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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)