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| import gradio as gr | |
| import subprocess | |
| import os | |
| import cv2 | |
| import numpy as np | |
| def greet(name, image): | |
| # Specify the path to the run.py script | |
| script_path = "run.py" | |
| # Specify the paths for the image, video, and output | |
| image_path = os.path.abspath("uploaded_image.jpg") | |
| video_path = os.path.abspath("video.mp4") | |
| output_path = os.path.abspath("output.mp4") | |
| # Convert the PIL.Image to a NumPy array | |
| image_np = np.array(image) | |
| # Save the uploaded image using OpenCV | |
| cv2.imwrite(image_path, cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)) | |
| # Construct the command to execute the run.py script with the specified arguments | |
| command = f"python {script_path} --execution-provider cuda -s {image_path} -t {video_path} -o {output_path}" | |
| # Execute the command using subprocess | |
| subprocess.run(command, shell=True) | |
| # Check if the output file exists | |
| if os.path.exists(output_path): | |
| # Return the output video as a gradio Image object | |
| return output_path, "" | |
| else: | |
| return None, "Error: Failed to generate output video." | |
| iface = gr.Interface(fn=greet, inputs=["text", gr.inputs.Image(type="pil")], outputs=["video", "text"]) | |
| iface.launch() | |