e", repo_id=repo_id, filename=filename) Read video containing extracted pose images   Copied from PIL import Image
import imageio

reader = imageio.get_reader(video_path, "ffmpeg")
frame_count = 8
pose_images = [Image.fromarray(reader.get_data(i)) for i in range(frame_count)] To extract pose from actual video, read ControlNet documentation. Run StableDiffusionControlNetPipeline with our custom attention processor   Copied import torch
from diff