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tiger-ai-lab /anyv2v:3c7b5bc5

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
video
string
Input video
edited_first_frame
string
Provide the edited first frame of the input video. This is optional, leave it blank and provide the prompt below to use the default pipeline that edits the frist frame with instructpix2pix
instruct_pix2pix_prompt
string
turn man into robot
The first step invovles using timbrooks/instruct-pix2pix to edit the first frame. Specify the prompt for editing the first frame. This will be ignored if edited_first_frame above is provided.
editing_prompt
string
a man doing exercises for the body and mind
Describe the input video
editing_negative_prompt
string
Distorted, discontinuous, Ugly, blurry, low resolution, motionless, static, disfigured, disconnected limbs, Ugly faces, incomplete arms
Things not to see int the edited video
num_inference_steps
integer
50

Min: 1

Max: 500

Number of denoising steps
guidance_scale
number
9

Min: 1

Max: 20

Scale for classifier-free guidance
pnp_f_t
number
1

Max: 1

Specifies the proportion of time steps in the DDIM sampling process where the convolutional injection is applied. A higher value improves motion consistency. 1.0 indicates injection at every time step
pnp_spatial_attn_t
number
1

Max: 1

Specifies the proportion of time steps in the DDIM sampling process where the spatial attention injection is applied. A higher value improves motion consistency. 1.0 indicates injection at every time step
pnp_temp_attn_t
number
1

Max: 1

Specifies the proportion of time steps in the DDIM sampling process where the temporal attention injection is applied. A higher value improves motion consistency. 1.0 indicates injection at every time step
ddim_init_latents_t_idx
integer
0
This parameter determines the time step index at which to begin sampling from the initial DDIM inversed latents, with a range of [0, num_inference_steps-1]. In the context of a DDIM sampling process where the sampling step is 50, the scheduler progresses through the time steps in the sequence [981, 961, 941, ..., 1]. Therefore, setting ddim_init_latents_t_idx to 0 initiates the sampling from t=981, whereas setting it to 1 starts the process at t=961. A higher index enhances motion consistency with the source video but may lead to flickering and cause the edited video to diverge from the edited first frame.
ddim_inversion_steps
integer
100
Number of ddim inversion steps
seed
integer
Random seed. Leave blank to randomize the seed

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'format': 'uri', 'title': 'Output', 'type': 'string'}