import gradio as gr import os import cv2 import numpy as np from moviepy.editor import * token = os.environ.get('HF_TOKEN') pix2pix = gr.Blocks.load(name="spaces/fffiloni/instruct-pix2pix-clone", api_key=token) def get_frames(video_in): frames = [] #resize the video clip = mp.VideoFileClip(video_in) clip_resized = clip.resize(height=512) clip_resized.write_videofile("video_resized.mp4") # Opens the Video file with CV2 cap= cv2.VideoCapture("video_resized.mp4") fps = cap.get(cv2.CAP_PROP_FPS) i=0 while(cap.isOpened()): ret, frame = cap.read() if ret == False: break cv2.imwrite('kang'+str(i)+'.jpg',frame) frames.append('kang'+str(i)+'.jpg') i+=1 cap.release() cv2.destroyAllWindows() return frames, fps def create_video(frames, fps): clip = ImageSequenceClip(frames, fps=fps) clip.write_videofile("movie.mp4", fps=fps) return 'movie.mp4' def infer(prompt,video_in, seed_in, trim_value): break_vid = get_frames(video_in) frames_list= break_vid[0] fps = break_vid[1] n_frame = int(trim_value*fps) result_frames = [] for i in frames_list[0:n_frame]: pix2pix_img = pix2pix(prompt,5.5,1.5,i,15,"",512,512,seed_in,fn_index=0) images = [os.path.join(pix2pix_img[0], img) for img in os.listdir(pix2pix_img[0])] result_frames.append(images[0]) print("frame " + i + ": done;") final_vid = create_video(result_frames, fps) return final_vid title = """
Apply Instruct Pix2Pix Diffusion to a video