self, pipe, steps, cfg, sampler_name, eta, s_noise, upscale_ratio, start_step, end_step, upscale_n_step, unsharp_kernel_size, unsharp_sigma, unsharp_strength, seed_num, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, steps, cfg, sampler_name, eta, s_noise, upscale_ratio, start_step, end_step, upscale_n_step, unsharp_kernel_size, unsharp_sigma, unsharp_strength, seed, prompt=None, extra_pnginfo=None, my_unique_id=None): model = pipe['model'] # sigma timesteps = torch.flip(torch.arange(1, 11) * 100 - 1, (0,))[:steps] @@ -2110,7 +2110,7 @@ class sdTurboSettings: "samples": pipe["samples"], "images": pipe["images"], - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -2125,7 +2125,7 @@ class sdTurboSettings: del pipe - return {"ui": {"value": [seed_num]}, "result": (new_pipe,)} + return {"ui": {"value": [seed]}, "result": (new_pipe,)} # cascade预采样参数 @@ -2145,7 +2145,7 @@ class cascadeSettings: "sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"default":"euler_ancestral"}), "scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"default":"simple"}), "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional": { "image_to_latent_c": ("IMAGE",), @@ -2161,7 +2161,7 @@ class cascadeSettings: FUNCTION = "settings" CATEGORY = "EasyUse/PreSampling" - def settings(self, pipe, encode_vae_name, decode_vae_name, steps, cfg, sampler_name, scheduler, denoise, seed_num, model=None, image_to_latent_c=None, latent_c=None, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, encode_vae_name, decode_vae_name, steps, cfg, sampler_name, scheduler, denoise, seed, model=None, image_to_latent_c=None, latent_c=None, prompt=None, extra_pnginfo=None, my_unique_id=None): images, samples_c = None, None samples = pipe['samples'] batch_size = pipe["loader_settings"]["batch_size"] if "batch_size" in pipe["loader_settings"] else 1 @@ -2211,7 +2211,7 @@ class cascadeSettings: "samples": samples, "images": images, - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -2230,7 +2230,7 @@ class cascadeSettings: del pipe - return {"ui": {"value": [seed_num]}, "result": (new_pipe,)} + return {"ui": {"value": [seed]}, "result": (new_pipe,)} # layerDiffusion预采样参数 class layerDiffusionSettings: @@ -2250,11 +2250,12 @@ class layerDiffusionSettings: "sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"default": "euler_ancestral"}), "scheduler": (comfy.samplers.KSampler.SCHEDULERS, {"default": "simple"}), "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional": { "image": ("IMAGE",), "blended_image": ("IMAGE",), + "mask": ("MASK",), # "latent": ("LATENT",), # "blended_latent": ("LATENT",), }, @@ -2277,7 +2278,7 @@ class layerDiffusionSettings: method = LayerMethod.FG_BLEND_TO_BG return method - def settings(self, pipe, method, weight, steps, cfg, sampler_name, scheduler, denoise, seed_num, image=None, blended_image=None, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, method, weight, steps, cfg, sampler_name, scheduler, denoise, seed, image=None, blended_image=None, mask=None, prompt=None, extra_pnginfo=None, my_unique_id=None): blend_samples = pipe['blend_samples'] if "blend_samples" in pipe else None vae = pipe["vae"] batch_size = pipe["loader_settings"]["batch_size"] if "batch_size" in pipe["loader_settings"] else 1 @@ -2286,7 +2287,11 @@ class layerDiffusionSettings: if image is not None or "image" in pipe: image = image if image is not None else pipe['image'] - samples = {"samples": vae.encode(image[:,:,:,:3])} + if mask is not None: + print('inpaint') + samples, = VAEEncodeForInpaint().encode(vae, image, mask) + else: + samples = {"samples": vae.encode(image[:,:,:,:3])} samples = RepeatLatentBatch().repeat(samples, batch_size)[0] images = image elif "samp_images" in pipe: @@ -2317,7 +2322,7 @@ class layerDiffusionSettings: "samples": samples, "blend_samples": blend_samples, "images": images, - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -2334,7 +2339,7 @@ class layerDiffusionSettings: del pipe - return {"ui": {"value": [seed_num]}, "result": (new_pipe,)} + return {"ui": {"value": [seed]}, "result": (new_pipe,)} # 预采样设置（layerDiffuse附加） class layerDiffusionSettingsADDTL: @@ -2410,7 +2415,7 @@ class dynamicCFGSettings: "sampler_name": (comfy.samplers.KSampler.SAMPLERS,), "scheduler": (comfy.samplers.KSampler.SCHEDULERS,), "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional":{ "image_to_latent": ("IMAGE",), @@ -2427,7 +2432,7 @@ class dynamicCFGSettings: FUNCTION = "settings" CATEGORY = "EasyUse/PreSampling" - def settings(self, pipe, steps, cfg, cfg_mode, cfg_scale_min,sampler_name, scheduler, denoise, seed_num, image_to_latent=None, latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): + def settings(self, pipe, steps, cfg, cfg_mode, cfg_scale_min,sampler_name, scheduler, denoise, seed, image_to_latent=None, latent=None, prompt=None, extra_pnginfo=None, my_unique_id=None): dynamic_thresh = DynThresh(7.0, 1.0,"CONSTANT", 0, cfg_mode, cfg_scale_min, 0, 0, 999, False, @@ -2471,7 +2476,7 @@ class dynamicCFGSettings: "samples": samples, "images": images, - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], @@ -2485,7 +2490,7 @@ class dynamicCFGSettings: del pipe - return {"ui": {"value": [seed_num]}, "result": (new_pipe,)} + return {"ui": {"value": [seed]}, "result": (new_pipe,)} # 动态CFG class dynamicThresholdingFull: @@ -2554,7 +2559,7 @@ class samplerFull(LayerDiffuse): "save_prefix": ("STRING", {"default": "ComfyUI"}), }, "optional": { - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), "model": ("MODEL",), "positive": ("CONDITIONING",), "negative": ("CONDITIONING",), @@ -2575,7 +2580,7 @@ class samplerFull(LayerDiffuse): FUNCTION = "run" CATEGORY = "EasyUse/Sampler" - def run(self, pipe, steps, cfg, sampler_name, scheduler, denoise, image_output, link_id, save_prefix, seed_num=None, model=None, positive=None, negative=None, latent=None, vae=None, clip=None, xyPlot=None, tile_size=None, prompt=None, extra_pnginfo=None, my_unique_id=None, force_full_denoise=False, disable_noise=False, downscale_options=None): + def run(self, pipe, steps, cfg, sampler_name, scheduler, denoise, image_output, link_id, save_prefix, seed=None, model=None, positive=None, negative=None, latent=None, vae=None, clip=None, xyPlot=None, tile_size=None, prompt=None, extra_pnginfo=None, my_unique_id=None, force_full_denoise=False, disable_noise=False, downscale_options=None): # Clean loaded_objects easyCache.update_loaded_objects(prompt) @@ -2587,7 +2592,7 @@ class samplerFull(LayerDiffuse): samp_vae = vae if vae is not None else pipe["vae"] samp_clip = clip if clip is not None else pipe["clip"] - samp_seed = seed_num if seed_num is not None else pipe['seed'] + samp_seed = seed if seed is not None else pipe['seed'] steps = steps if steps is not None else pipe['loader_settings']['steps'] start_step = pipe['loader_settings']['start_step'] if 'start_step' in pipe['loader_settings'] else 0 @@ -3254,7 +3259,7 @@ class samplerCascadeFull: "image_output": (["Hide", "Preview", "Save", "Hide/Save", "Sender", "Sender/Save"],), "link_id": ("INT", {"default": 0, "min": 0, "max": sys.maxsize, "step": 1}), "save_prefix": ("STRING", {"default": "ComfyUI"}), - "seed_num": ("INT:seed", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), + "seed": ("INT", {"default": 0, "min": 0, "max": MAX_SEED_NUM}), }, "optional": { @@ -3274,7 +3279,7 @@ class samplerCascadeFull: FUNCTION = "run" CATEGORY = "EasyUse/Sampler" - def run(self, pipe, encode_vae_name, decode_vae_name, steps, cfg, sampler_name, scheduler, denoise, image_output, link_id, save_prefix, seed_num, image_to_latent_c=None, latent_c=None, model_c=None, tile_size=None, prompt=None, extra_pnginfo=None, my_unique_id=None, force_full_denoise=False, disable_noise=False): + def run(self, pipe, encode_vae_name, decode_vae_name, steps, cfg, sampler_name, scheduler, denoise, image_output, link_id, save_prefix, seed, image_to_latent_c=None, latent_c=None, model_c=None, tile_size=None, prompt=None, extra_pnginfo=None, my_unique_id=None, force_full_denoise=False, disable_noise=False): encode_vae_name = encode_vae_name if encode_vae_name is not None else pipe['loader_settings']['encode_vae_name'] decode_vae_name = decode_vae_name if decode_vae_name is not None else pipe['loader_settings']['decode_vae_name'] @@ -3321,7 +3326,7 @@ class samplerCascadeFull: samp_negative = pipe["negative"] samp_samples = samples_c - samp_seed = seed_num if seed_num is not None else pipe['seed'] + samp_seed = seed if seed is not None else pipe['seed'] steps = steps if steps is not None else pipe['loader_settings']['steps'] start_step = pipe['loader_settings']['start_step'] if 'start_step' in pipe['loader_settings'] else 0 @@ -3386,7 +3391,7 @@ class samplerCascadeFull: "samples": samples_b, "images": images, - "seed": seed_num, + "seed": seed, "loader_settings": { **pipe["loader_settings"], diff --git a/py/libs/utils.py b/py/libs/utils.py index f0e7740..86bc141 100644 --- a/py/libs/utils.py +++ b/py/libs/utils.py @@ -79,7 +79,9 @@ def find_wildcards_seed(clip_id, text, prompt): if id != 0: if id == wildcard_id: wildcard_node = prompt[wildcard_id] - seed = wildcard_node["inputs"]["seed_num"] if "seed_num" in wildcard_node["inputs"] else None + seed = wildcard_node["inputs"]["seed"] if "seed" in wildcard_node["inputs"] else None + if seed is None: + seed = wildcard_node["inputs"]["seed_num"] if "seed_num" in wildcard_node["inputs"] else None return seed else: return find_link_clip_id(id, seed, wildcard_id) diff --git a/web/js/easy/easyDynamicWidgets.js b/web/js/easy/easyDynamicWidgets.js index 9b270bb..79e2220 100644 --- a/web/js/easy/easyDynamicWidgets.js +++ b/web/js/easy/easyDynamicWidgets.js @@ -97,11 +97,13 @@ function widgetLogic(node, widget) { } if (widget.name === 'add_noise') { if (widget.value === "disable") { - toggleWidget(node, findWidgetByName(node, 'seed_num')) + toggleWidget(node, findWidgetByName(node, 'seed')) toggleWidget(node, findWidgetByName(node, 'control_before_generate')) + toggleWidget(node, findWidgetByName(node, 'control_after_generate')) } else { - toggleWidget(node, findWidgetByName(node, 'seed_num'), true) + toggleWidget(node, findWidgetByName(node, 'seed'), true) toggleWidget(node, findWidgetByName(node, 'control_before_generate'), true) + toggleWidget(node, findWidgetByName(node, 'control_after_generate'), true) } updateNodeHeight(node) } @@ -791,7 +793,7 @@ app.registerExtension({ // serialize: false // }) // seed_widget.linkedWidgets = [seed_control] - const seed_widget = this.widgets.find(w => w.name == 'seed_num') + const seed_widget = this.widgets.find(w => ['seed_num','seed'].includes(w.name)) const seed_control = this.widgets.find(w=> ['control_before_generate','control_after_generate'].includes(w.name)) if(nodeData.name == 'easy seed'){ this.addWidget("button", "🎲 Manual Random Seed", null, _=>{ diff --git a/web/js/easy/easyExtraMenu.js b/web/js/easy/easyExtraMenu.js index 9e4529a..2ad5ac7 100644 --- a/web/js/easy/easyExtraMenu.js +++ b/web/js/easy/easyExtraMenu.js @@ -30,7 +30,8 @@ const widgetMapping = { "sampler_name": "sampler_name", "scheduler": "scheduler", "denoise": "denoise", - "seed_num": "seed_num" + "seed_num": "seed_num", + "seed": "seed" }, "kSampler":{ "image_output": "image_output",