File size: 1,801 Bytes
1e9483f 84372b1 1e9483f 84372b1 1e9483f 84372b1 1e9483f 84372b1 1e9483f 84372b1 1e9483f 84372b1 1e9483f 84372b1 1e9483f 6840feb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
from flask import Flask, request, jsonify
from gradio_client import Client, handle_file
import os
app = Flask(__name__)
# Initialize Gradio Client
client = Client("jallenjia/Change-Clothes-AI")
@app.route('/tryon', methods=['POST'])
def tryon():
try:
# Extract parameters from JSON request
data = request.get_json()
# Validate required parameters
if not data or not all(key in data for key in ['background', 'garm_img', 'garment_des']):
return jsonify({"error": "Missing required parameters: background, garm_img, garment_des"}), 400
# Prepare input dictionary
input_dict = {
"background": handle_file(data['background']) if data.get('background') else None,
"layers": data.get('layers', []),
"composite": handle_file(data.get('composite')) if data.get('composite') else None,
"id": data.get('id')
}
# Call Gradio API
result = client.predict(
dict=input_dict,
garm_img=handle_file(data['garm_img']),
garment_des=data['garment_des'],
is_checked=data.get('is_checked', True),
is_checked_crop=data.get('is_checked_crop', False),
denoise_steps=data.get('denoise_steps', 30),
seed=data.get('seed', -1),
category=data.get('category', 'upper_body'),
api_name="/tryon"
)
# Format response
response = {
"output_image": result[0], # Filepath of output image
"masked_image": result[1] # Filepath of masked image
}
return jsonify(response), 200
except Exception as e:
return jsonify({"error": str(e)}), 500
if __name__ == '__main__':
app.run(host='0.0.0.0', port=7860) |