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| import os | |
| from flask import Flask, request | |
| import requests | |
| from gradio_client import Client | |
| import base64 | |
| base_gradio_url = os.getenv('URL_GRADIO', 'http://localhost:7860') | |
| client = None | |
| app = Flask(__name__, static_url_path='/static') | |
| def index(): | |
| return app.send_static_file('index.html') | |
| def save_base64_image(base64Image): | |
| image_data = base64.b64decode(base64Image) | |
| path = "input_image.jpg" | |
| with open(path, 'wb') as f: | |
| f.write(image_data) | |
| return path | |
| def encode_image_to_base64(filepath): | |
| with open(filepath, "rb") as image_file: | |
| encoded_image = base64.b64encode(image_file.read()).decode("utf-8") | |
| return encoded_image | |
| def predict(): | |
| data = request.get_json() | |
| base64Image = data['data'][0] | |
| prompt = data['data'][1] | |
| steps = data['data'][2] | |
| seed = data['data'][3] | |
| global client | |
| if not client: | |
| client = Client(base_gradio_url) | |
| b64meta, b64_data = base64Image.split(',') | |
| image_path = save_base64_image(b64_data) | |
| result = client.predict( | |
| image_path, prompt, steps, seed, fn_index=0 | |
| ) | |
| return b64meta + ',' + encode_image_to_base64(result) | |
| if __name__ == '__main__': | |
| app.run(host='0.0.0.0', port=int( | |
| os.environ.get('PORT', 8000)), debug=True) | |