diff --git a/src/comfyworkflows/edit_image_2_qwen.json b/src/comfyworkflows/edit_image_2_qwen.json index e32bec3..aaf776d 100644 --- a/src/comfyworkflows/edit_image_2_qwen.json +++ b/src/comfyworkflows/edit_image_2_qwen.json @@ -57,7 +57,7 @@ }, "7": { "inputs": { - "seed": 920668017513581, + "seed": 936152772258115, "steps": 8, "cfg": 1, "sampler_name": "euler", @@ -76,8 +76,8 @@ 0 ], "latent_image": [ - "11", - 6 + "28", + 0 ] }, "class_type": "KSampler", @@ -163,11 +163,11 @@ 0 ], "image1": [ - "23", + "30", 0 ], "image2": [ - "24", + "27", 0 ] }, @@ -178,20 +178,41 @@ }, "14": { "inputs": { - "image": "f81662775bd0e7950e4794933ef4b3d973fbb9c2db397c8b46809797954d0074.png" + "image": "model_outfit_location_1760043932148.png" }, "class_type": "LoadImage", "_meta": { - "title": "Load Image" + "title": "load base image" } }, - "15": { + "19": { "inputs": { - "image": "monster_554.png" + "rgthree_comparer": { + "images": [ + { + "name": "A", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_dxzmg_00211_.png&type=temp&subfolder=&rand=0.09499077981761894" + }, + { + "name": "B", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_dxzmg_00212_.png&type=temp&subfolder=&rand=0.21125213225471684" + } + ] + }, + "image_a": [ + "11", + 1 + ], + "image_b": [ + "8", + 0 + ] }, - "class_type": "LoadImage", + "class_type": "Image Comparer (rgthree)", "_meta": { - "title": "Load Image" + "title": "Image Comparer (rgthree)" } }, "20": { @@ -209,7 +230,7 @@ }, "21": { "inputs": { - "value": "只提取图2中的怪物，怪物站在图1的女生身后，使用图1的背景，并调整怪物的光线以符合图1。\n\n\n\n\n\n\n" + "value": "请将图2中的模特处理成手持图1中包包的照片。" }, "class_type": "PrimitiveStringMultiline", "_meta": { @@ -231,17 +252,65 @@ }, "23": { "inputs": { - "width": [ + "width": 720, + "height": 1280, + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + }, + "24": { + "inputs": { + "vae_name": "sdxl_vae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "Load VAE" + } + }, + "25": { + "inputs": { + "samples": [ + "23", + 0 + ], + "vae": [ + "24", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "26": { + "inputs": { + "images": [ "25", 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "27": { + "inputs": { + "width": [ + "31", + 0 ], "height": [ - "26", + "32", 0 ], "upscale_method": "nearest-exact", - "keep_proportion": "stretch", - "pad_color": "0, 0, 0", + "keep_proportion": "resize", + "pad_color": "192,192,192", "crop_position": "center", "divisible_by": 2, "device": "cpu", @@ -255,24 +324,49 @@ "title": "Resize Image v2" } }, - "24": { + "28": { + "inputs": { + "pixels": [ + "27", + 0 + ], + "vae": [ + "3", + 0 + ] + }, + "class_type": "VAEEncode", + "_meta": { + "title": "VAE Encode" + } + }, + "29": { + "inputs": { + "image": "handbag_1760043932148.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "load reference image" + } + }, + "30": { "inputs": { "width": [ - "25", + "31", 0 ], "height": [ - "26", + "32", 0 ], "upscale_method": "nearest-exact", - "keep_proportion": "stretch", - "pad_color": "0, 0, 0", + "keep_proportion": "resize", + "pad_color": "192,192,192", "crop_position": "center", "divisible_by": 2, "device": "cpu", "image": [ - "15", + "29", 0 ] }, @@ -281,20 +375,20 @@ "title": "Resize Image v2" } }, - "25": { + "31": { "inputs": { - "Number": "1280" + "Value": 720 }, - "class_type": "Int", + "class_type": "DF_Integer", "_meta": { "title": "width" } }, - "26": { + "32": { "inputs": { - "Number": "720" + "Value": 1280 }, - "class_type": "Int", + "class_type": "DF_Integer", "_meta": { "title": "height" } diff --git a/src/comfyworkflows/edit_image_2_qwen_empty.json b/src/comfyworkflows/edit_image_2_qwen_empty.json new file mode 100644 index 0000000..64b0f20 --- /dev/null +++ b/src/comfyworkflows/edit_image_2_qwen_empty.json @@ -0,0 +1,444 @@ +{ + "1": { + "inputs": { + "unet_name": "qwen_image_edit_2509_fp8_e4m3fn.safetensors", + "weight_dtype": "default" + }, + "class_type": "UNETLoader", + "_meta": { + "title": "Load Diffusion Model" + } + }, + "2": { + "inputs": { + "clip_name": "qwen_2.5_vl_7b_fp8_scaled.safetensors", + "type": "qwen_image", + "device": "default" + }, + "class_type": "CLIPLoader", + "_meta": { + "title": "Load CLIP" + } + }, + "3": { + "inputs": { + "vae_name": "qwen_image_vae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "Load VAE" + } + }, + "4": { + "inputs": { + "lora_name": "Qwen-Image-Lightning-8steps-V2.0.safetensors", + "strength_model": 1, + "model": [ + "1", + 0 + ] + }, + "class_type": "LoraLoaderModelOnly", + "_meta": { + "title": "LoraLoaderModelOnly" + } + }, + "5": { + "inputs": { + "conditioning": [ + "11", + 0 + ] + }, + "class_type": "ConditioningZeroOut", + "_meta": { + "title": "ConditioningZeroOut" + } + }, + "7": { + "inputs": { + "seed": 38026585691397, + "steps": 8, + "cfg": 1, + "sampler_name": "euler", + "scheduler": "beta", + "denoise": 1, + "model": [ + "4", + 0 + ], + "positive": [ + "11", + 0 + ], + "negative": [ + "5", + 0 + ], + "latent_image": [ + "36", + 0 + ] + }, + "class_type": "KSampler", + "_meta": { + "title": "KSampler" + } + }, + "8": { + "inputs": { + "samples": [ + "7", + 0 + ], + "vae": [ + "3", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "9": { + "inputs": { + "font_file": "Alibaba-PuHuiTi-Heavy.ttf", + "font_size": 40, + "border": 32, + "color_theme": "light", + "reel_1": [ + "10", + 0 + ] + }, + "class_type": "LayerUtility: ImageReelComposit", + "_meta": { + "title": "LayerUtility: Image Reel Composit" + } + }, + "10": { + "inputs": { + "image1_text": "Original image", + "image2_text": "Reference", + "image3_text": "Result", + "image4_text": "image4", + "reel_height": 512, + "border": 32, + "image1": [ + "11", + 1 + ], + "image2": [ + "11", + 2 + ], + "image3": [ + "8", + 0 + ] + }, + "class_type": "LayerUtility: ImageReel", + "_meta": { + "title": "LayerUtility: Image Reel" + } + }, + "11": { + "inputs": { + "prompt": [ + "21", + 0 + ], + "enable_resize": false, + "enable_vl_resize": false, + "upscale_method": "lanczos", + "crop": "disabled", + "instruction": "<|im_start|>system\nDescribe the key features of the input image (color, shape, size, texture, objects, background), then explain how the user's text instruction should alter or modify the image. Generate a new image that meets the user's requirements while maintaining consistency with the original input where appropriate.<|im_end|>\n<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n", + "clip": [ + "2", + 0 + ], + "vae": [ + "3", + 0 + ], + "image1": [ + "27", + 0 + ], + "image2": [ + "33", + 0 + ] + }, + "class_type": "TextEncodeQwenImageEditPlus_lrzjason", + "_meta": { + "title": "TextEncodeQwenImageEditPlus 小志Jason(xiaozhijason)" + } + }, + "14": { + "inputs": { + "image": "model_1760082843769.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "load base image" + } + }, + "19": { + "inputs": { + "rgthree_comparer": { + "images": [ + { + "name": "A", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_uoazy_00279_.png&type=temp&subfolder=&rand=0.4405150352070387" + }, + { + "name": "B", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_uoazy_00280_.png&type=temp&subfolder=&rand=0.9388629603648289" + } + ] + }, + "image_a": [ + "11", + 1 + ], + "image_b": [ + "8", + 0 + ] + }, + "class_type": "Image Comparer (rgthree)", + "_meta": { + "title": "Image Comparer (rgthree)" + } + }, + "20": { + "inputs": { + "filename_prefix": "combined", + "images": [ + "8", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "21": { + "inputs": { + "value": "以图像2为基础，生成一张女性肖像照片。她穿着一件黑色薄纱长袖上衣，一条光滑的皮革及膝裙，和勃艮第色的尖头靴子，手提一个深红色的手提包。场景改为极简主义风格的客厅，摆放着中性的沙发、镜面墙饰、盆栽植物和浅色地板，营造出明亮而宽敞的美感。" + }, + "class_type": "PrimitiveStringMultiline", + "_meta": { + "title": "String (Multiline)" + } + }, + "22": { + "inputs": { + "filename_prefix": "ComfyUI", + "images": [ + "9", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "23": { + "inputs": { + "width": 720, + "height": 1280, + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + }, + "24": { + "inputs": { + "vae_name": "sdxl_vae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "Load VAE" + } + }, + "25": { + "inputs": { + "samples": [ + "23", + 0 + ], + "vae": [ + "24", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "26": { + "inputs": { + "images": [ + "25", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "27": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "upscale_method": "nearest-exact", + "keep_proportion": "resize", + "pad_color": "192,192,192", + "crop_position": "center", + "divisible_by": 2, + "device": "cpu", + "image": [ + "14", + 0 + ] + }, + "class_type": "ImageResizeKJv2", + "_meta": { + "title": "Resize Image v2" + } + }, + "28": { + "inputs": { + "pixels": [ + "27", + 0 + ], + "vae": [ + "3", + 0 + ] + }, + "class_type": "VAEEncode", + "_meta": { + "title": "VAE Encode" + } + }, + "29": { + "inputs": { + "image": "pose_1760082843769.png" + }, + "class_type": "LoadImage", 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+ "title": "DWPose Estimator" + } + }, + "35": { + "inputs": { + "images": [ + "33", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "36": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + } +} \ No newline at end of file diff --git a/src/comfyworkflows/edit_image_2_qwen_handbag.json b/src/comfyworkflows/edit_image_2_qwen_handbag.json new file mode 100644 index 0000000..154bd1a --- /dev/null +++ b/src/comfyworkflows/edit_image_2_qwen_handbag.json @@ -0,0 +1,396 @@ +{ + "1": { + "inputs": { + "unet_name": "qwen_image_edit_2509_fp8_e4m3fn.safetensors", + "weight_dtype": "default" + }, + "class_type": "UNETLoader", + "_meta": { + "title": "Load Diffusion Model" + } + }, + "2": { + "inputs": { + "clip_name": "qwen_2.5_vl_7b_fp8_scaled.safetensors", + "type": "qwen_image", + "device": "default" + }, + "class_type": "CLIPLoader", + "_meta": { + "title": "Load CLIP" + } + }, + "3": { + "inputs": { + "vae_name": "qwen_image_vae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "Load VAE" + } + }, + "4": { + "inputs": { + "lora_name": "Qwen-Image-Lightning-8steps-V2.0.safetensors", + "strength_model": 1, + "model": [ + "1", + 0 + ] + }, + "class_type": "LoraLoaderModelOnly", + "_meta": { + "title": "LoraLoaderModelOnly" + } + }, + "5": { + "inputs": { + "conditioning": [ + "11", + 0 + ] + }, + "class_type": "ConditioningZeroOut", + "_meta": { + "title": "ConditioningZeroOut" + } + }, + "7": { + "inputs": { + "seed": 323591075024702, + "steps": 8, + "cfg": 1, + "sampler_name": "euler", + "scheduler": "beta", + "denoise": 1, + "model": [ + "4", + 0 + ], + "positive": [ + "11", + 0 + ], + "negative": [ + "5", + 0 + ], + "latent_image": [ + "28", + 0 + ] + }, + "class_type": "KSampler", + "_meta": { + "title": "KSampler" + } + }, + "8": { + "inputs": { + "samples": [ + 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Generate a new image that meets the user's requirements while maintaining consistency with the original input where appropriate.<|im_end|>\n<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n", + "clip": [ + "2", + 0 + ], + "vae": [ + "3", + 0 + ], + "image1": [ + "27", + 0 + ], + "image2": [ + "30", + 0 + ] + }, + "class_type": "TextEncodeQwenImageEditPlus_lrzjason", + "_meta": { + "title": "TextEncodeQwenImageEditPlus 小志Jason(xiaozhijason)" + } + }, + "14": { + "inputs": { + "image": "model_outfit_location_handbag1_1760085003312.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "Load Image" + } + }, + "19": { + "inputs": { + "rgthree_comparer": { + "images": [ + { + "name": "A", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_uoazy_00305_.png&type=temp&subfolder=&rand=0.5408789951924671" + }, + { + "name": "B", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_uoazy_00306_.png&type=temp&subfolder=&rand=0.2425856190711294" + } + ] + }, + "image_a": [ + "11", + 1 + ], + "image_b": [ + "8", + 0 + ] + }, + "class_type": "Image Comparer (rgthree)", + "_meta": { + "title": "Image Comparer (rgthree)" + } + }, + "20": { + "inputs": { + "filename_prefix": "combined", + "images": [ + "8", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "21": { + "inputs": { + "value": "请将图2中的女性修改成把图1的包背在肩上。" + }, + "class_type": "PrimitiveStringMultiline", + "_meta": { + "title": "String (Multiline)" + } + }, + "22": { + "inputs": { + "filename_prefix": "ComfyUI", + "images": [ + "9", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "23": { + "inputs": { + "width": 720, + "height": 1280, + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + }, + "24": { + "inputs": { + "vae_name": "sdxl_vae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "Load VAE" + } + }, + "25": { + "inputs": { + "samples": [ + "23", + 0 + ], + "vae": [ + "24", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "26": { + "inputs": { + "images": [ + "25", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "27": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "upscale_method": "nearest-exact", + "keep_proportion": "crop", + "pad_color": "192,192,192", + "crop_position": "center", + "divisible_by": 2, + "device": "cpu", + "image": [ + "14", + 0 + ] + }, + "class_type": "ImageResizeKJv2", + "_meta": { + "title": "Resize Image v2" + } + }, + "28": { + "inputs": { + "pixels": [ + "27", + 0 + ], + "vae": [ + "3", + 0 + ] + }, + "class_type": "VAEEncode", + "_meta": { + "title": "VAE Encode" + } + }, + "29": { + "inputs": { + "image": "handbag_1760085003312.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "Load Image" + } + }, + "30": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "upscale_method": "nearest-exact", + "keep_proportion": "crop", + "pad_color": "192,192,192", + "crop_position": "center", + "divisible_by": 2, + "device": "cpu", + "image": [ + "29", + 0 + ] + }, + "class_type": "ImageResizeKJv2", + "_meta": { + "title": "Resize Image v2" + } + }, + "31": { + "inputs": { + "Value": 720 + }, + "class_type": "DF_Integer", + "_meta": { + "title": "width" + } + }, + "32": { + "inputs": { + "Value": 1280 + }, + "class_type": "DF_Integer", + "_meta": { + "title": "height" + } + } +} \ No newline at end of file diff --git a/src/comfyworkflows/edit_image_2_qwen_pose.json b/src/comfyworkflows/edit_image_2_qwen_pose.json new file mode 100644 index 0000000..64b0f20 --- /dev/null +++ b/src/comfyworkflows/edit_image_2_qwen_pose.json @@ -0,0 +1,444 @@ +{ + "1": { + "inputs": { + "unet_name": "qwen_image_edit_2509_fp8_e4m3fn.safetensors", + "weight_dtype": "default" + }, + "class_type": "UNETLoader", + "_meta": { + 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[ + "5", + 0 + ], + "latent_image": [ + "36", + 0 + ] + }, + "class_type": "KSampler", + "_meta": { + "title": "KSampler" + } + }, + "8": { + "inputs": { + "samples": [ + "7", + 0 + ], + "vae": [ + "3", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "9": { + "inputs": { + "font_file": "Alibaba-PuHuiTi-Heavy.ttf", + "font_size": 40, + "border": 32, + "color_theme": "light", + "reel_1": [ + "10", + 0 + ] + }, + "class_type": "LayerUtility: ImageReelComposit", + "_meta": { + "title": "LayerUtility: Image Reel Composit" + } + }, + "10": { + "inputs": { + "image1_text": "Original image", + "image2_text": "Reference", + "image3_text": "Result", + "image4_text": "image4", + "reel_height": 512, + "border": 32, + "image1": [ + "11", + 1 + ], + "image2": [ + "11", + 2 + ], + "image3": [ + "8", + 0 + ] + }, + "class_type": "LayerUtility: ImageReel", + "_meta": { + "title": "LayerUtility: Image Reel" + } + }, + "11": { + "inputs": { + "prompt": [ + "21", + 0 + ], + "enable_resize": false, + "enable_vl_resize": false, + "upscale_method": "lanczos", + "crop": "disabled", + "instruction": "<|im_start|>system\nDescribe the key features of the input image (color, shape, size, texture, objects, background), then explain how the user's text instruction should alter or modify the image. Generate a new image that meets the user's requirements while maintaining consistency with the original input where appropriate.<|im_end|>\n<|im_start|>user\n{}<|im_end|>\n<|im_start|>assistant\n", + "clip": [ + "2", + 0 + ], + "vae": [ + "3", + 0 + ], + "image1": [ + "27", + 0 + ], + "image2": [ + "33", + 0 + ] + }, + "class_type": "TextEncodeQwenImageEditPlus_lrzjason", + "_meta": { + "title": "TextEncodeQwenImageEditPlus 小志Jason(xiaozhijason)" + } + }, + "14": { + "inputs": { + "image": "model_1760082843769.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "load base image" + } + }, + "19": { + "inputs": { + "rgthree_comparer": { + "images": [ + { + "name": "A", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_uoazy_00279_.png&type=temp&subfolder=&rand=0.4405150352070387" + }, + { + "name": "B", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_uoazy_00280_.png&type=temp&subfolder=&rand=0.9388629603648289" + } + ] + }, + "image_a": [ + "11", + 1 + ], + "image_b": [ + "8", + 0 + ] + }, + "class_type": "Image Comparer (rgthree)", + "_meta": { + "title": "Image Comparer (rgthree)" + } + }, + "20": { + "inputs": { + "filename_prefix": "combined", + "images": [ + "8", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "21": { + "inputs": { + "value": "以图像2为基础，生成一张女性肖像照片。她穿着一件黑色薄纱长袖上衣，一条光滑的皮革及膝裙，和勃艮第色的尖头靴子，手提一个深红色的手提包。场景改为极简主义风格的客厅，摆放着中性的沙发、镜面墙饰、盆栽植物和浅色地板，营造出明亮而宽敞的美感。" + }, + "class_type": "PrimitiveStringMultiline", + "_meta": { + "title": "String (Multiline)" + } + }, + "22": { + "inputs": { + "filename_prefix": "ComfyUI", + "images": [ + "9", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "23": { + "inputs": { + "width": 720, + "height": 1280, + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + }, + "24": { + "inputs": { + "vae_name": "sdxl_vae.safetensors" + }, + "class_type": "VAELoader", + "_meta": { + "title": "Load VAE" + } + }, + "25": { + "inputs": { + "samples": [ + "23", + 0 + ], + "vae": [ + "24", + 0 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "26": { + "inputs": { + "images": [ + "25", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "27": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "upscale_method": "nearest-exact", + "keep_proportion": "resize", + "pad_color": "192,192,192", + "crop_position": "center", + "divisible_by": 2, + "device": "cpu", + "image": [ + "14", + 0 + ] + }, + "class_type": "ImageResizeKJv2", + "_meta": { + "title": "Resize Image v2" + } + }, + "28": { + "inputs": { + "pixels": [ + "27", + 0 + ], + "vae": [ + "3", + 0 + ] + }, + "class_type": "VAEEncode", + "_meta": { + "title": "VAE Encode" + } + }, + "29": { + "inputs": { + "image": "pose_1760082843769.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "load reference image" + } + }, + "30": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "upscale_method": "nearest-exact", + "keep_proportion": "resize", + "pad_color": "192,192,192", + "crop_position": "center", + "divisible_by": 2, + "device": "cpu", + "image": [ + "29", + 0 + ] + }, + "class_type": "ImageResizeKJv2", + "_meta": { + "title": "Resize Image v2" + } + }, + "31": { + "inputs": { + "Value": 720 + }, + "class_type": "DF_Integer", + "_meta": { + "title": "width" + } + }, + "32": { + "inputs": { + "Value": 1280 + }, + "class_type": "DF_Integer", + "_meta": { + "title": "height" + } + }, + "33": { + "inputs": { + "detect_hand": "enable", + "detect_body": "enable", + "detect_face": "enable", + "resolution": 512, + "bbox_detector": "yolox_l.onnx", + "pose_estimator": "dw-ll_ucoco_384_bs5.torchscript.pt", + "scale_stick_for_xinsr_cn": "disable", + "image": [ + "30", + 0 + ] + }, + "class_type": "DWPreprocessor", + "_meta": { + "title": "DWPose Estimator" + } + }, + "35": { + "inputs": { + "images": [ + "33", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "36": { + "inputs": { + "width": [ + "31", + 0 + ], + "height": [ + "32", + 0 + ], + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + } +} \ No newline at end of file diff --git a/src/comfyworkflows/facerestore_upscale.json b/src/comfyworkflows/facerestore_upscale.json new file mode 100644 index 0000000..51b288d --- /dev/null +++ b/src/comfyworkflows/facerestore_upscale.json @@ -0,0 +1,111 @@ +{ + "1": { + "inputs": { + "image": "model_outfit_location_handbag3_1760086053609.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "Load Image" + } + }, + "2": { + "inputs": { + "enabled": true, + "swap_model": "inswapper_128.onnx", + "facedetection": "YOLOv5l", + "face_restore_model": "GPEN-BFR-1024.onnx", + "face_restore_visibility": 0.5200000000000001, + "codeformer_weight": 0.5, + "detect_gender_input": "no", + "detect_gender_source": "no", + "input_faces_index": "0", + "source_faces_index": "0", + "console_log_level": 1, + "input_image": [ + "6", + 0 + ], + "source_image": [ + "3", + 0 + ] + }, + "class_type": "ReActorFaceSwap", + "_meta": { + "title": "ReActor 🌌 Fast Face Swap" + } + }, + "3": { + "inputs": { + "image": "outfit_1760086053609.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "Load Image" + } + }, + "4": { + "inputs": { + "images": [ + "2", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "6": { + "inputs": { + "resize_to": "4k", + "images": [ + "1", + 0 + ], + "upscaler_trt_model": [ + "8", + 0 + ] + }, + "class_type": "UpscalerTensorrt", + "_meta": { + "title": "Upscaler Tensorrt ⚡" + } + }, + "7": { + "inputs": { + "images": [ + "6", + 0 + ] + }, + "class_type": "PreviewImage", + "_meta": { + "title": "Preview Image" + } + }, + "8": { + "inputs": { + "model": "4x-UltraSharp", + "precision": "fp16" + }, + "class_type": "LoadUpscalerTensorrtModel", + "_meta": { + "title": "Load Upscale Tensorrt Model" + } + }, + "9": { + "inputs": { + "filename_prefix": "upscaled", + "images": [ + "2", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + } +} \ No newline at end of file diff --git a/src/comfyworkflows/upscale.json b/src/comfyworkflows/upscale.json new file mode 100644 index 0000000..34a9557 --- /dev/null +++ b/src/comfyworkflows/upscale.json @@ -0,0 +1,388 @@ +{ + "4": { + "inputs": { + "ckpt_name": "dreamshaperXL_v21TurboDPMSDE.safetensors" + }, + "class_type": "CheckpointLoaderSimple", + "_meta": { + "title": "Load Checkpoint" + } + }, + "12": { + "inputs": { + "seed": 302411063911982, + "steps": 8, + "cfg": 2, + "sampler_name": "dpmpp_sde", + "scheduler": "karras", + "denoise": 1, + "model": [ + "4", + 0 + ], + "positive": [ + "65", + 0 + ], + "negative": [ + "69", + 0 + ], + "latent_image": [ + "13", + 0 + ] + }, + "class_type": "KSampler", + "_meta": { + "title": "KSampler" + } + }, + "13": { + "inputs": { + "width": 1216, + "height": 832, + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + }, + "16": { + "inputs": { + "samples": [ + "12", + 0 + ], + "vae": [ + "4", + 2 + ] + }, + "class_type": "VAEDecode", + "_meta": { + "title": "VAE Decode" + } + }, + "36": { + "inputs": { + "method": "Mixture of Diffusers", + "tile_width": 1024, + "tile_height": 1024, + "tile_overlap": 32, + "tile_batch_size": 8, + "model": [ + "4", + 0 + ] + }, + "class_type": "TiledDiffusion", + "_meta": { + "title": "Tiled Diffusion" + } + }, + "51": { + "inputs": { + "tile_size": 1024, + "fast": false, + "samples": [ + "80", + 0 + ], + "vae": [ + "4", + 2 + ] + }, + "class_type": "VAEDecodeTiled_TiledDiffusion", + "_meta": { + "title": "Tiled VAE Decode" + } + }, + "65": { + "inputs": { + "text": "photo of a high end sports car", + "clip": [ + "4", + 1 + ] + }, + "class_type": "CLIPTextEncode", + "_meta": { + "title": "CLIP Text Encode (Prompt)" + } + }, + "69": { + "inputs": { + "text": "text, watermark, (film grain, noise:1.2)", + "clip": [ + "4", + 1 + ] + }, + "class_type": "CLIPTextEncode", + "_meta": { + "title": "CLIP Text Encode (Prompt)" + } + }, + "80": { + "inputs": { + "seed": 105566927616764, + "steps": 4, + "cfg": 2, + "sampler_name": "dpmpp_sde", + "scheduler": "karras", + "denoise": 1, + "model": [ + "36", + 0 + ], + "positive": [ + "141", + 0 + ], + "negative": [ + "141", + 1 + ], + "latent_image": [ + "84", + 0 + ] + }, + "class_type": "KSampler", + "_meta": { + "title": "KSampler" + } + }, + "84": { + "inputs": { + "width": [ + "106", + 0 + ], + "height": [ + "107", + 0 + ], + "batch_size": 1 + }, + "class_type": "EmptyLatentImage", + "_meta": { + "title": "Empty Latent Image" + } + }, + "105": { + "inputs": { + "image": [ + "115", + 0 + ] + }, + "class_type": "GetImageSizeAndCount", + "_meta": { + "title": "Get Image Size & Count" + } + }, + "106": { + "inputs": { + "value": "a*b", + "a": [ + "105", + 1 + ], + "b": [ + "117", + 0 + ] + }, + "class_type": "SimpleMath+", + "_meta": { + "title": "🔧 Simple Math" + } + }, + "107": { + "inputs": { + "value": "a*b", + "a": [ + "105", + 2 + ], + "b": [ + "117", + 0 + ] + }, + "class_type": "SimpleMath+", + "_meta": { + "title": "🔧 Simple Math" + } + }, + "111": { + "inputs": { + "image": "model_outfit_location_handbag1_1760092227085.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "Load Image" + } + }, + "115": { + "inputs": { + "any_01": [ + "111", + 0 + ] + }, + "class_type": "Any Switch (rgthree)", + "_meta": { + "title": "Any Switch (rgthree)" + } + }, + "117": { + "inputs": { + "value": 4.000000000000001 + }, + "class_type": "FloatConstant", + "_meta": { + "title": "Float Constant" + } + }, + "133": { + "inputs": { + "rgthree_comparer": { + "images": [ + { + "name": "A", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_ybqmm_00009_.png&type=temp&subfolder=&rand=0.02707950499627365" + }, + { + "name": "B", + "selected": true, + "url": "/api/view?filename=rgthree.compare._temp_ybqmm_00010_.png&type=temp&subfolder=&rand=0.18690183070180255" + } + ] + }, + "image_a": [ + "115", + 0 + ], + "image_b": [ + "149", + 0 + ] + }, + "class_type": "Image Comparer (rgthree)", + "_meta": { + "title": "Image Comparer (rgthree)" + } + }, + "141": { + "inputs": { + "strength": 0.65, + "start_percent": 0, + "end_percent": 0.9, + "positive": [ + "65", + 0 + ], + "negative": [ + "69", + 0 + ], + "control_net": [ + "142", + 0 + ], + "image": [ + "115", + 0 + ] + }, + "class_type": "ACN_AdvancedControlNetApply", + "_meta": { + "title": "Apply Advanced ControlNet 🛂🅐🅒🅝" + } + }, + "142": { + "inputs": { + "control_net_name": "xinsircontrolnet-tile-sdxl-1.0.safetensors" + }, + "class_type": "ControlNetLoaderAdvanced", + "_meta": { + "title": "Load Advanced ControlNet Model 🛂🅐🅒🅝" + } + }, + "148": { + "inputs": { + "color_space": "LAB", + "factor": 0.8, + "device": "auto", + "batch_size": 0, + "image": [ + "51", + 0 + ], + "reference": [ + "115", + 0 + ] + }, + "class_type": "ImageColorMatch+", + "_meta": { + "title": "🔧 Image Color Match" + } + }, + "149": { + "inputs": { + "sharpen_radius": 1, + "sigma": 1, + "alpha": 0.05, + "image": [ + "148", + 0 + ] + }, + "class_type": "ImageSharpen", + "_meta": { + "title": "Image Sharpen" + } + }, + "154": { + "inputs": { + "filename_prefix": "Upscaled", + "images": [ + "149", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + }, + "165": { + "inputs": { + "image": "model_outfit_location_handbag1_1760092227085.png" + }, + "class_type": "LoadImage", + "_meta": { + "title": "Load Image" + } + }, + "166": { + "inputs": { + "filename_prefix": "upscaled", + "images": [ + "149", + 0 + ] + }, + "class_type": "SaveImage", + "_meta": { + "title": "Save Image" + } + } +} \ No newline at end of file diff --git a/src/lib/image-converter.ts b/src/lib/image-converter.ts index bf48a27..89cfd1a 100644 --- a/src/lib/image-converter.ts +++ b/src/lib/image-converter.ts @@ -15,17 +15,27 @@ async function convertImage( baseFileName: string, comfyBaseUrl: string, comfyOutputDir: string, - size: ImageSize = { width: 720, height: 1280 } + size: ImageSize = { width: 720, height: 1280 }, + useEmpltyLatent: boolean = false ): Promise { const COMFY_BASE_URL = comfyBaseUrl.replace(/\/$/, ''); const COMFY_OUTPUT_DIR = comfyOutputDir; let workflow; - workflow = JSON.parse(await fs.readFile('src/comfyworkflows/edit_image_qwen.json', 'utf-8')); - workflow['21']['inputs']['value'] = prompt; - workflow['23']['inputs']['width'] = size.width; - workflow['23']['inputs']['height'] = size.height; - workflow['14']['inputs']['image'] = baseFileName; + if (useEmpltyLatent) { + workflow = JSON.parse(await fs.readFile('src/comfyworkflows/edit_image_2_qwen_empty.json', 'utf-8')); + workflow['21']['inputs']['value'] = prompt; + workflow['30']['inputs']['width'] = size.width; + workflow['31']['inputs']['height'] = size.height; + workflow['14']['inputs']['image'] = baseFileName; + } else { + workflow = JSON.parse(await fs.readFile('src/comfyworkflows/edit_image_qwen.json', 'utf-8')); + workflow['21']['inputs']['value'] = prompt; + workflow['23']['inputs']['width'] = size.width; + workflow['23']['inputs']['height'] = size.height; + workflow['14']['inputs']['image'] = baseFileName; + } + const response = await axios.post(`${COMFY_BASE_URL}/prompt`, { prompt: workflow }); const promptId = response.data.prompt_id; @@ -66,7 +76,8 @@ async function convertImage( return newFilePath; } - +// basefilename is connected to image2 +// sencondfilename is connect to image1 async function convertImageWithFile( prompt: string, baseFileName: string, @@ -81,10 +92,131 @@ async function convertImageWithFile( workflow = JSON.parse(await fs.readFile('src/comfyworkflows/edit_image_2_qwen.json', 'utf-8')); workflow['21']['inputs']['value'] = prompt; - workflow['25']['inputs']['width'] = size.width; - workflow['26']['inputs']['height'] = size.height; + workflow['31']['inputs']['Value'] = size.width; + workflow['32']['inputs']['Value'] = size.height; workflow['14']['inputs']['image'] = baseFileName; - workflow['15']['inputs']['image'] = secondFileName; + workflow['29']['inputs']['image'] = secondFileName; + + const response = await axios.post(`${COMFY_BASE_URL}/prompt`, { prompt: workflow }); + const promptId = response.data.prompt_id; + + let history; + do { + await new Promise(resolve => setTimeout(resolve, 1000)); + const historyResponse = await axios.get(`${COMFY_BASE_URL}/history/${promptId}`); + history = historyResponse.data[promptId]; + } while (!history || Object.keys(history.outputs).length === 0); + + const files = await fs.readdir(COMFY_OUTPUT_DIR!); + const generatedFiles = files.filter(file => file.startsWith('combined')); + + const fileStats = await Promise.all( + generatedFiles.map(async (file) => { + const stat = await fs.stat(path.join(COMFY_OUTPUT_DIR!, file)); + return { file, mtime: stat.mtime }; + }) + ); + + fileStats.sort((a, b) => b.mtime.getTime() - a.mtime.getTime()); + + const latestFile = fileStats[0].file; + const newFilePath = path.resolve('./generated', baseFileName); + + await fs.mkdir('./generated', { recursive: true }); + + const sourcePath = path.join(COMFY_OUTPUT_DIR!, latestFile); + try { + await fs.unlink(newFilePath); + } catch (err) { + // ignore if not exists + } + + await fs.copyFile(sourcePath, newFilePath); + + return newFilePath; +} + + +// basefilename is connected to image1 +// sencondfilename is connect to image2 +async function convertImageWithFileHandbag( + prompt: string, + baseFileName: string, + secondFileName: string, + comfyBaseUrl: string, + comfyOutputDir: string, + size: ImageSize = { width: 720, height: 1280 } +): Promise { + const COMFY_BASE_URL = comfyBaseUrl.replace(/\/$/, ''); + const COMFY_OUTPUT_DIR = comfyOutputDir; + let workflow; + + workflow = JSON.parse(await fs.readFile('src/comfyworkflows/edit_image_2_qwen_handbag.json', 'utf-8')); + workflow['21']['inputs']['value'] = prompt; + workflow['31']['inputs']['Value'] = size.width; + workflow['32']['inputs']['Value'] = size.height; + workflow['14']['inputs']['image'] = baseFileName; + workflow['29']['inputs']['image'] = secondFileName; + + const response = await axios.post(`${COMFY_BASE_URL}/prompt`, { prompt: workflow }); + const promptId = response.data.prompt_id; + + let history; + do { + await new Promise(resolve => setTimeout(resolve, 1000)); + const historyResponse = await axios.get(`${COMFY_BASE_URL}/history/${promptId}`); + history = historyResponse.data[promptId]; + } while (!history || Object.keys(history.outputs).length === 0); + + const files = await fs.readdir(COMFY_OUTPUT_DIR!); + const generatedFiles = files.filter(file => file.startsWith('combined')); + + const fileStats = await Promise.all( + generatedFiles.map(async (file) => { + const stat = await fs.stat(path.join(COMFY_OUTPUT_DIR!, file)); + return { file, mtime: stat.mtime }; + }) + ); + + fileStats.sort((a, b) => b.mtime.getTime() - a.mtime.getTime()); + + const latestFile = fileStats[0].file; + const newFilePath = path.resolve('./generated', baseFileName); + + await fs.mkdir('./generated', { recursive: true }); + + const sourcePath = path.join(COMFY_OUTPUT_DIR!, latestFile); + try { + await fs.unlink(newFilePath); + } catch (err) { + // ignore if not exists + } + + await fs.copyFile(sourcePath, newFilePath); + + return newFilePath; +} + +// basefilename is connected to image1 +// sencondfilename is connect to image2 +async function convertImageWithFileForPose( + prompt: string, + baseFileName: string, + secondFileName: string, + comfyBaseUrl: string, + comfyOutputDir: string, + size: ImageSize = { width: 720, height: 1280 } +): Promise { + const COMFY_BASE_URL = comfyBaseUrl.replace(/\/$/, ''); + const COMFY_OUTPUT_DIR = comfyOutputDir; + let workflow; + + workflow = JSON.parse(await fs.readFile('src/comfyworkflows/edit_image_2_qwen_pose.json', 'utf-8')); + workflow['21']['inputs']['value'] = prompt; + workflow['31']['inputs']['Value'] = size.width; + workflow['32']['inputs']['Value'] = size.height; + workflow['14']['inputs']['image'] = baseFileName; + workflow['29']['inputs']['image'] = secondFileName; const response = await axios.post(`${COMFY_BASE_URL}/prompt`, { prompt: workflow }); const promptId = response.data.prompt_id; @@ -369,4 +501,4 @@ export async function convertImageVtonPose( return newFilePath; } -export { convertImage, convertImageWithFile }; +export { convertImage, convertImageWithFile, convertImageWithFileForPose, convertImageWithFileHandbag }; diff --git a/src/lib/image-upscaler.ts b/src/lib/image-upscaler.ts new file mode 100644 index 0000000..0c019ec --- /dev/null +++ b/src/lib/image-upscaler.ts @@ -0,0 +1,118 @@ +import * as fs from 'fs/promises'; +import * as path from 'path'; +import axios from 'axios'; +import dotenv from 'dotenv'; + +dotenv.config(); + +interface ImageSize { + width: number; + height: number; +} + +async function facerestore_upscale( + baseFileName: string, + faceReferenceName: string, + comfyBaseUrl: string, + comfyOutputDir: string, +): Promise { + const COMFY_BASE_URL = comfyBaseUrl.replace(/\/$/, ''); + const COMFY_OUTPUT_DIR = comfyOutputDir; + let workflow; + + workflow = JSON.parse(await fs.readFile('src/comfyworkflows/facerestore_upscale.json', 'utf-8')); + workflow['1']['inputs']['image'] = baseFileName; + workflow['3']['inputs']['image'] = faceReferenceName; + + const response = await axios.post(`${COMFY_BASE_URL}/prompt`, { prompt: workflow }); + const promptId = response.data.prompt_id; + + let history; + do { + await new Promise(resolve => setTimeout(resolve, 1000)); + const historyResponse = await axios.get(`${COMFY_BASE_URL}/history/${promptId}`); + history = historyResponse.data[promptId]; + } while (!history || Object.keys(history.outputs).length === 0); + + const files = await fs.readdir(COMFY_OUTPUT_DIR!); + const generatedFiles = files.filter(file => file.startsWith('upscaled')); + + const fileStats = await Promise.all( + generatedFiles.map(async (file) => { + const stat = await fs.stat(path.join(COMFY_OUTPUT_DIR!, file)); + return { file, mtime: stat.mtime }; + }) + ); + + fileStats.sort((a, b) => b.mtime.getTime() - a.mtime.getTime()); + + const latestFile = fileStats[0].file; + const newFilePath = path.resolve('./generated', baseFileName); + + await fs.mkdir('./generated', { recursive: true }); + + const sourcePath = path.join(COMFY_OUTPUT_DIR!, latestFile); + try { + await fs.unlink(newFilePath); + } catch (err) { + // ignore if not exists + } + + await fs.copyFile(sourcePath, newFilePath); + + return newFilePath; +} + + +async function upscale( + baseFileName: string, + comfyBaseUrl: string, + comfyOutputDir: string, +): Promise { + const COMFY_BASE_URL = comfyBaseUrl.replace(/\/$/, ''); + const COMFY_OUTPUT_DIR = comfyOutputDir; + let workflow; + + workflow = JSON.parse(await fs.readFile('src/comfyworkflows/upscale.json', 'utf-8')); + workflow['111']['inputs']['image'] = baseFileName; + const response = await axios.post(`${COMFY_BASE_URL}/prompt`, { prompt: workflow }); + const promptId = response.data.prompt_id; + + let history; + do { + await new Promise(resolve => setTimeout(resolve, 1000)); + const historyResponse = await axios.get(`${COMFY_BASE_URL}/history/${promptId}`); + history = historyResponse.data[promptId]; + } while (!history || Object.keys(history.outputs).length === 0); + + const files = await fs.readdir(COMFY_OUTPUT_DIR!); + const generatedFiles = files.filter(file => file.startsWith('upscaled')); + + const fileStats = await Promise.all( + generatedFiles.map(async (file) => { + const stat = await fs.stat(path.join(COMFY_OUTPUT_DIR!, file)); + return { file, mtime: stat.mtime }; + }) + ); + + fileStats.sort((a, b) => b.mtime.getTime() - a.mtime.getTime()); + + const latestFile = fileStats[0].file; + const newFilePath = path.resolve('./generated', baseFileName); + + await fs.mkdir('./generated', { recursive: true }); + + const sourcePath = path.join(COMFY_OUTPUT_DIR!, latestFile); + try { + await fs.unlink(newFilePath); + } catch (err) { + // ignore if not exists + } + + await fs.copyFile(sourcePath, newFilePath); + + return newFilePath; +} + + +export { facerestore_upscale, upscale }; diff --git a/src/vton/handback_portrait.ts b/src/vton/handback_portrait.ts new file mode 100644 index 0000000..6e59b22 --- /dev/null +++ b/src/vton/handback_portrait.ts @@ -0,0 +1,538 @@ +import * as fs from 'fs/promises'; +import * as path from 'path'; +import dotenv from 'dotenv'; +import { downloadImagesFromPinterestSearch } from '../lib/pinterest'; +import { convertImage, convertImageWithFile, convertImageWithFileForPose, convertImageWithFileHandbag } from '../lib/image-converter'; +import { logger } from '../lib/logger'; +import { callLmstudio, callLMStudioAPIWithFile } from '../lib/lmstudio'; +import { upscale } from '../lib/image-upscaler'; +dotenv.config(); + +const SERVER1_COMFY_BASE_URL = process.env.SERVER1_COMFY_BASE_URL!; +const SERVER1_COMFY_OUTPUT_DIR = process.env.SERVER1_COMFY_OUTPUT_DIR!; +const imageSize: { width: number; height: number } = { width: 1280, height: 720 }; + + +async function upscaleAndFix( + baseImage: string, + faceImage: string, + outputFilename: string, + outputDir: string, +): Promise { + try { + + // Copy both images to ComfyUI input directory + const inputFolderFullPath = SERVER1_COMFY_OUTPUT_DIR.replace('output', 'input'); + await fs.mkdir(inputFolderFullPath, { recursive: true }); + + const baseFilePath = path.join(outputDir, baseImage); + const referenceFilePath = path.join(outputDir, faceImage); + + const baseFileName = path.basename(baseImage); + const referenceFileName = path.basename(faceImage); + + const inputBasePath = path.join(inputFolderFullPath, baseFileName); + const inputReferencePath = path.join(inputFolderFullPath, referenceFileName); + + logger.info(`Copying base image to ComfyUI input: ${inputBasePath}`); + await fs.copyFile(baseFilePath, inputBasePath); + + logger.info(`Copying reference image to ComfyUI input: ${inputReferencePath}`); + await fs.copyFile(referenceFilePath, inputReferencePath); + + // Convert images with prompt + logger.info(`Processing images with convertImageWithFile...`); + + const convertedImagePath = await upscale( + baseFileName, + SERVER1_COMFY_BASE_URL, + SERVER1_COMFY_OUTPUT_DIR, + ) + + logger.info(`Converted image: ${convertedImagePath}`); + + // Copy the converted image to final destination + const finalOutputPath = path.join(outputDir, outputFilename); + logger.info(`Copying to final destination: ${finalOutputPath}`); + await fs.copyFile(convertedImagePath, finalOutputPath); + + logger.info(`✓ Successfully generated: ${finalOutputPath}`); + + } catch (error) { + logger.error(`Error processing two images:`, error); + throw error; + } +} + +/** + * Process a single image: download from Pinterest, convert with prompt, and save + * @param keyword - Pinterest search keyword + * @param prompt - Image conversion prompt + * @param filename - Output filename + * @param outputDir - Directory to save the generated file + * @param shouldConvert - Whether to convert the image with prompt or just copy it + */ +async function processImage( + keyword: string, + prompt: string, + filename: string, + outputDir: string, + shouldConvert: boolean = true +): Promise { + try { + logger.info(`\n=== Processing: ${filename} ===`); + logger.info(`Keyword: ${keyword}`); + logger.info(`Should convert: ${shouldConvert}`); + + // Step 1: Download image from Pinterest + logger.info(`Step 1: Downloading image from Pinterest with keyword: "${keyword}"...`); + const downloadedImages = await downloadImagesFromPinterestSearch(keyword, 1); + + if (downloadedImages.length === 0) { + logger.error(`Failed to download image for keyword: "${keyword}"`); + return; + } + + const downloadedImagePath = downloadedImages[0]; + logger.info(`Downloaded image: ${downloadedImagePath}`); + + const finalOutputPath = path.join(outputDir, filename); + + if (shouldConvert) { + logger.info(`Prompt: ${prompt}`); + + // Step 2: Copy image to ComfyUI input directory + const inputFolderFullPath = SERVER1_COMFY_OUTPUT_DIR.replace('output', 'input'); + await fs.mkdir(inputFolderFullPath, { recursive: true }); + + const imageFileName = path.basename(downloadedImagePath); + const inputImagePath = path.join(inputFolderFullPath, imageFileName); + + logger.info(`Step 2: Copying image to ComfyUI input folder: ${inputImagePath}`); + await fs.copyFile(downloadedImagePath, inputImagePath); + + // Step 3: Convert image with prompt + logger.info(`Step 3: Converting image with prompt...`); + const convertedImagePath = await convertImage( + prompt, + imageFileName, + SERVER1_COMFY_BASE_URL, + SERVER1_COMFY_OUTPUT_DIR, + imageSize + ); + logger.info(`Converted image: ${convertedImagePath}`); + + // Step 4: Copy the converted image to final destination + logger.info(`Step 4: Copying to final destination: ${finalOutputPath}`); + await fs.copyFile(convertedImagePath, finalOutputPath); + } else { + // Just copy the downloaded image directly to the output directory with the specified filename + logger.info(`Step 2: Copying directly to final destination: ${finalOutputPath}`); + await fs.copyFile(downloadedImagePath, finalOutputPath); + } + + logger.info(`✓ Successfully generated: ${finalOutputPath}`); + + } catch (error) { + logger.error(`Error processing image for keyword "${keyword}":`, error); + throw error; + } +} + +/** + * Convert an existing image with a prompt + * @param prompt - Image conversion prompt + * @param imagePath - Path to the existing image + * @param outputFilename - Output filename + * @param outputDir - Directory to save the converted file + */ +async function convertImageWithPrompt( + prompt: string, + imagePath: string, + outputFilename: string, + outputDir: string +): Promise { + try { + logger.info(`\n=== Converting Image: ${outputFilename} ===`); + logger.info(`Source: ${imagePath}`); + logger.info(`Prompt: ${prompt}`); + + // Step 1: Copy image to ComfyUI input directory + const inputFolderFullPath = SERVER1_COMFY_OUTPUT_DIR.replace('output', 'input'); + await fs.mkdir(inputFolderFullPath, { recursive: true }); + + const imageFileName = path.basename(imagePath); + const inputImagePath = path.join(inputFolderFullPath, imageFileName); + + logger.info(`Step 1: Copying image to ComfyUI input folder: ${inputImagePath}`); + await fs.copyFile(imagePath, inputImagePath); + + // Step 2: Convert image with prompt + logger.info(`Step 2: Converting image with prompt...`); + const convertedImagePath = await convertImage( + prompt, + imageFileName, + SERVER1_COMFY_BASE_URL, + SERVER1_COMFY_OUTPUT_DIR, + imageSize + ); + logger.info(`Converted image: ${convertedImagePath}`); + + // Step 3: Copy the converted image to final destination + const finalOutputPath = path.join(outputDir, outputFilename); + logger.info(`Step 3: Copying to final destination: ${finalOutputPath}`); + await fs.copyFile(convertedImagePath, finalOutputPath); + + logger.info(`✓ Successfully converted: ${finalOutputPath}`); + + } catch (error) { + logger.error(`Error converting image:`, error); + throw error; + } +} + +/** + * Process two images together: combine base image with reference image using prompt + * @param prompt - Processing prompt + * @param baseFile - Base image filename (in generated folder) + * @param referenceFile - Reference image filename (in generated folder) + * @param outputFilename - Output filename + * @param outputDir - Directory to save the generated file + */ +async function processTwoImages( + prompt: string, + baseFile: string, + referenceFile: string, + outputFilename: string, + outputDir: string, + isPose: boolean = false +): Promise { + try { + logger.info(`\n=== Processing: ${outputFilename} ===`); + logger.info(`Base: ${baseFile}, Reference: ${referenceFile}`); + logger.info(`Prompt: ${prompt}`); + + // Copy both images to ComfyUI input directory + const inputFolderFullPath = SERVER1_COMFY_OUTPUT_DIR.replace('output', 'input'); + await fs.mkdir(inputFolderFullPath, { recursive: true }); + + const baseFilePath = path.join(outputDir, baseFile); + const referenceFilePath = path.join(outputDir, referenceFile); + + const baseFileName = path.basename(baseFile); + const referenceFileName = path.basename(referenceFile); + + const inputBasePath = path.join(inputFolderFullPath, baseFileName); + const inputReferencePath = path.join(inputFolderFullPath, referenceFileName); + + logger.info(`Copying base image to ComfyUI input: ${inputBasePath}`); + await fs.copyFile(baseFilePath, inputBasePath); + + logger.info(`Copying reference image to ComfyUI input: ${inputReferencePath}`); + await fs.copyFile(referenceFilePath, inputReferencePath); + + // Convert images with prompt + logger.info(`Processing images with convertImageWithFile...`); + + const convertedImagePath = isPose ? await convertImageWithFileForPose( + prompt, + baseFileName, + referenceFileName, + SERVER1_COMFY_BASE_URL, + SERVER1_COMFY_OUTPUT_DIR, + imageSize + ) : await convertImageWithFile( + prompt, + baseFileName, + referenceFileName, + SERVER1_COMFY_BASE_URL, + SERVER1_COMFY_OUTPUT_DIR, + imageSize + ) + + logger.info(`Converted image: ${convertedImagePath}`); + + // Copy the converted image to final destination + const finalOutputPath = path.join(outputDir, outputFilename); + logger.info(`Copying to final destination: ${finalOutputPath}`); + await fs.copyFile(convertedImagePath, finalOutputPath); + + logger.info(`✓ Successfully generated: ${finalOutputPath}`); + + } catch (error) { + logger.error(`Error processing two images:`, error); + throw error; + } +} + + +/** + * Process two images together: combine base image with reference image using prompt + * @param prompt - Processing prompt + * @param baseFile - Base image filename (in generated folder) + * @param referenceFile - Reference image filename (in generated folder) + * @param outputFilename - Output filename + * @param outputDir - Directory to save the generated file + */ +async function processTwoImagesHandbag( + prompt: string, + baseFile: string, + referenceFile: string, + outputFilename: string, + outputDir: string, +): Promise { + try { + logger.info(`\n=== Processing: ${outputFilename} ===`); + logger.info(`Base: ${baseFile}, Reference: ${referenceFile}`); + logger.info(`Prompt: ${prompt}`); + + // Copy both images to ComfyUI input directory + const inputFolderFullPath = SERVER1_COMFY_OUTPUT_DIR.replace('output', 'input'); + await fs.mkdir(inputFolderFullPath, { recursive: true }); + + const baseFilePath = path.join(outputDir, baseFile); + const referenceFilePath = path.join(outputDir, referenceFile); + + const baseFileName = path.basename(baseFile); + const referenceFileName = path.basename(referenceFile); + + const inputBasePath = path.join(inputFolderFullPath, baseFileName); + const inputReferencePath = path.join(inputFolderFullPath, referenceFileName); + + logger.info(`Copying base image to ComfyUI input: ${inputBasePath}`); + await fs.copyFile(baseFilePath, inputBasePath); + + logger.info(`Copying reference image to ComfyUI input: ${inputReferencePath}`); + await fs.copyFile(referenceFilePath, inputReferencePath); + + // Convert images with prompt + logger.info(`Processing images with convertImageWithFile...`); + + const convertedImagePath = await convertImageWithFileHandbag( + prompt, + baseFileName, + referenceFileName, + SERVER1_COMFY_BASE_URL, + SERVER1_COMFY_OUTPUT_DIR, + imageSize + ) + + logger.info(`Converted image: ${convertedImagePath}`); + + // Copy the converted image to final destination + const finalOutputPath = path.join(outputDir, outputFilename); + logger.info(`Copying to final destination: ${finalOutputPath}`); + await fs.copyFile(convertedImagePath, finalOutputPath); + + logger.info(`✓ Successfully generated: ${finalOutputPath}`); + + } catch (error) { + logger.error(`Error processing two images:`, error); + throw error; + } +} + +/** + * Process a complete iteration: download base images and apply sequential transformations + */ +async function processIteration(iteration: number): Promise { + try { + const timestamp = Date.now(); + logger.info(`\n${'='.repeat(80)}`); + logger.info(`ITERATION ${iteration} - Starting with timestamp: ${timestamp}`); + logger.info(`${'='.repeat(80)}`); + + // Create output directory for this iteration + const outputDir = path.join(process.cwd(), 'generated', `vton_${timestamp}`); + await fs.mkdir(outputDir, { recursive: true }); + logger.info(`Output directory created: ${outputDir}`); + + // === PHASE 1: Download base images === + logger.info(`\n--- PHASE 1: Downloading base images ---`); + + await processImage( + 'cute girl face high resolution', + '', + `model_${timestamp}.png`, + outputDir, + false + ); + + await processImage( + 'woman elegant outfit fullbody single', + '', + `outfit_${timestamp}.png`, + outputDir, + false + ); + + await processImage( + 'photo elegant indoor room', + '', + `room_${timestamp}.png`, + outputDir, + false + ); + + await processImage( + 'handbag single product photography', + '请提取照片中的包，并将其正面朝向地放置在亮灰色背景上。', + `handbag_${timestamp}.png`, + outputDir, + true + ); + + await processImage( + 'woman portrait standing', + '', + `pose_${timestamp}.png`, + outputDir, + false + ); + + // === PHASE 2: Sequential transformations === + logger.info(`\n--- PHASE 2: Sequential transformations ---`); + + // Step 1: Generate outfit prompt using LMStudio API + logger.info('Step 1: Generating outfit prompt with LMStudio API...'); + const outfitImagePath = path.join(outputDir, `outfit_${timestamp}.png`); + const outfitPromptResponse = await callLMStudioAPIWithFile( + outfitImagePath, + 'Describe this outfit in detail about 30 words. Focus on color and cloth type. Return the result in this format: {"result":""}' + ); + const outfitPrompt = outfitPromptResponse.result || outfitPromptResponse; + logger.info(`Generated outfit prompt: ${outfitPrompt}`); + + // Step 2: Generate location prompt using LMStudio API + logger.info('Step 2: Generating location prompt with LMStudio API...'); + const roomImagePath = path.join(outputDir, `room_${timestamp}.png`); + const locationPromptResponse = await callLMStudioAPIWithFile( + roomImagePath, + 'Describe this location/room in detail about 30 words. Return the result in this format: {"result":""}' + ); + const locationPrompt = locationPromptResponse.result || locationPromptResponse; + logger.info(`Generated location prompt: ${locationPrompt}`); + + // Step 3: Generate Chinese prompt using LMStudio API + logger.info('Step 3: Generating Chinese prompt for model transformation...'); + const chinesePromptRequest = `Generate a Chinese prompt for image transformation that describes: +- Prefix: genereate a portarit photo of a woman in image1 +- Use outfit to: ${outfitPrompt} +- Use location to: ${locationPrompt} + +Return the result in this format: {"result":""}`; + + const chinesePromptResponse = await callLmstudio(chinesePromptRequest); + const chinesePrompt = chinesePromptResponse.result || chinesePromptResponse; + logger.info(`Generated Chinese prompt: ${chinesePrompt}`); + + // Process model with outfit and location using the Chinese prompt + logger.info('Step 4: Processing model with outfit and location...'); + const modelImagePath = path.join(outputDir, `model_${timestamp}.png`); + + // Copy model image to ComfyUI input directory + const inputFolderFullPath = SERVER1_COMFY_OUTPUT_DIR.replace('output', 'input'); + await fs.mkdir(inputFolderFullPath, { recursive: true }); + const modelFileName = path.basename(modelImagePath); + const inputModelPath = path.join(inputFolderFullPath, modelFileName); + await fs.copyFile(modelImagePath, inputModelPath); + + // Convert image with Chinese prompt and pose + await processTwoImages( + `请将图1中模特的姿势更改为图2的姿势。, ${chinesePrompt}`, + modelFileName, + `pose_${timestamp}.png`, + `model_outfit_location_pose_${timestamp}.png`, + outputDir, + true + ); + + // Step 5: Add handbag to model + await processTwoImagesHandbag( + '请将图1中的女性修改成手持图2的包。', + `model_outfit_location_pose_${timestamp}.png`, + `handbag_${timestamp}.png`, + `model_outfit_location_handbag1_${timestamp}.png`, + outputDir + ); + + + await processTwoImagesHandbag( + '请让图1的女性看起来像是在手里拿着图2的包。', + `model_outfit_location_pose_${timestamp}.png`, + `handbag_${timestamp}.png`, + `model_outfit_location_handbag2_${timestamp}.png`, + outputDir + ); + + await processTwoImagesHandbag( + '请将图1中的女性修改成双手拿着图2的包。', + `model_outfit_location_pose_${timestamp}.png`, + `handbag_${timestamp}.png`, + `model_outfit_location_handbag3_${timestamp}.png`, + outputDir + ); + + await upscaleAndFix( + `model_outfit_location_handbag1_${timestamp}.png`, + `model_${timestamp}.png`, + `model_outfit_location_handbag1_upscaled_${timestamp}.png`, + outputDir + ); + + await upscaleAndFix( + `model_outfit_location_handbag2_${timestamp}.png`, + `model_${timestamp}.png`, + `model_outfit_location_handbag2_upscaled_${timestamp}.png`, + outputDir + ); + + await upscaleAndFix( + `model_outfit_location_handbag3_${timestamp}.png`, + `model_${timestamp}.png`, + `model_outfit_location_handbag3_upscaled_${timestamp}.png`, + outputDir + ); + + + logger.info(`\n${'='.repeat(80)}`); + logger.info(`ITERATION ${iteration} COMPLETED!`); + logger.info(`Generated files are saved in: ${outputDir}`); + logger.info(`${'='.repeat(80)}\n`); + + } catch (error) { + logger.error(`Error in iteration ${iteration}:`, error); + throw error; + } +} + +/** + * Main execution function with infinite iteration + */ +async function main() { + let iteration = 1; + + try { + logger.info('Starting infinite processing loop...'); + logger.info('Press Ctrl+C to stop the process\n'); + + while (true) { + await processIteration(iteration); + iteration++; + + // Small delay between iterations + logger.info('Waiting 5 seconds before next iteration...\n'); + await new Promise(resolve => setTimeout(resolve, 5000)); + } + } catch (error) { + logger.error('Error in main execution:', error); + process.exit(1); + } +} + +// Execute main function if this file is run directly +if (require.main === module) { + main(); +} + +export { processImage, convertImageWithPrompt, processTwoImages, processIteration, main };