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fix import order and deprecate for CVX 2B models

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LittleNyima 2025-02-26 15:54:58 +08:00
parent d6bb910697
commit 2c33c0982b
1 changed files with 16 additions and 2 deletions
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18
inference/ddim_inversion.py
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@ -3,8 +3,17 @@ This script performs DDIM inversion for video frames using a pre-trained model a
a video reconstruction based on a provided prompt. It utilizes the CogVideoX pipeline to a video reconstruction based on a provided prompt. It utilizes the CogVideoX pipeline to
process video frames, apply the DDIM inverse scheduler, and produce an output video. process video frames, apply the DDIM inverse scheduler, and produce an output video.
**Please notice that this script is based on the CogVideoX 5B model, and would not generate
a good result for 2B variants.**
Usage: Usage:
python script.py --model-path /path/to/model --prompt "a prompt" --video-path /path/to/video.mp4 --output-path /path/to/output python ddim_inversion.py
--model-path /path/to/model
--prompt "a prompt"
--video-path /path/to/video.mp4
--output-path /path/to/output
For more details about the cli arguments, please run `python ddim_inversion.py --help`.
Author: Author:
LittleNyima <littlenyima[at]163[dot]com> LittleNyima <littlenyima[at]163[dot]com>
@ -15,7 +24,6 @@ import math
import os import os
from typing import Any, Dict, List, Optional, Tuple, TypedDict, Union, cast from typing import Any, Dict, List, Optional, Tuple, TypedDict, Union, cast
import decord
import torch import torch
import torch.nn.functional as F import torch.nn.functional as F
import torchvision.transforms as T import torchvision.transforms as T
@ -27,6 +35,10 @@ from diffusers.pipelines.cogvideo.pipeline_cogvideox import CogVideoXPipeline, r
from diffusers.schedulers import CogVideoXDDIMScheduler, DDIMInverseScheduler from diffusers.schedulers import CogVideoXDDIMScheduler, DDIMInverseScheduler
from diffusers.utils import export_to_video from diffusers.utils import export_to_video
# Must import after torch because this can sometimes lead to a nasty segmentation fault, or stack smashing error.
# Very few bug reports but it happens. Look in decord Github issues for more relevant information.
import decord # isort: skip
class DDIMInversionArguments(TypedDict): class DDIMInversionArguments(TypedDict):
model_path: str model_path: str
@ -399,6 +411,8 @@ def ddim_inversion(
device: torch.device, device: torch.device,
): ):
pipeline: CogVideoXPipeline = CogVideoXPipeline.from_pretrained(model_path, torch_dtype=dtype).to(device=device) pipeline: CogVideoXPipeline = CogVideoXPipeline.from_pretrained(model_path, torch_dtype=dtype).to(device=device)
if not pipeline.transformer.config.use_rotary_positional_embeddings:
raise NotImplementedError("This script supports CogVideoX 5B model only.")
video_frames = get_video_frames( video_frames = get_video_frames(
video_path=video_path, video_path=video_path,
width=width, width=width,