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fofr /lcm-video2video:40dc81b6
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 |
---|---|---|---|
prompt |
string
|
Self-portrait oil painting, a beautiful cyborg with golden hair, 8k
|
Prompt for video2video
|
video |
string
|
Video to split into frames
|
|
fps |
integer
|
8
Min: 1 |
Number of images per second of video, when not exporting all frames
|
extract_all_frames |
boolean
|
False
|
Get every frame of the video. Ignores fps. Slow for large videos.
|
max_width |
integer
|
512
Min: 1 |
Maximum width of the video. Maintains aspect ratio.
|
prompt_strength |
number
|
0.2
Max: 1 |
1.0 corresponds to full destruction of information in video frame
|
num_inference_steps |
integer
|
4
Min: 1 Max: 50 |
Number of denoising steps per frame. Recommend 1 to 8 steps.
|
controlnet |
string
(enum)
|
none
Options: none, canny, illusion |
Controlnet to use
|
controlnet_conditioning_scale |
number
|
2
Min: 0.1 Max: 4 |
Controlnet conditioning scale
|
control_guidance_start |
number
|
0
Max: 1 |
Controlnet start
|
control_guidance_end |
number
|
1
Max: 1 |
Controlnet end
|
canny_low_threshold |
number
|
100
Min: 1 Max: 255 |
Canny low threshold
|
canny_high_threshold |
number
|
200
Min: 1 Max: 255 |
Canny high threshold
|
guidance_scale |
number
|
8
Min: 1 Max: 20 |
Scale for classifier-free guidance
|
seed |
integer
|
Random seed. Leave blank to randomize the seed
|
|
return_frames |
boolean
|
False
|
Return a tar file with all the frames alongside the video
|
Output schema
The shape of the response you’ll get when you run this model with an API.
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}