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upscale", "properties": { "Node name for S&R": "" } }, { "id": 178, "type": "Note", "pos": [ 834, -903 ], "size": { "0": 243.64602661132812, "1": 127.71123504638672 }, "flags": {}, "order": 1, "mode": 0, "properties": { "text": "" }, "widgets_values": [ "Use Euler ancestral or DPM samplers for smoother and more stable animations.\n\nFind a comparison of samplers here:\nhttps://www.reddit.com/r/StableDiffusion/comments/15qmjxy/animatediff_sampler_stats/" ], "color": "#222", "bgcolor": "#000" }, { "id": 106, "type": "PrimitiveNode", "pos": [ 598, -874 ], "size": { "0": 210, "1": 82 }, "flags": {}, "order": 2, "mode": 0, "outputs": [ { "name": "INT", "type": "INT", "links": [ 213 ], "slot_index": 0, "widget": { "name": "seed" } } ], "properties": { "Run widget replace on values": false }, "widgets_values": [ 981423447252632, "randomize" ] }, { "id": 170, "type": "ControlNetLoaderAdvanced", "pos": [ 640, -1640 ], "size": { "0": 381.58392333984375, "1": 58 }, "flags": {}, "order": 3, 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], "properties": { "Node name for S&R": "ControlNetApplyAdvanced" }, "widgets_values": [ 0.5, 0, 1 ], "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 177, "type": "PreviewImage", "pos": [ 1820, -1640 ], "size": { "0": 321.4112548828125, "1": 246 }, "flags": {}, "order": 28, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 349 } ], "properties": { "Node name for S&R": "PreviewImage" } }, { "id": 176, "type": "ControlNetApplyAdvanced", "pos": [ 1346, -1244 ], "size": { "0": 427.7201232910156, "1": 239.03790283203125 }, "flags": {}, "order": 31, "mode": 0, "inputs": [ { "name": "positive", "type": "CONDITIONING", "link": 342 }, { "name": "negative", "type": "CONDITIONING", "link": 343 }, { "name": "control_net", "type": "CONTROL_NET", "link": 345 }, { "name": "image", "type": "IMAGE", "link": 344 } ], "outputs": [ { "name": "positive", "type": "CONDITIONING", "links": [ 347 ], "shape": 3, "slot_index": 0 }, { "name": "negative", "type": "CONDITIONING", "links": [ 348 ], "shape": 3, "slot_index": 1 } ], "properties": { "Node name for S&R": "ControlNetApplyAdvanced" }, "widgets_values": [ 0.7000000000000001, 0, 1 ], "color": "#2a363b", "bgcolor": "#3f5159" }, { "id": 160, "type": "Note", "pos": [ 1813, -1263 ], "size": { "0": 416.1223449707031, "1": 266.65899658203125 }, "flags": {}, "order": 4, "mode": 0, "properties": { "text": "" }, "widgets_values": [ "You must install 'ComfyUI's ControlNet Auxiliary Preprocessors' custom nodes manually or via the Manager (->Install Missing Custom Nodes) \nmore info here: https://github.com/Fannovel16/comfyui_controlnet_aux\n\nLineart and HED Lines work best for faces/expressions and if you want to keep details of the input sequence.\n\nOpenPose works best for full body movement (i.e. dancing, walking etc)\n\nAs shown here, you can mix multiple ControlNets for the cost of longer render time and higher usage of VRAM.\n\nControlNet examples:\nhttps://comfyanonymous.github.io/ComfyUI_examples/controlnet/" ], 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Keep your prompts below 75 tokens.\n\nThe negative prompt should not be longer than the positive prompt!" ], "color": "#222", "bgcolor": "#000" }, { "id": 50, "type": "PreviewImage", "pos": [ -596.9493750961091, -1677.8411773868754 ], "size": { "0": 350.0137634277344, "1": 326.18408203125 }, "flags": {}, "order": 23, "mode": 0, "inputs": [ { "name": "images", "type": "IMAGE", "link": 86 } ], "properties": { "Node name for S&R": "PreviewImage" } }, { "id": 96, "type": "PrimitiveNode", "pos": [ -670, -970 ], "size": { "0": 210, "1": 82 }, "flags": {}, "order": 7, "mode": 0, "outputs": [ { "name": "INT", "type": "INT", "links": [ 209 ], "slot_index": 0, "widget": { "name": "width" } } ], "title": "Width", "properties": { "Run widget replace on values": false }, "widgets_values": [ 512, "fixed" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 97, "type": "PrimitiveNode", "pos": [ -449, -969 ], "size": { "0": 210, "1": 82 }, "flags": {}, "order": 8, "mode": 0, "outputs": [ { "name": "INT", "type": "INT", "links": [ 210 ], "slot_index": 0, "widget": { "name": "height" } } ], "title": "Height", "properties": { "Run widget replace on values": false }, "widgets_values": [ 512, "fixed" ], "color": "#332922", "bgcolor": "#593930" }, { "id": 56, "type": "VAEEncode", "pos": [ -491, -611 ], "size": { "0": 241.0370635986328, "1": 81.81757354736328 }, "flags": {}, "order": 24, "mode": 0, "inputs": [ { "name": "pixels", "type": "IMAGE", "link": 87 }, { "name": "vae", "type": "VAE", "link": 88 } ], "outputs": [ { "name": "LATENT", "type": "LATENT", "links": [ 208 ], "shape": 3, "slot_index": 0 } ], "properties": { "Node name for S&R": "VAEEncode" } }, { "id": 1, "type": "CheckpointLoaderSimpleWithNoiseSelect", "pos": [ -1052, -842 ], "size": { "0": 802.761474609375, "1": 182.4549102783203 }, "flags": {}, "order": 9, "mode": 0, "outputs": [ { "name": "MODEL", "type": "MODEL", "links": [ 303 ], "shape": 3, "slot_index": 0 }, { "name": "CLIP", "type": "CLIP", "links": [ 304 ], "shape": 3, "slot_index": 1 }, { "name": "VAE", "type": "VAE", "links": null, "shape": 3, "slot_index": 2 } ], "properties": { "Node name for S&R": "CheckpointLoaderSimpleWithNoiseSelect" }, "widgets_values": [ "Illu\\revAnimated_v11.safetensors", "sqrt_linear (AnimateDiff)", false, 1 ], "color": "#432", "bgcolor": "#653" }, { "id": 53, "type": "ImageScale", "pos": [ -595.4545454545456, -1170.9090909090908 ], "size": { "0": 351.3953857421875, "1": 161.42391967773438 }, "flags": {}, "order": 19, "mode": 0, "inputs": [ { "name": "image", "type": "IMAGE", "link": 318 }, { "name": "width", "type": "INT", "link": 209, "widget": { "name": "width" }, "slot_index": 1 }, { "name": "height", "type": "INT", "link": 210, "widget": { "name": "height" }, "slot_index": 2 } ], "outputs": [ { "name": "IMAGE", "type": "IMAGE", "links": [ 86, 87, 351 ], "shape": 3, "slot_index": 0 } ], "properties": { "Node name for S&R": "ImageScale" }, "widgets_values": [ "nearest-exact", 512, 512, "center" ] }, { "id": 157, "type": "Note", "pos": [ 300, -559 ], "size": { "0": 250.90220642089844, "1": 351.9985046386719 }, "flags": {}, "order": 10, "mode": 0, "properties": { "text": "" }, "widgets_values": [ "You can add any LoRA to the stack. There are also 'Motion LoRAs' for camera control, but they don't make much sense here, as we want the result to be somewhat close to the source.\n\nBut sometimes I got interesting effects from using them so I suggest you just try by yourself. \n\nYou can download the motion LoRAs here:\n\nhttps://huggingface.co/conrevo/AnimateDiff-A1111/tree/main/lora" ], "color": "#222", "bgcolor": "#000" }, { "id": 153, "type": "Note", "pos": [ -1072, -1032 ], "size": { "0": 389.503662109375, "1": 147.4991455078125 }, "flags": {}, "order": 11, "mode": 0, "properties": { "text": "" }, "widgets_values": [ "You need to prepare a folder that contains an image sequence and load it here.\n\nUse this tool to create the sequence from a video or gif file https://www.shutterencoder.com\n\nThe SD1.5 motion modules are trained with 16 frames, so it’ll give the best results when the number of frames is 16 - but it should also work for longer animations." ], "color": "#222", "bgcolor": "#000" }, { "id": 181, "type": "Note", "pos": [ -597, -1307 ], "size": { "0": 348.4784240722656, "1": 92.85890197753906 }, "flags": {}, "order": 12, "mode": 0, "properties": { "text": "" }, "widgets_values": [ "The images are scaled (and optionally cropped) to the correct size of 512x512px here. \n\nAnimateDiff is trained on 512x512 images so it works best with 512x512 output." ], "color": "#222", "bgcolor": "#000" }, { "id": 159, "type": "Note", "pos": [ -195, -1476 ], "size": { "0": 373.4175109863281, "1": 105.35885620117188 }, "flags": {}, "order": 13, "mode": 0, "properties": { "text": "" }, "widgets_values": [ "Download the models here\nhttps://huggingface.co/guoyww/animatediff/tree/main\n\nand drop them in\n[ComfyUI folder]/custom_nodes/comfyui-animatediff/models/" ], "color": "#222", "bgcolor": "#000" }, { "id": 103, "type": "VHS_LoadImages", "pos": [ -1059.9493750961087, -1683.8411773868754 ], "size": [ 443.2850646972656, 611.2850646972656 ], "flags": {}, "order": 14, "mode": 0, "outputs": [ { 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