Update app.py

app.py

@@ -1,45 +1,4 @@
-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)
+iface = gr.load("spaces/radames/Enhance-This-HiDiffusion-SDXL)