Our AnyV2V(ConsistI2V) is a standalone version.
conda env create -f environment.yaml
conda activate consisti2v
Note: due to the lower training resolution of ConsistI2V (256x256), it might perform better on 256x256 inputs. We provide configurations for running on both 256x256 and 512x512.
Usage Example:
python run_ddim_inversion.py --config configs/pipeline_256/ddim_inversion_256.yaml video_path=/path/to/your_video.mp4 video_name=your_video
Saved latent goes to ./ddim_version
(can be configurated in ./configs/pipeline_256(512)/ddim_inversion_256(512).yaml
).
Your need to prepare your edited image frame first. We provided an image editing script in the root folder of AnyV2V.
Usage Example:
python run_pnp_edit.py --config configs/pipeline_256/pnp_edit.yaml \
video_path=/path/to/your_video.mp4 \
video_name=your_video \
edited_first_frame_path=/path/to/edited_first_frame.png \
editing_prompt="<editing_prompt>" \
ddim_latents_path=/path/to/ddim_latents
Saved video goes to ./anyv2v_results
(can be configurated in ./configs/pipeline_256(512)/pnp_edit.yaml
).