import gradio as gr import os import subprocess import requests import time UPLOAD_FOLDER = 'uploads_gradio' OUTPUT_FOLDER = 'outputs_gradio' os.makedirs(UPLOAD_FOLDER, exist_ok=True) os.makedirs(OUTPUT_FOLDER, exist_ok=True) # Start TorchServe in the background # Adjust arguments to match your configuration ts_process = subprocess.Popen([ "torchserve", "--start", "--model-store", "/home/torchserve/model-store", "--ts-config", "/home/torchserve/config.properties", "--no-config-snapshots" ]) # Wait for TorchServe to become healthy while True: try: r = requests.get("http://127.0.0.1:8080/ping") if r.status_code == 200: break except: pass time.sleep(1) def animate_image(file_path): # Here you can call TorchServe endpoints if needed, for example: # response = requests.post("http://127.0.0.1:8080/predictions/drawn_humanoid_detector", files={"data": open(file_path, "rb")}) # Process the response and then run your animation logic. # ... # Or if you run your original script, just as before: if not file_path: raise ValueError("No file uploaded.") input_path = file_path filename = os.path.basename(input_path) base, ext = os.path.splitext(filename) allowed_extensions = ['.png', '.jpg', '.jpeg', '.bmp'] if ext.lower() not in allowed_extensions: raise ValueError("Unsupported file type.") char_anno_dir = os.path.join(OUTPUT_FOLDER, f"{base}_out") os.makedirs(char_anno_dir, exist_ok=True) subprocess.run(['python', 'examples/image_to_animation.py', input_path, char_anno_dir], check=True) gif_path = os.path.join(char_anno_dir, "video.gif") if os.path.exists(gif_path): return gif_path else: raise FileNotFoundError("Animation failed to generate.") iface = gr.Interface( fn=animate_image, inputs=gr.Image(label="Upload Drawing", type="filepath", sources=["upload", "webcam"]), outputs=gr.Image(label="Animated GIF"), title="Animated Drawings", description="Upload or take a photo of a drawing, get an animated GIF." ) if __name__ == "__main__": # Gradio on port 7860 iface.launch(server_name="0.0.0.0", server_port=7860)