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asppj /cog-comfyui-img:c493b0bb
Input schema
The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.
| Field | Type | Default value | Description |
|---|---|---|---|
| workflow_json |
string
|
{"3": {"inputs": {"seed": 237514639057514, "steps": 20, "cfg": 2.5, "sampler_name": "euler", "scheduler": "karras", "denoise": 1, "model": ["14", 0], "positive": ["12", 0], "negative": ["12", 1], "latent_image": ["12", 2]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "8": {"inputs": {"samples": ["3", 0], "vae": ["15", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "10": {"inputs": {"filename_prefix": "ComfyUI", "fps": 10, "lossless": false, "quality": 85, "method": "default", "images": ["8", 0]}, "class_type": "SaveAnimatedWEBP", "_meta": {"title": "SaveAnimatedWEBP"}}, "12": {"inputs": {"width": 1024, "height": 576, "video_frames": 25, "motion_bucket_id": 127, "fps": 6, "augmentation_level": 0, "clip_vision": ["15", 1], "init_image": ["20", 0], "vae": ["15", 2]}, "class_type": "SVD_img2vid_Conditioning", "_meta": {"title": "SVD_img2vid_Conditioning"}}, "14": {"inputs": {"min_cfg": 1, "model": ["15", 0]}, "class_type": "VideoLinearCFGGuidance", "_meta": {"title": "VideoLinearCFGGuidance"}}, "15": {"inputs": {"ckpt_name": "svd_xt.safetensors"}, "class_type": "ImageOnlyCheckpointLoader", "_meta": {"title": "Image Only Checkpoint Loader (img2vid model)"}}, "16": {"inputs": {"ckpt_name": "sd_xl_base_1.0.safetensors"}, "class_type": "CheckpointLoaderSimple", "_meta": {"title": "Load Checkpoint"}}, "17": {"inputs": {"seed": 144698910769133, "steps": 15, "cfg": 8, "sampler_name": "uni_pc_bh2", "scheduler": "normal", "denoise": 1, "model": ["16", 0], "positive": ["18", 0], "negative": ["19", 0], "latent_image": ["22", 0]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "18": {"inputs": {"text": "A dramatic scene of a rocket launch at dawn with logo ihandy name, with a towering rocket on the launch pad, surrounded by a cloud of smoke and flames. The sky is painted in shades of orange and purple as the sun rises, casting a warm glow on the scene. Ground crew in the foreground, wearing safety gear, are monitoring the launch. The rocket is detailed with futuristic designs and logos, and the launch pad is equipped with various technical equipment. The atmosphere is filled with excitement and anticipation.", "clip": ["16", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "19": {"inputs": {"text": "watermark", "clip": ["16", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "20": {"inputs": {"samples": ["17", 0], "vae": ["16", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "21": {"inputs": {"images": ["20", 0]}, "class_type": "PreviewImage", "_meta": {"title": "Preview Image"}}, "22": {"inputs": {"width": 1024, "height": 576, "batch_size": 1}, "class_type": "EmptyLatentImage", "_meta": {"title": "Empty Latent Image"}}}
|
Your ComfyUI workflow as JSON. You must use the API version of your workflow. Get it from ComfyUI using ‘Save (API format)’. Instructions here: https://github.com/fofr/cog-comfyui
|
| input_file |
string
|
Input image, tar or zip file. Read guidance on workflows and input files here: https://github.com/fofr/cog-comfyui. Alternatively, you can replace inputs with URLs in your JSON workflow and the model will download them.
|
|
| return_temp_files |
boolean
|
False
|
Return any temporary files, such as preprocessed controlnet images. Useful for debugging.
|
| output_format |
string
(enum)
|
webp
Options: webp, jpg, png |
Format of the output images
|
| output_quality |
integer
|
95
Max: 100 |
Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.
|
| randomise_seeds |
boolean
|
True
|
Automatically randomise seeds (seed, noise_seed, rand_seed)
|
| force_reset_cache |
boolean
|
False
|
Force reset the ComfyUI cache before running the workflow. Useful for debugging.
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}