app.py

from flask import Flask, request, jsonify
from gradio_client import Client
import gradio as gr

app = Flask(__name__)

client = Client("radames/Enhance-This-HiDiffusion-SDXL")

@app.route('/predict', methods=['POST'])
def my_interface():
    data = request.get_json()

    input_image = data['input_image']
    prompt = data.get('prompt', "This is a beautiful scenery")
    negative_prompt = data.get('negative_prompt', "blurry, ugly, duplicate, poorly drawn, deformed, mosaic")
    seed = data.get('seed', 1415926535897932)
    guidance_scale = data.get('guidance_scale', 8.5)
    scale = data.get('scale', 2)
    controlnet_conditioning_scale = data.get('controlnet_conditioning_scale', 0.5)
    strength = data.get('strength', 1.0)
    controlnet_start = data.get('controlnet_start', 0.0)
    controlnet_end = data.get('controlnet_end', 1.0)
    guassian_sigma = data.get('guassian_sigma', 2.0)
    intensity_threshold = data.get('intensity_threshold', 3)

    result = client.predict(
        input_image=input_image, 
        prompt=prompt, 
        negative_prompt=negative_prompt, 
        seed=seed, 
        guidance_scale=guidance_scale, 
        scale=scale, 
        controlnet_conditioning_scale=controlnet_conditioning_scale, 
        strength=strength, 
        controlnet_start=controlnet_start, 
        controlnet_end=controlnet_end, 
        guassian_sigma=guassian_sigma, 
        intensity_threshold=intensity_threshold, 
        api_name="/predict"
    )

    return jsonify(result[0][0])

if __name__ == '__main__':
    app.run(debug=True)