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"kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "clip_h3" ], "widgets_values_named": { "Constant": "clip_h3" }, "color": "#432", "bgcolor": "#653" }, { "id": 152, "type": "GetNode", "pos": [ 1736.3480029312675, -218.22060141012153 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 21, "mode": 0, "inputs": [], "outputs": [ { "name": "*", "type": "*", "links": [] } ], "title": "Get_pdd_sigmas", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "pdd_sigmas" ], "widgets_values_named": { "Constant": "pdd_sigmas" } }, { "id": 142, "type": "SetNode", "pos": [ 542.6842287926896, -108.31464034192885 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 104, "mode": 0, "inputs": [ { "name": "IMAGE", "type": "IMAGE", "link": 352 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": null } ], "title": "Set_first_frames", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "first_frames", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "first_frames" ], "widgets_values_named": { "Constant": "first_frames" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 133, "type": "SetNode", "pos": [ 2025.912755096627, 378.7702187411243 ], "size": [ 228.4419921875, 60 ], "flags": { "collapsed": true }, "order": 99, "mode": 0, "inputs": [ { "name": "IMAGE", "type": "IMAGE", "link": 289 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": null } ], "title": "Set_first_pass_result_frames", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "first_pass_result_frames", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "first_pass_result_frames" ], "widgets_values_named": { "Constant": "first_pass_result_frames" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 46, "type": "CreateVideo", "pos": [ 2795.4785804381545, -708.2299527390891 ], "size": [ 300, 126 ], "flags": {}, "order": 64, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 286 }, { "name": "audio", "shape": 7, "type": "AUDIO", "link": 417 }, { "name": "fps", "type": "FLOAT", "widget": { "name": "fps" }, "link": 340 } ], "outputs": [ { "name": "VIDEO", "type": "VIDEO", "links": [ 76 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "CreateVideo", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ 24, 8, "sRGB" ], "widgets_values_named": { "fps": 24, "bit_depth": 8, "color_space": "sRGB" } }, { "id": 108, "type": "GetNode", "pos": [ -122.93480925596202, -542.9599175481366 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 22, "mode": 0, "inputs": [], "outputs": [ { "name": "AUDIO", "type": "AUDIO", "links": [] } ], "title": "Get_audio_original", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "audio_original" ], "widgets_values_named": { "Constant": "audio_original" } }, { "id": 103, "type": "GetNode", "pos": [ -113.93120217944634, -696.4701205561989 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 23, "mode": 0, "inputs": [], "outputs": [ { "name": "VAE", "type": "VAE", "links": [ 237 ] } ], "title": "Get_video_vae", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "video_vae" ], "widgets_values_named": { "Constant": "video_vae" }, "color": "#322", "bgcolor": "#533" }, { "id": 6, "type": "ComfyMathExpression", "pos": [ -2548.756609255668, -413.09676205385546 ], "size": [ 225, 128 ], "flags": { "collapsed": true }, "order": 68, "mode": 0, "inputs": [ { "label": "a", "name": "values.a", "type": "FLOAT,INT,BOOLEAN", "link": 1 }, { "label": "b", "name": "values.b", "shape": 7, "type": "FLOAT,INT,BOOLEAN", "link": null } ], "outputs": [ { "name": "FLOAT", "type": "FLOAT", "links": [] }, { "name": "INT", "type": "INT", "links": [ 617 ] }, { "name": "BOOL", "type": "BOOLEAN", "links": [] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "ComfyMathExpression", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "max(5, round(a * 24)) + (5 - (max(5, round(a * 24)) % 17)) % 17" ], "widgets_values_named": { "expression": "max(5, round(a * 24)) + (5 - (max(5, round(a * 24)) % 17)) % 17" } }, { "id": 236, "type": "VHS_VideoInfo", "pos": [ -2145.872420165265, -5.3168749031513185 ], "size": [ 234.931640625, 206 ], "flags": { "collapsed": true }, "order": 114, "mode": 0, "inputs": [ { "name": "video_info", "type": "VHS_VIDEOINFO", "link": 618 } ], "outputs": [ { "name": "source_fps🟨", "type": "FLOAT", "links": null }, { "name": "source_frame_count🟨", "type": "INT", "links": null }, { "name": "source_duration🟨", "type": "FLOAT", "links": null }, { "name": "source_width🟨", "type": "INT", "links": null }, { "name": "source_height🟨", "type": "INT", "links": null }, { "name": "loaded_fps🟦", "type": "FLOAT", "links": null }, { "name": "loaded_frame_count🟦", "type": "INT", "links": [ 451 ] }, { "name": "loaded_duration🟦", "type": "FLOAT", "links": null }, { "name": "loaded_width🟦", "type": "INT", "links": null }, { "name": "loaded_height🟦", "type": "INT", "links": null } ], "properties": { "cnr_id": "comfyui-videohelpersuite", "ver": "993082e4f2473bf4acaf06f51e33877a7eb38960", "Node name for S&R": "VHS_VideoInfo", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": {} }, { "id": 340, "type": "GetNode", "pos": [ 3715.4908339144304, -224.5115534499018 ], "size": [ 229.9048828125, 58 ], "flags": { "collapsed": true }, "order": 24, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 648, 653 ] } ], "title": "Get_first_pass_result_frames", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "first_pass_result_frames" ], "widgets_values_named": { "Constant": "first_pass_result_frames" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 339, "type": "GetImageSize", "pos": [ 3753.3058532675955, -150.12680223403095 ], "size": [ 140, 124 ], "flags": { "collapsed": true }, "order": 65, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 653 } ], "outputs": [ { "name": "width", "type": "INT", "links": [ 655 ] }, { "name": "height", "type": "INT", "links": [ 656 ] }, { "name": "batch_size", "type": "INT", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "GetImageSize", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [], "widgets_values_named": {} }, { "id": 176, "type": "Note", "pos": [ -4141.988434238028, -781.7497981616898 ], "size": [ 670.8119022955361, 633.2092097514608 ], "flags": {}, "order": 25, "mode": 0, "inputs": [], "outputs": [], "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "H3 Models\n\nhttps://huggingface.co/Comfy-Org/MiniMax-H3/tree/main\n\n\nhttps://github.com/Jalen-Brunson/ComfyUI-MiniMax-H3-PDD-Acc.git\n\n/models/pdd_acc/ (optional if uses PDD_ACC)\n\nwget https://huggingface.co/aptech0081/MiniMax-H3-Acc-LoRAs-ComfyUI/resolve/main/minimax_h3_ref2va_pdd_acc_8step_comfyui.safetensors --content-disposition\n\n\nUpscaler (optional)\n\nhttps://huggingface.co/LBH-123-AI/Minimax_h3_latent_Upscaler/blob/main/minimax_h3_latent_upscaler_3d_fp16.safetensors\n\nhttps://github.com/LBH-123-AI/Comfyui_Minimax_h3_latent_Upscaler\n\nText Encoder (Prompt Extract Face Details)\n\nhttps://huggingface.co/ethanfel/Qwen3-VL-4B-Heretic-ComfyUI-ConvRot-INT8/blob/main/qwen3-vl-4b-heretic_int8_dynamic_convrot.safetensors\n\nCustom Nodes (required)\n\nhttps://github.com/ostris/ComfyUI-AIToolkit-MiniMaxH3\n\nVAE for Preview\n\n/models/vae_approx/\n\nhttps://huggingface.co/Kijai/MiniMax-H3-TAE/blob/main/vae_approx/taeh3.safetensors\n\nor by hf\n/data/comfyui/models/vae_approx# hf download Kijai/MiniMax-H3-TAE vae_approx/taeh3.safetensors --local-dir .\n\n" ], "widgets_values_named": { "text": "H3 Models\n\nhttps://huggingface.co/Comfy-Org/MiniMax-H3/tree/main\n\n\nhttps://github.com/Jalen-Brunson/ComfyUI-MiniMax-H3-PDD-Acc.git\n\n/models/pdd_acc/ (optional if uses PDD_ACC)\n\nwget https://huggingface.co/aptech0081/MiniMax-H3-Acc-LoRAs-ComfyUI/resolve/main/minimax_h3_ref2va_pdd_acc_8step_comfyui.safetensors --content-disposition\n\n\nUpscaler (optional)\n\nhttps://huggingface.co/LBH-123-AI/Minimax_h3_latent_Upscaler/blob/main/minimax_h3_latent_upscaler_3d_fp16.safetensors\n\nhttps://github.com/LBH-123-AI/Comfyui_Minimax_h3_latent_Upscaler\n\nText Encoder (Prompt Extract Face Details)\n\nhttps://huggingface.co/ethanfel/Qwen3-VL-4B-Heretic-ComfyUI-ConvRot-INT8/blob/main/qwen3-vl-4b-heretic_int8_dynamic_convrot.safetensors\n\nCustom Nodes (required)\n\nhttps://github.com/ostris/ComfyUI-AIToolkit-MiniMaxH3\n\nVAE for Preview\n\n/models/vae_approx/\n\nhttps://huggingface.co/Kijai/MiniMax-H3-TAE/blob/main/vae_approx/taeh3.safetensors\n\nor by hf\n/data/comfyui/models/vae_approx# hf download Kijai/MiniMax-H3-TAE vae_approx/taeh3.safetensors --local-dir .\n\n" }, "color": "#432", "bgcolor": "#653" }, { "id": 336, "type": "SomethingToString", "pos": [ 3728.9319204580534, -503.44810708454554 ], "size": [ 270, 82 ], "flags": { "collapsed": true }, "order": 93, "mode": 0, "inputs": [ { "name": "input", "type": "*", "link": 650 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 646 ] } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "SomethingToString", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "(", "x" ], "widgets_values_named": { "prefix": "(", "suffix": "x" } }, { "id": 337, "type": "SomethingToString", "pos": [ 3732.253811400289, -443.07050817830765 ], "size": [ 270, 82 ], "flags": { "collapsed": true }, "order": 94, "mode": 0, "inputs": [ { "name": "input", "type": "*", "link": 651 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 647 ] } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "SomethingToString", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "", ")" ], "widgets_values_named": { "prefix": "", "suffix": ")" } }, { "id": 8, "type": "ImageResizeKJv2", "pos": [ -2137.5890300050246, -129.74213104929785 ], "size": [ 270, 336.00000000000006 ], "flags": { "collapsed": true }, "order": 112, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 616 }, { "name": "mask", "shape": 7, "type": "MASK", "link": null }, { "name": "width", "type": "INT", "widget": { "name": "width" }, "link": 17 }, { "name": "height", "type": "INT", "widget": { "name": "height" }, "link": 18 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 239 ] }, { "name": "width", "type": "INT", "links": [] }, { "name": "height", "type": "INT", "links": [] }, { "name": "mask", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "ImageResizeKJv2", "aux_id": "aining2022/ComfyUI_Swwan", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 512, 512, "lanczos", "resize", "0, 0, 0", "center", 2, "cpu" ], "widgets_values_named": { "width": 512, "height": 512, "upscale_method": "lanczos", "keep_proportion": "resize", "pad_color": "0, 0, 0", "crop_position": "center", "divisible_by": 2, "device": "cpu" } }, { "id": 100, "type": "GetNode", "pos": [ 494.9909922514548, -436.98150377199715 ], "size": [ 210, 58 ], "flags": { "collapsed": true }, "order": 26, "mode": 0, "inputs": [], "outputs": [ { "name": "VAE", "type": "VAE", "links": [ 231 ] } ], "title": "Get_video_vae", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "video_vae" ], "widgets_values_named": { "Constant": "video_vae" }, "color": "#322", "bgcolor": "#533" }, { "id": 81, "type": "MiniMaxH3AddGuide", "pos": [ 816.8004754108588, -560.158488281434 ], "size": [ 274.640234375, 158 ], "flags": {}, "order": 70, "mode": 0, "inputs": [ { "name": "positive", "type": "CONDITIONING", "link": 715 }, { "name": "latent", "type": "LATENT", "link": 753 }, { "name": "vae", "shape": 7, "type": "VAE", "link": 231 }, { "name": "audio_vae", "shape": 7, "type": "VAE", "link": null }, { "name": "image", "shape": 7, "type": "IMAGE", "link": 743 }, { "name": "audio", "shape": 7, "type": "AUDIO", "link": null } ], "outputs": [ { "name": "positive", "type": "CONDITIONING", "links": [ 737, 738 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "MiniMaxH3AddGuide", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 0 ], "widgets_values_named": { "frame_idx": 0 } }, { "id": 144, "type": "GetNode", "pos": [ 521.6508068477432, -379.3107159111921 ], "size": [ 210, 58 ], "flags": { "collapsed": true }, "order": 27, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 743 ] } ], "title": "Get_first_frames", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "first_frames" ], "widgets_values_named": { "Constant": "first_frames" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 123, "type": "GetNode", "pos": [ -114.74557642728573, -494.1216284946731 ], "size": [ 210, 50 ], "flags": { "collapsed": true }, "order": 28, "mode": 0, "inputs": [], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 265, 612 ] } ], "title": "Get_final_prompt", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "final_prompt" ], "widgets_values_named": { "Constant": "final_prompt" } }, { "id": 11, "type": "CFGGuider", "pos": [ 1658.2157654419043, -505.3382536844294 ], "size": [ 270, 98 ], "flags": {}, "order": 89, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 385 }, { "name": "positive", "type": "CONDITIONING", "link": 737 }, { "name": "negative", "type": "CONDITIONING", "link": 738 } ], "outputs": [ { "name": "GUIDER", "type": "GUIDER", "links": [ 8 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "CFGGuider", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 1 ], "widgets_values_named": { "cfg": 1 } }, { "id": 141, "type": "GetNode", "pos": [ 571.3654880232812, -572.9418730628773 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 29, "mode": 0, "inputs": [], "outputs": [ { "name": "CONDITIONING", "type": "CONDITIONING", "links": [ 715 ] } ], "title": "Get_first_positive", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "first_positive" ], "widgets_values_named": { "Constant": "first_positive" }, "color": "#332922", "bgcolor": "#593930" }, { "id": 363, "type": "GetNode", "pos": [ -104.90058765589971, -595.7793717415992 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 30, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 713 ] } ], "title": "Get_ref_image", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "ref_image" ], "widgets_values_named": { "Constant": "ref_image" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 237, "type": "SetNode", "pos": [ -2146.348429051246, 52.66591350328379 ], "size": [ 210, 58 ], "flags": { "collapsed": true }, "order": 124, "mode": 0, "inputs": [ { "name": "INT", "type": "INT", "link": 451 } ], "outputs": [ { "name": "INT", "type": "INT", "links": null } ], "title": "Set_loaded_frame_count", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "loaded_frame_count", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "loaded_frame_count" ], "widgets_values_named": { "Constant": "loaded_frame_count" }, "color": "#1b4669", "bgcolor": "#29699c" }, { "id": 104, "type": "SetNode", "pos": [ -2137.9397674080906, -70.57960371931813 ], "size": [ 213.136328125, 60 ], "flags": { "collapsed": true }, "order": 122, "mode": 0, "inputs": [ { "name": "IMAGE", "type": "IMAGE", "link": 239 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [] } ], "title": "Set_body_reference_video", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "body_reference_video", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "body_reference_video" ], "widgets_values_named": { "Constant": "body_reference_video" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 181, "type": "BasicScheduler", "pos": [ 1719.1992687304644, -61.70582083486841 ], "size": [ 256.17751364710057, 113.88354175534164 ], "flags": {}, "order": 84, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 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{ "id": 106, "type": "SetNode", "pos": [ -2458.6683998928943, 49.969754900244546 ], "size": [ 210.83905452888257, 60 ], "flags": { "collapsed": true }, "order": 123, "mode": 0, "inputs": [ { "name": "AUDIO", "type": "AUDIO", "link": 799 } ], "outputs": [ { "name": "AUDIO", "type": "AUDIO", "links": [] } ], "title": "Set_audio_original", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "audio_original", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "audio_original" ], "widgets_values_named": { "Constant": "audio_original" } }, { "id": 362, "type": "ImageResizeKJv2", "pos": [ -2237.5973606349608, 181.43715257734868 ], "size": [ 270, 336 ], "flags": { "collapsed": true }, "order": 79, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 691 }, { "name": "mask", "shape": 7, "type": "MASK", "link": null } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 692 ] }, { "name": "width", "type": "INT", "links": null }, { "name": "height", "type": "INT", "links": null }, { "name": "mask", "type": "MASK", "links": null } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "ImageResizeKJv2", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 512, 512, "lanczos", "resize", "0, 0, 0", "center", 2, "cpu" ], "widgets_values_named": { "width": 512, "height": 512, "upscale_method": "lanczos", "keep_proportion": "resize", "pad_color": "0, 0, 0", "crop_position": "center", "divisible_by": 2, "device": "cpu" } }, { "id": 361, "type": "SetNode", "pos": [ -2231.4120600368597, 245.55468978300436 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 97, "mode": 0, "inputs": [ { "name": "IMAGE", "type": "IMAGE", "link": 692 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": null } ], "title": "Set_ref_image", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "ref_image", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "ref_image" ], "widgets_values_named": { "Constant": "ref_image" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 175, "type": "EmptyAudio", "pos": [ -2579.934612097621, -82.66646589706141 ], "size": [ 210, 106 ], "flags": { "collapsed": true }, "order": 69, "mode": 0, "inputs": [ { "name": "duration", "type": "FLOAT", "widget": { "name": "duration" }, "link": 353 } ], "outputs": [ { "name": "AUDIO", "type": "AUDIO", "links": [] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "EmptyAudio", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 60, 44100, 2 ], "widgets_values_named": { "duration": 60, "sample_rate": 44100, "channels": 2 } }, { "id": 375, "type": "GetNode", "pos": [ -1325.0933297637077, -1264.896494729541 ], "size": [ 210, 58 ], "flags": { "collapsed": true }, "order": 36, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 705 ] } ], "title": "Get_ref_image", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "ref_image" ], "widgets_values_named": { "Constant": "ref_image" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 417, "type": "GetNode", "pos": [ -1319.5481499987588, -1920.9106007108367 ], "size": [ 210, 34 ], "flags": { "collapsed": true }, "order": 37, "mode": 0, "inputs": [], "outputs": [ { "name": "CLIP", "type": "CLIP", "links": [ 812 ] } ], "title": "Get_clip_auto_prompt", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "clip_auto_prompt" ], "widgets_values_named": { "Constant": "clip_auto_prompt" }, "color": "#432", "bgcolor": "#653" }, { "id": 379, "type": "StringConcatenate", "pos": [ -1407.643049736263, -1202.8758734003954 ], "size": [ 762.7232728358504, 538.726313309814 ], "flags": { "collapsed": true }, "order": 38, "mode": 0, "inputs": [], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 706 ] } ], "title": "Prompt Template With Ref Image", "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "StringConcatenate", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "You receive:\n\n* several frames from a source video\n* a style reference image\n* a user text request describing the desired look\n\nAnalyze the style image to identify what a painter would copy, then convert the\nuser's request into one concise restyle instruction.\n\nOutput ONLY the final prompt.\nAlways output English.\nAlways start exactly with:\n\nstyle_transfer:\n\nThe style image defines HOW the video should look.\nThe user text defines any constraint on the edit.\nThe frames only tell you what is being restyled -- never describe them.\n\nThe reference image enters the model as . Refer to it by that exact tag.\n\nDEFAULT FORM -- use this whenever a style image is provided:\n\n this video in the style of : <3 to 5 visual attributes>.\n\nVerbs, in the order they appear in training: Re-render, Restyle, Apply, Transfer,\nRender, Reinterpret. Use no other verb.\n\nLength: 15 to 24 words, median 21.\n\nExample:\n[style image: flat pop-art portrait, yellow background, halftone dots]\n-> style_transfer: Re-render this video with the style of : bold graphic\n style, vibrant colours, clean lines, flat shading, halftone pattern.\n\nExample:\n[style image: thick oil painting, muted earth tones]\n-> style_transfer: Restyle this video in the style of : loose visible\n brushstrokes, muted earth palette, soft edges, thick impasto texture.\n\nTHE ATTRIBUTES ARE THE WHOLE JOB. Write 3 to 5, comma separated, lowercase,\ncovering only what a painter would copy:\n\n linework, brushwork, palette, shading, contrast, texture, finish, level of detail\n\nVocabulary that appears in training, by frequency:\n linework(36) soft(35) bold(35) vibrant(31) shading(29) palette(26) clean(25)\n texture(24) lines(23) contrast(21) outlines(19) colours(18) subtle(17) tones(17)\n delicate(16) geometric(16) flat(15) shapes(14) finish(14) thick(14)\n brushstrokes(14) detail(13) rich(12) shadows(12)\n\nNEVER name an artist, a movement, a country, a decade or a franchise in the\nattributes. \"andy warhol style\" resolves the task from text alone and the model\nstops looking at -- the reference goes inert. Write what the image\nLOOKS like, not what it IS.\n\nNEVER describe the content of the style image. No person, face, portrait, figure,\nlandscape, object, animal, scene. 31% of style references are portraits, and naming\nthe subject is what makes the model transfer the character into the video instead of\nthe style. Attributes only.\n\nSHORT FORM -- when no style image is available or the user wants a bare prompt:\n\nstyle_transfer: Transfer the visual style of onto this video.\nstyle_transfer: Reinterpret this video in the style of .\nstyle_transfer: Render this video in the style shown in .\n\n9 to 11 words. Same verbs.\n\nNAMED FORM -- only when the user names a style AND provides no image:\n\nstyle_transfer: Make it cinematic style.\nstyle_transfer: Change this video to studio ghibli style.\nstyle_transfer: Transform it into art deco.\n\n4 to 10 words. Free wording. Verbs seen: Make, Apply, Stylize, Render, Restyle,\nOutput, Modify, Transform, Create, Remake, Reproduce.\n\nNEVER mix a style name with in the same sentence. No training caption\ndoes, and the model follows the text and ignores the image when both are present.\n\nDo not mention the frames.\nDo not invent unrelated details.\nDo not add extra edits.\nOutput one instruction only.\n\nNow wait for the user's text request, the style image and the video frames.\n", "", "" ], "widgets_values_named": { "string_a": "You receive:\n\n* several frames from a source video\n* a style reference image\n* a user text request describing the desired look\n\nAnalyze the style image to identify what a painter would copy, then convert the\nuser's request into one concise restyle instruction.\n\nOutput ONLY the final prompt.\nAlways output English.\nAlways start exactly with:\n\nstyle_transfer:\n\nThe style image defines HOW the video should look.\nThe user text defines any constraint on the edit.\nThe frames only tell you what is being restyled -- never describe them.\n\nThe reference image enters the model as . Refer to it by that exact tag.\n\nDEFAULT FORM -- use this whenever a style image is provided:\n\n this video in the style of : <3 to 5 visual attributes>.\n\nVerbs, in the order they appear in training: Re-render, Restyle, Apply, Transfer,\nRender, Reinterpret. Use no other verb.\n\nLength: 15 to 24 words, median 21.\n\nExample:\n[style image: flat pop-art portrait, yellow background, halftone dots]\n-> style_transfer: Re-render this video with the style of : bold graphic\n style, vibrant colours, clean lines, flat shading, halftone pattern.\n\nExample:\n[style image: thick oil painting, muted earth tones]\n-> style_transfer: Restyle this video in the style of : loose visible\n brushstrokes, muted earth palette, soft edges, thick impasto texture.\n\nTHE ATTRIBUTES ARE THE WHOLE JOB. Write 3 to 5, comma separated, lowercase,\ncovering only what a painter would copy:\n\n linework, brushwork, palette, shading, contrast, texture, finish, level of detail\n\nVocabulary that appears in training, by frequency:\n linework(36) soft(35) bold(35) vibrant(31) shading(29) palette(26) clean(25)\n texture(24) lines(23) contrast(21) outlines(19) colours(18) subtle(17) tones(17)\n delicate(16) geometric(16) flat(15) shapes(14) finish(14) thick(14)\n brushstrokes(14) detail(13) rich(12) shadows(12)\n\nNEVER name an artist, a movement, a country, a decade or a franchise in the\nattributes. \"andy warhol style\" resolves the task from text alone and the model\nstops looking at -- the reference goes inert. Write what the image\nLOOKS like, not what it IS.\n\nNEVER describe the content of the style image. No person, face, portrait, figure,\nlandscape, object, animal, scene. 31% of style references are portraits, and naming\nthe subject is what makes the model transfer the character into the video instead of\nthe style. Attributes only.\n\nSHORT FORM -- when no style image is available or the user wants a bare prompt:\n\nstyle_transfer: Transfer the visual style of onto this video.\nstyle_transfer: Reinterpret this video in the style of .\nstyle_transfer: Render this video in the style shown in .\n\n9 to 11 words. Same verbs.\n\nNAMED FORM -- only when the user names a style AND provides no image:\n\nstyle_transfer: Make it cinematic style.\nstyle_transfer: Change this video to studio ghibli style.\nstyle_transfer: Transform it into art deco.\n\n4 to 10 words. Free wording. Verbs seen: Make, Apply, Stylize, Render, Restyle,\nOutput, Modify, Transform, Create, Remake, Reproduce.\n\nNEVER mix a style name with in the same sentence. No training caption\ndoes, and the model follows the text and ignores the image when both are present.\n\nDo not mention the frames.\nDo not invent unrelated details.\nDo not add extra edits.\nOutput one instruction only.\n\nNow wait for the user's text request, the style image and the video frames.\n", "string_b": "", "delimiter": "" } }, { "id": 418, "type": "TextGenerate", "pos": [ -1044.544716355421, -1932.4825292780756 ], "size": [ 541.818181818182, 412 ], "flags": { "collapsed": false }, "order": 92, "mode": 0, "inputs": [ { "name": "clip", "type": "CLIP", "link": 812 }, { "name": "image", "shape": 7, "type": "IMAGE", "link": null }, { "name": "video", "shape": 7, "type": "IMAGE", "link": null }, { "name": "audio", "shape": 7, "type": "AUDIO", "link": null }, { "name": "prompt", "type": "STRING", "widget": { "name": "prompt" }, "link": 820 } ], "outputs": [ { "name": "generated_text", "type": "STRING", "links": [ 814 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.20.1", "Node name for S&R": "TextGenerate", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "", 4133, "on", 0.7, 64, 0.95, 0.05, 1.05, 1, 0, true, true ], "widgets_values_named": { "prompt": "", "max_length": 4133, "sampling_mode": "on", "sampling_mode.temperature": 0.7, "sampling_mode.top_k": 64, "sampling_mode.top_p": 0.95, "sampling_mode.min_p": 0.05, "sampling_mode.repetition_penalty": 1.05, "sampling_mode.seed": 1, "sampling_mode.presence_penalty": 0, "thinking": true, "use_default_template": true } }, { "id": 374, "type": "GetNode", "pos": [ -1358.018537833506, -1330.2518314942984 ], "size": [ 210, 50 ], "flags": { "collapsed": true }, "order": 39, "mode": 0, "inputs": [], "outputs": [ { "name": "CLIP", "type": "CLIP", "links": [ 704 ] } ], "title": "Get_clip_auto_prompt", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "clip_auto_prompt" ], "widgets_values_named": { "Constant": "clip_auto_prompt" }, "color": "#432", "bgcolor": "#653" }, { "id": 376, "type": "TextGenerate", "pos": [ -991.5617066566048, -1358.084427053384 ], "size": [ 541.818181818182, 412 ], "flags": { "collapsed": false }, "order": 72, "mode": 0, "inputs": [ { "name": "clip", "type": "CLIP", "link": 704 }, { "name": "image", "shape": 7, "type": "IMAGE", "link": 705 }, { "name": "video", "shape": 7, "type": "IMAGE", "link": null }, { "name": "audio", "shape": 7, "type": "AUDIO", "link": null }, { "name": "prompt", "type": "STRING", "widget": { "name": "prompt" }, "link": 706 } ], "outputs": [ { "name": "generated_text", "type": "STRING", "links": [ 707 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.20.1", "Node name for S&R": "TextGenerate", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "", 4133, "on", 0.7, 64, 0.95, 0.05, 1.05, 1, 0, true, true ], "widgets_values_named": { "prompt": "", "max_length": 4133, "sampling_mode": "on", "sampling_mode.temperature": 0.7, "sampling_mode.top_k": 64, "sampling_mode.top_p": 0.95, "sampling_mode.min_p": 0.05, "sampling_mode.repetition_penalty": 1.05, "sampling_mode.seed": 1, "sampling_mode.presence_penalty": 0, "thinking": true, "use_default_template": true } }, { "id": 420, "type": "PreviewAny", "pos": [ -316.3921124668553, -1903.0781682413767 ], "size": [ 552.2568945952953, 360.5576118068452 ], "flags": {}, "order": 108, "mode": 0, "inputs": [ { "name": "source", "type": "*", "link": 814 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 853 ] } ], "title": "Prompt Preview", "properties": { "cnr_id": "comfy-core", "ver": "0.20.1", "Node name for S&R": "PreviewAny", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [], "widgets_values_named": {} }, { "id": 378, "type": "PreviewAny", "pos": [ -354.5525790208971, -1339.916379034733 ], "size": [ 552.2568945952953, 360.5576118068452 ], "flags": {}, "order": 91, "mode": 0, "inputs": [ { "name": "source", "type": "*", "link": 707 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 854 ] } ], "title": "Prompt Preview", "properties": { "cnr_id": "comfy-core", "ver": "0.20.1", "Node name for S&R": "PreviewAny", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [], "widgets_values_named": {} }, { "id": 13, "type": "RandomNoise", "pos": [ -1766.655580085758, -0.5854095952166254 ], "size": [ 270, 82 ], "flags": {}, "order": 40, "mode": 0, "inputs": [], "outputs": [ { "name": "NOISE", "type": "NOISE", "links": [ 321 ] } ], "title": "Seed", "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "RandomNoise", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 42, "fixed" ], "widgets_values_named": { "noise_seed": 42, "control_after_generate": "fixed" } }, { "id": 153, "type": "SetNode", "pos": [ -1344.4612950009746, 25.120491716050896 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 73, "mode": 0, "inputs": [ { "name": "NOISE", "type": "NOISE", "link": 321 } ], "outputs": [ { "name": "NOISE", "type": "NOISE", "links": null } ], "title": "Set_noise", "properties": { "Node name for S&R": "SetNode", "aux_id": "kijai/ComfyUI-KJNodes", "previousName": "noise", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "noise" ], "widgets_values_named": { "Constant": "noise" }, "color": "#2e2e2e", "bgcolor": "#242121" }, { "id": 445, "type": "GetNode", "pos": [ -1767.6859895556584, -383.2375522327724 ], "size": [ 210, 60 ], "flags": { "collapsed": true }, "order": 41, "mode": 0, "inputs": [], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 855 ] } ], "title": "Get_final_prompt", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "final_prompt" ], "widgets_values_named": { "Constant": "final_prompt" } }, { "id": 9, "type": "MiniMaxH3SigmaShift", "pos": [ -1082.9104824609735, -689.762683204829 ], "size": [ 380, 82 ], "flags": {}, "order": 55, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 257 } ], "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 124 ] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "MiniMaxH3SigmaShift", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ 12, 3 ], "widgets_values_named": { "shift_video": 12, "shift_audio": 3 }, "color": "#322", "bgcolor": "#533" }, { "id": 416, "type": "StringConcatenate", "pos": [ -1367.3045951345684, -1808.205025528254 ], "size": [ 762.7232728358504, 538.726313309814 ], "flags": { "collapsed": true }, "order": 75, "mode": 0, "inputs": [ { "name": "string_b", "type": "STRING", "widget": { "name": "string_b" }, "link": 857 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 820 ] } ], "title": "Prompt Template Without Ref Image", "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "StringConcatenate", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "You rewrite a video-editing request into the exact instruction format this LoRA was trained on.\nOutput the final prompt ONLY — no explanation, no preamble, no quotes around it.\nAlways output English, whatever language the request is written in.\n\nEvery hard number in this document is measured from the 1000 RefVideo6M retexture captions\n(1000 instructions) that the retexture LoRA actually trained on.\n\n================================================================================\nTRIGGER — MANDATORY\n===================\n\nEvery output begins with exactly:\n\nretexture:\n\nNever omit it, translate it, alter it, put anything before it, or write it twice.\n\n================================================================================\nANALYZE THE VIDEO FRAMES FIRST — MANDATORY\n==========================================\n\nBefore writing the prompt, analyze the available video frames carefully.\n\nUse the frames to understand:\n\n* which object the user's request refers to, and what it currently looks like\n* its present material and finish — matte or glossy, rough or smooth, woven, knitted, painted,\n wet, dusty, worn\n* its colour, because 49% of trained instructions name a colour\n* whether several similar objects exist, so the one you name is unambiguous\n* the scale at which the texture is visible: a distant cliff needs coarse words, a sleeve in\n close-up can take pores, fibres and weave\n\nThe object name in the instruction must match what is visible: 91% of trained instructions\ntarget \"the \" with a definite article, and the model finds the object through that\nnoun phrase alone. \"Make the jacket matte\" fails when the frame holds two jackets.\n\nDo not mention the analysis in the output. Never write \"based on the frames\", \"as seen in the\nvideo\", \"the frames show\". Do not invent details that are not visible or stated by the user.\n\n================================================================================\nTHE MATERIAL REFERENCE IMAGE — IT BECOMES WORDS, NOT INPUT\n==========================================================\n\nThe retexture LoRA was trained on guide latents only: the source video and the text. It has NO\nreference-image input. A material reference the user supplies is therefore YOUR input, not the\nmodel's — you look at it and convert it into the qualifiers of the instruction.\n\nRead from the reference: finish (matte / satin / glossy / metallic), relief (smooth / grainy /\nribbed / quilted / cracked), weave or grain if any, dominant colour, and any distinctive marking.\nThen write those as the target texture. Never write \"like the reference image\", \"matching\n\", or any pointer to it — the model cannot see it and the phrase is off-distribution.\n\n reference: photo of scuffed black leather\n -> retexture: Turn the black jacket's texture from matte fabric to worn glossy leather with\n soft creases and scuffed highlights.\n\n================================================================================\nHOW MANY INSTRUCTIONS — EXACTLY ONE\n===================================\n\nEvery one of the 1000 trained captions carries exactly ONE instruction. Not a majority: all of\nthem. This LoRA has never seen two edits in one prompt.\n\nOne object, one texture change, one sentence. If the user asks for two surfaces, that is two\nseparate runs — do not chain them with \"and\" or with a second sentence.\n\n================================================================================\nINSTRUCTION FORMAT\n==================\n\nThe sentence starts with one of these five verbs — and only these five. The percentage is that\nverb's share of the 1000 trained instructions:\n\n Make the . 42%\n Turn the ['s texture] into/from ... to . 28%\n Change the ['s texture] to . 19%\n Convert the 's texture to . 6%\n Retexture the to . 5%\n\n\"Apply\", \"Give\", \"Add\", \"Replace\", \"Restyle\", \"Set\" DO NOT EXIST in this LoRA's training data —\nzero occurrences in 1000 instructions. Never use them.\n\nLENGTH: median 9 words, mean 10, p10 6, p90 15. Aim for 8-14. This is a much shorter form than\na scene-editing prompt — the sentence names one object and one surface, nothing else.\n\nTHE WORD \"texture\" appears in 93% of trained instructions, and 41% use the possessive form\n\"the 's texture\". Writing it is close to mandatory:\n\n Make the cliffside texture darker, rougher, and more rugged with visible rocks.\n Convert the hand's texture to a natural, matte, skin-like texture with visible pores.\n Turn the box into rough texture.\n\nFROM/TO: 12% of trained instructions anchor both ends — \"from to \". Use this\nform when the frames show the current material clearly; it is the strongest form in the set\nbecause it tells the model what to stop doing as well as what to do:\n\n Turn the pink flowers' texture from soft and fuzzy to dense and granular.\n Turn the Beach's texture from Sandy to Smooth.\n\nQUALIFIERS: give two or three, not a bare material name. 17% of trained instructions stack\ncomma-separated qualifiers. The measured vocabulary, by frequency in the training captions:\n\n matte (178), rough (133), smooth (131), glossy (95), weathered (77), opaque (48),\n fibrous (35), stone-like (31), metallic (31), fuzzy (28), woven (28), fabric (28),\n translucent (24), reflective (24), grainy (21), coarse (17), dull (15), granular (14),\n speckled (14), brick (14), wood (13), spongy (11), sand (11), concrete (10), shiny (10),\n knitted (9), velvety (7), glass (7), fur (7), fine (6)\n\nPrefer a word from this list over a synonym the data never saw. \"Satin\" and \"lustrous\" are\noutside it; \"glossy\" and \"smooth\" are inside it.\n\nCOLOUR: 49% of trained instructions name a colour along with the texture. Include one when the\nuser asked for a colour change too, or when the colour identifies the object. Leave it out when\nthe user wants the colour preserved — and in that case say so explicitly, because the data\nmixes colour and texture freely and the model will otherwise drift:\n\n Turn the black jacket's texture to matte quilted nylon, keeping the black colour.\n\nPOSITION ANCHORS: only 8% of trained instructions carry one (\"the right building\", \"the left\nskirt\"). Use one only to disambiguate between similar objects, not as a habit.\n\n================================================================================\nWHAT THIS LoRA DOES NOT DO\n==========================\n\nRetexture changes the SURFACE of an object: material, finish, pattern, weave, colour. It never\nchanges shape, silhouette, garment type, or what the object is. Nothing in the 1000 training\ncaptions replaces one object with another.\n\n \"black jacket -> black leather jacket\" retexture — surface only\n \"black jacket -> hoodie\" NOT retexture; that is the tryon LoRA\n \"remove the jacket\" NOT retexture; that is object removal\n \"make the whole video look like an oil painting\" NOT retexture; that is style_transfer\n\nIf the request is one of those, say so instead of forcing it into this format.\n\n================================================================================\nEXAMPLES\n========\n\nRequest: \"a jaqueta preta do cara para couro\"\n[frames: one man in a matte black fabric jacket, medium shot]\n\nretexture: Turn the black jacket's texture from matte fabric to glossy black leather with soft\ncreases.\n\nRequest: \"deixa a parede com aspecto de concreto velho\"\n[frames: a smooth painted interior wall behind a seated woman]\n\nretexture: Make the wall texture weathered concrete, rough and grainy with visible stains.\n\nRequest: \"o sofá em veludo\"\n[frames: a beige leather sofa in a living room]\n\nretexture: Change the sofa's texture from smooth leather to soft velvety fabric with a fine nap.\n\nRequest: \"textura de tricô no suéter, mantendo a cor\"\n[frames: a woman in a plain dark green sweater]\n\nretexture: Make the sweater have a chunky knitted texture, keeping the dark green colour.\n\nRequest: \"a montanha mais realista\"\n[frames: a distant mountain range, flat-looking rock faces]\n\nretexture: Make the mountains have a realistic, weathered stone texture with rough, defined rock\nfaces.\n\nWRONG — two edits in one prompt, which the LoRA never saw:\nretexture: Make the jacket glossy leather and turn the wall into concrete.\n\nWRONG — verb outside the trained set, and a pointer to an image the model cannot see:\nretexture: Apply the material from the reference image to the jacket.\n\nRIGHT:\nretexture: Turn the jacket's texture to glossy dark leather with soft creases and scuffed\nhighlights.\n\nThe scene details in these examples belong to THESE examples only. Never carry \"jacket\", \"wall\"\nor \"sofa\" into another request — read the actual frames every time.\n\n================================================================================\nFINAL CHECK — RUN THIS BEFORE OUTPUT\n====================================\n\n1. Did you analyze the frames before writing?\n2. Does it start with \"retexture: \" exactly once?\n3. Is there exactly ONE instruction, one object, one surface?\n4. Does the sentence start with Make, Turn, Change, Convert or Retexture — and nothing else?\n5. Is it between 8 and 14 words?\n6. Does it contain the word \"texture\" (93% of training does)?\n7. Is the object named with a definite article and enough detail to be unambiguous in the frames?\n8. Did you give two or three qualifiers rather than a bare material name?\n9. Are the qualifiers drawn from the measured vocabulary above?\n10. If the frames show the current material clearly, did you use the \"from to \"\n form?\n11. If a reference image was supplied, did you convert it into words and avoid pointing at it?\n12. If the colour must stay, did you say so explicitly?\n13. Did you avoid changing shape, silhouette, garment type or object identity?\n14. Did you avoid inventing edits nobody asked for?\n15. Is every scene detail taken from THESE frames, not from an example in this document?\n\nIf any check fails, rewrite before answering. Output the prompt and nothing else.\n", "", "" ], "widgets_values_named": { "string_a": "You rewrite a video-editing request into the exact instruction format this LoRA was trained on.\nOutput the final prompt ONLY — no explanation, no preamble, no quotes around it.\nAlways output English, whatever language the request is written in.\n\nEvery hard number in this document is measured from the 1000 RefVideo6M retexture captions\n(1000 instructions) that the retexture LoRA actually trained on.\n\n================================================================================\nTRIGGER — MANDATORY\n===================\n\nEvery output begins with exactly:\n\nretexture:\n\nNever omit it, translate it, alter it, put anything before it, or write it twice.\n\n================================================================================\nANALYZE THE VIDEO FRAMES FIRST — MANDATORY\n==========================================\n\nBefore writing the prompt, analyze the available video frames carefully.\n\nUse the frames to understand:\n\n* which object the user's request refers to, and what it currently looks like\n* its present material and finish — matte or glossy, rough or smooth, woven, knitted, painted,\n wet, dusty, worn\n* its colour, because 49% of trained instructions name a colour\n* whether several similar objects exist, so the one you name is unambiguous\n* the scale at which the texture is visible: a distant cliff needs coarse words, a sleeve in\n close-up can take pores, fibres and weave\n\nThe object name in the instruction must match what is visible: 91% of trained instructions\ntarget \"the \" with a definite article, and the model finds the object through that\nnoun phrase alone. \"Make the jacket matte\" fails when the frame holds two jackets.\n\nDo not mention the analysis in the output. Never write \"based on the frames\", \"as seen in the\nvideo\", \"the frames show\". Do not invent details that are not visible or stated by the user.\n\n================================================================================\nTHE MATERIAL REFERENCE IMAGE — IT BECOMES WORDS, NOT INPUT\n==========================================================\n\nThe retexture LoRA was trained on guide latents only: the source video and the text. It has NO\nreference-image input. A material reference the user supplies is therefore YOUR input, not the\nmodel's — you look at it and convert it into the qualifiers of the instruction.\n\nRead from the reference: finish (matte / satin / glossy / metallic), relief (smooth / grainy /\nribbed / quilted / cracked), weave or grain if any, dominant colour, and any distinctive marking.\nThen write those as the target texture. Never write \"like the reference image\", \"matching\n\", or any pointer to it — the model cannot see it and the phrase is off-distribution.\n\n reference: photo of scuffed black leather\n -> retexture: Turn the black jacket's texture from matte fabric to worn glossy leather with\n soft creases and scuffed highlights.\n\n================================================================================\nHOW MANY INSTRUCTIONS — EXACTLY ONE\n===================================\n\nEvery one of the 1000 trained captions carries exactly ONE instruction. Not a majority: all of\nthem. This LoRA has never seen two edits in one prompt.\n\nOne object, one texture change, one sentence. If the user asks for two surfaces, that is two\nseparate runs — do not chain them with \"and\" or with a second sentence.\n\n================================================================================\nINSTRUCTION FORMAT\n==================\n\nThe sentence starts with one of these five verbs — and only these five. The percentage is that\nverb's share of the 1000 trained instructions:\n\n Make the . 42%\n Turn the ['s texture] into/from ... to . 28%\n Change the ['s texture] to . 19%\n Convert the 's texture to . 6%\n Retexture the to . 5%\n\n\"Apply\", \"Give\", \"Add\", \"Replace\", \"Restyle\", \"Set\" DO NOT EXIST in this LoRA's training data —\nzero occurrences in 1000 instructions. Never use them.\n\nLENGTH: median 9 words, mean 10, p10 6, p90 15. Aim for 8-14. This is a much shorter form than\na scene-editing prompt — the sentence names one object and one surface, nothing else.\n\nTHE WORD \"texture\" appears in 93% of trained instructions, and 41% use the possessive form\n\"the 's texture\". Writing it is close to mandatory:\n\n Make the cliffside texture darker, rougher, and more rugged with visible rocks.\n Convert the hand's texture to a natural, matte, skin-like texture with visible pores.\n Turn the box into rough texture.\n\nFROM/TO: 12% of trained instructions anchor both ends — \"from to \". Use this\nform when the frames show the current material clearly; it is the strongest form in the set\nbecause it tells the model what to stop doing as well as what to do:\n\n Turn the pink flowers' texture from soft and fuzzy to dense and granular.\n Turn the Beach's texture from Sandy to Smooth.\n\nQUALIFIERS: give two or three, not a bare material name. 17% of trained instructions stack\ncomma-separated qualifiers. The measured vocabulary, by frequency in the training captions:\n\n matte (178), rough (133), smooth (131), glossy (95), weathered (77), opaque (48),\n fibrous (35), stone-like (31), metallic (31), fuzzy (28), woven (28), fabric (28),\n translucent (24), reflective (24), grainy (21), coarse (17), dull (15), granular (14),\n speckled (14), brick (14), wood (13), spongy (11), sand (11), concrete (10), shiny (10),\n knitted (9), velvety (7), glass (7), fur (7), fine (6)\n\nPrefer a word from this list over a synonym the data never saw. \"Satin\" and \"lustrous\" are\noutside it; \"glossy\" and \"smooth\" are inside it.\n\nCOLOUR: 49% of trained instructions name a colour along with the texture. Include one when the\nuser asked for a colour change too, or when the colour identifies the object. Leave it out when\nthe user wants the colour preserved — and in that case say so explicitly, because the data\nmixes colour and texture freely and the model will otherwise drift:\n\n Turn the black jacket's texture to matte quilted nylon, keeping the black colour.\n\nPOSITION ANCHORS: only 8% of trained instructions carry one (\"the right building\", \"the left\nskirt\"). Use one only to disambiguate between similar objects, not as a habit.\n\n================================================================================\nWHAT THIS LoRA DOES NOT DO\n==========================\n\nRetexture changes the SURFACE of an object: material, finish, pattern, weave, colour. It never\nchanges shape, silhouette, garment type, or what the object is. Nothing in the 1000 training\ncaptions replaces one object with another.\n\n \"black jacket -> black leather jacket\" retexture — surface only\n \"black jacket -> hoodie\" NOT retexture; that is the tryon LoRA\n \"remove the jacket\" NOT retexture; that is object removal\n \"make the whole video look like an oil painting\" NOT retexture; that is style_transfer\n\nIf the request is one of those, say so instead of forcing it into this format.\n\n================================================================================\nEXAMPLES\n========\n\nRequest: \"a jaqueta preta do cara para couro\"\n[frames: one man in a matte black fabric jacket, medium shot]\n\nretexture: Turn the black jacket's texture from matte fabric to glossy black leather with soft\ncreases.\n\nRequest: \"deixa a parede com aspecto de concreto velho\"\n[frames: a smooth painted interior wall behind a seated woman]\n\nretexture: Make the wall texture weathered concrete, rough and grainy with visible stains.\n\nRequest: \"o sofá em veludo\"\n[frames: a beige leather sofa in a living room]\n\nretexture: Change the sofa's texture from smooth leather to soft velvety fabric with a fine nap.\n\nRequest: \"textura de tricô no suéter, mantendo a cor\"\n[frames: a woman in a plain dark green sweater]\n\nretexture: Make the sweater have a chunky knitted texture, keeping the dark green colour.\n\nRequest: \"a montanha mais realista\"\n[frames: a distant mountain range, flat-looking rock faces]\n\nretexture: Make the mountains have a realistic, weathered stone texture with rough, defined rock\nfaces.\n\nWRONG — two edits in one prompt, which the LoRA never saw:\nretexture: Make the jacket glossy leather and turn the wall into concrete.\n\nWRONG — verb outside the trained set, and a pointer to an image the model cannot see:\nretexture: Apply the material from the reference image to the jacket.\n\nRIGHT:\nretexture: Turn the jacket's texture to glossy dark leather with soft creases and scuffed\nhighlights.\n\nThe scene details in these examples belong to THESE examples only. Never carry \"jacket\", \"wall\"\nor \"sofa\" into another request — read the actual frames every time.\n\n================================================================================\nFINAL CHECK — RUN THIS BEFORE OUTPUT\n====================================\n\n1. Did you analyze the frames before writing?\n2. Does it start with \"retexture: \" exactly once?\n3. Is there exactly ONE instruction, one object, one surface?\n4. Does the sentence start with Make, Turn, Change, Convert or Retexture — and nothing else?\n5. Is it between 8 and 14 words?\n6. Does it contain the word \"texture\" (93% of training does)?\n7. Is the object named with a definite article and enough detail to be unambiguous in the frames?\n8. Did you give two or three qualifiers rather than a bare material name?\n9. Are the qualifiers drawn from the measured vocabulary above?\n10. If the frames show the current material clearly, did you use the \"from to \"\n form?\n11. If a reference image was supplied, did you convert it into words and avoid pointing at it?\n12. If the colour must stay, did you say so explicitly?\n13. Did you avoid changing shape, silhouette, garment type or object identity?\n14. Did you avoid inventing edits nobody asked for?\n15. Is every scene detail taken from THESE frames, not from an example in this document?\n\nIf any check fails, rewrite before answering. 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"cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "AddLabel", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 0, 2, 48, 16, "white", "black", "FreeMono.ttf", "LoRA On (strength 1.3) (Video Guide Latents) - First Pass (Input and Output 0.590mp - 576x1024)", "up" ], "widgets_values_named": { "text_x": 0, "text_y": 2, "height": 48, "font_size": 16, "font_color": "white", "label_color": "black", "font": "FreeMono.ttf", "text": "LoRA On (strength 1.3) (Video Guide Latents) - First Pass (Input and Output 0.590mp - 576x1024)", "direction": "up" } }, { "id": 331, "type": "AddLabel", "pos": [ 3968.7462670529076, -668.0513161816442 ], "size": [ 725.0576496223111, 277.5842941603719 ], "flags": { "collapsed": true }, "order": 128, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 641 }, { "name": "caption", "shape": 7, "type": "STRING", "link": null }, { 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"showOutputText": false, "horizontal": false, "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } } }, { "id": 387, "type": "AddLabel", "pos": [ 4198.676609909696, -210.0626580747002 ], "size": [ 725.0576496223111, 277.5842941603719 ], "flags": { "collapsed": true }, "order": 129, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 726 }, { "name": "caption", "shape": 7, "type": "STRING", "link": null }, { "name": "text", "type": "STRING", "widget": { "name": "text" }, "link": 727 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 762 ] } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "AddLabel", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 10, 2, 48, 12, "white", "black", "FreeMono.ttf", "GT (original size 422x736)", "up" ], "widgets_values_named": { "text_x": 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null } }, { "id": 332, "type": "ImageConcatMulti", "pos": [ 4249.5021814538195, -522.9668969371132 ], "size": [ 270, 230 ], "flags": { "collapsed": true }, "order": 134, "mode": 0, "inputs": [ { "name": "image_1", "type": "IMAGE,MASK", "link": 759 }, { "name": "image_2", "shape": 7, "type": "IMAGE,MASK", "link": 798 }, { "name": "image_3", "shape": 7, "type": "IMAGE,MASK", "link": 797 } ], "outputs": [ { "name": "output", "type": "IMAGE", "links": [ 869 ] } ], "properties": { "cnr_id": "comfyui-kjnodes", "ver": "60cd6bc1870db94c6eeb05fbe455147a8e91c4e9", "Node name for S&R": "ImageConcatMulti", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ 3, "right", false, null ], "widgets_values_named": { "inputcount": 3, "direction": "right", "match_image_size": false, "Update inputs": null } }, { "id": 381, "type": "GetNode", "pos": [ 4062.7007505888428, -136.2433425003862 ], "size": [ 210, 58 ], "flags": { "collapsed": true }, "order": 48, "mode": 0, "inputs": [], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 720, 726 ] } ], "title": "Get_ref_image", "properties": { "Node name for S&R": "GetNode", "aux_id": "kijai/ComfyUI-KJNodes", "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "ref_image" ], "widgets_values_named": { "Constant": "ref_image" }, "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 223, "type": "PrimitiveStringMultiline", "pos": [ -1769.0556316438028, -638.8450444670682 ], "size": [ 400, 200 ], "flags": {}, "order": 49, "mode": 0, "inputs": [], "outputs": [ { "name": "STRING", "type": "STRING", "links": [ 856 ] } ], "title": "Prompt (You can write in any language)", "properties": { "cnr_id": "comfy-core", "ver": "0.31.0", "Node name for S&R": "PrimitiveStringMultiline", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "Converte esse video para o estilo neon" ], "widgets_values_named": { "value": "Converte esse video para o estilo neon" } }, { "id": 14, "type": "SamplerCustomAdvanced", "pos": [ 2053.143488514906, -556.2935488738312 ], "size": [ 320.9345122916843, 712.1669944485636 ], "flags": { "collapsed": false }, "order": 103, "mode": 0, "inputs": [ { "name": "noise", "type": "NOISE", "link": 318 }, { "name": "guider", "type": "GUIDER", "link": 8 }, { "name": "sampler", "type": "SAMPLER", "link": 9 }, { "name": "sigmas", "type": "SIGMAS", "link": 773 }, { "name": "latent_image", "type": "LATENT", "link": 292 } ], "outputs": [ { "name": "output", "type": "LATENT", "links": [ 326 ] }, { "name": "denoised_output", "type": "LATENT", "links": [] } ], "properties": { "cnr_id": "comfy-core", "ver": "0.30.0", "Node name for S&R": "SamplerCustomAdvanced", "ue_properties": { "widget_ue_connectable": {}, "version": "7.8", "input_ue_unconnectable": {} } }, "color": "#323", "bgcolor": "#535" }, { "id": 452, "type": "Note", "pos": [ -2361.741990565687, -957.1170131859946 ], "size": [ 467, 88 ], "flags": {}, "order": 50, "mode": 0, "inputs": [], "outputs": [], "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "If your video doesn't have audio, it might cause an error, so you'll need to replace it with empty audio. Just connect the node that already exists in set_audio_original." ], "widgets_values_named": { "text": "If your video doesn't have audio, it might cause an error, so you'll need to replace it with empty audio. Just connect the node that already exists in set_audio_original." }, "color": "#432", "bgcolor": "#653" }, { "id": 438, "type": "PreviewAny", "pos": [ -1760.6705383841902, -330.6217074526263 ], "size": [ 508.62053095893157, 278.73942998866335 ], "flags": {}, "order": 74, "mode": 0, "inputs": [ { "name": "source", "type": "*", "link": 855 } ], "outputs": [ { "name": "STRING", "type": "STRING", "links": [] } ], "title": "Prompt Result", "properties": { "cnr_id": "comfy-core", "ver": "0.20.1", "Node name for S&R": "PreviewAny", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [], "widgets_values_named": {} }, { "id": 444, "type": "PrimitiveNode", "pos": [ -1770.5066216189978, -747.6839465089726 ], "size": [ 491.5918420712811, 60 ], "flags": {}, "order": 51, "mode": 0, "inputs": [], "outputs": [ { "name": "BOOLEAN", "type": "BOOLEAN", "widget": { "name": "switch" }, "links": [ 852, 861, 867 ] } ], "title": "Use Manual Prompt ? false = Ref Image, true = Only Prompt", "properties": { "Run widget replace on values": false, "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ false ], "widgets_values_named": { "value": false } }, { "id": 454, "type": "Note", "pos": [ -2626.3883984280924, 518.1560572934125 ], "size": [ 481.8043546888873, 108.59899084761946 ], "flags": {}, "order": 52, "mode": 0, "inputs": [], "outputs": [], "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "You can find some cool images of style, design, and art here, in this old repository of prompts for Midjourney.\n\nhttps://github.com/willwulfken/MidJourney-Styles-and-Keywords-Reference/blob/main/Pages/MJ_V5/Style_Pages/Just_The_Style/Design_Styles.md" ], "widgets_values_named": { "text": "You can find some cool images of style, design, and art here, in this old repository of prompts for Midjourney.\n\nhttps://github.com/willwulfken/MidJourney-Styles-and-Keywords-Reference/blob/main/Pages/MJ_V5/Style_Pages/Just_The_Style/Design_Styles.md" }, "color": "#432", "bgcolor": "#653" }, { "id": 453, "type": "Note", "pos": [ -673.244387804276, -101.23098953183889 ], "size": [ 410.773518947414, 95 ], "flags": {}, "order": 53, "mode": 0, "inputs": [], "outputs": [], "properties": { "ue_properties": { "widget_ue_connectable": {}, "version": "7.5.1", "input_ue_unconnectable": {} } }, "widgets_values": [ "If a LoRa strength of 1.0 is affecting or altering the video motion, try reducing the LoRa strength to 0.70." ], "widgets_values_named": { "text": "If a LoRa strength of 1.0 is affecting or altering the video motion, try reducing the LoRa strength to 0.70." }, "color": "#432", "bgcolor": "#653" }, { "id": 47, "type": "SaveVideo", "pos": [ 3114.251067293077, -725.7043763328619 ], "size": [ 505.72444900778646, 983.0177857636263 ], "flags": {}, "order": 85, "mode": 0, "inputs": [ { "name": "video", "type": "VIDEO", "link": 76 } ], "outputs": [ { "name": "video", "type": "VIDEO", "links": null } ], "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "SaveVideo", "ue_properties": { "widget_ue_connectable": {}, "input_ue_unconnectable": {}, "version": "7.5.1" } }, "widgets_values": [ "head_swap_first_pass_result", "auto", "auto", "auto" ], "widgets_values_named": { "filename_prefix": "head_swap_first_pass_result", "format": "auto", "format.codec": "auto", "codec": "auto" } }, { "id": 42, "type": "LoraLoaderModelOnly", "pos": [ -676.7065653939226, -330.78880061331876 ], "size": [ 417.5504831339992, 116.09126752363369 ], "flags": {}, "order": 133, "mode": 0, "inputs": [ { "name": "model", "type": "MODEL", "link": 572 } ], "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 802 ] } ], "title": "Guide Latent LoRA", "properties": { "cnr_id": "comfy-core", "ver": "0.33.0", "Node name for S&R": "LoraLoaderModelOnly", 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