| import gradio as gr | |
| import numpy as np | |
| import time | |
| def sepia(input_img, num_copies): | |
| sepia_filter = np.array([ | |
| [0.393, 0.769, 0.189], | |
| [0.349, 0.686, 0.168], | |
| [0.272, 0.534, 0.131] | |
| ]) | |
| # Normalize input image to 0-1 range | |
| input_img = input_img / 255.0 | |
| sepia_img = np.dot(input_img[...,:3], sepia_filter.T) | |
| sepia_img = np.clip(sepia_img, 0, 1) | |
| # Iterate to yield multiple sepia images | |
| for _ in range(num_copies): | |
| # Simulating a delay for demonstration, you might not need this | |
| time.sleep(1) | |
| yield (sepia_img * 255).astype(np.uint8) | |
| with gr.Blocks() as demo: | |
| gr.Image() | |
| demo.launch() | |
| if __name__ == "__main__": | |
| demo.launch() | |