upgrade.py

from transformers import pipeline
import cv2
import numpy as np
import os

# Initialize a text-to-image generation pipeline (for example purposes)
generator = pipeline('text-to-image', model='CompVis/stable-diffusion-v1-4')

# List of prompts for each frame
prompts = [
    "A spaceship in space, vibrant colors",
    "A spaceship flying past planets",
    "A spaceship approaching a distant galaxy",
    "A spaceship landing on an alien planet"
]

# Folder to save frames
os.makedirs('frames', exist_ok=True)

# Generate images for each prompt
for idx, prompt in enumerate(prompts):
    image = generator(prompt)[0]['image']
    image.save(f'frames/frame_{idx:03d}.png')

# Combine frames into a video
frame_files = [f'frames/frame_{i:03d}.png' for i in range(len(prompts))]
frame_width, frame_height = cv2.imread(frame_files[0]).shape[1], cv2.imread(frame_files[0]).shape[0]

video_writer = cv2.VideoWriter('space_video.mp4', cv2.VideoWriter_fourcc(*'mp4v'), 1, (frame_width, frame_height))

for file in frame_files:
    img = cv2.imread(file)
    video_writer.write(img)

video_writer.release()

print("Video created: space_video.mp4")