add gr load

app.py

@@ -4,79 +4,7 @@ import gradio as gr
 from numpy.linalg import norm
 from gradio_client import Client
 
-os.environ['CUDA_LAUNCH_BLOCKING'] = '0'
-G = ['Female', 'Male']
-
 token = os.environ['token']
-client = Client("https://vtechai-face-demo.hf.space/", token)
-
-def analyze(im, conf=0.65, area="Asia", f_age=False, f_gender=False, f_emotion=False):
-    im_path, jj = client.predict(im, conf, area, f_age, f_gender, f_emotion, fn_index=1)
-    with open(jj) as f:
-        jss = json.load(f)
-    return im_path, jss
-    
-def face_search(im1,im2, threshold):
-    im3, im4, te = client.predict(im1, im2, threshold, fn_index=3)
-    return im3, im4, te
-
-
-with gr.Blocks() as face_compare:
-    with gr.Row():
-        im1 = gr.Image(value="example/ronaldo.jpg", label='Register', type='filepath',  height=300) #.style(full_width=True, height=300)
-        im2 = gr.Image(value="example/face2.jpg", label='Image for Search', type='filepath',  height=300) #.style(full_width=True, height=300)
-    
-    with gr.Row():
-        im3 = gr.Image(label='Output', height=300) #.style(height=300, full_width=True, full_height=True)
-        im4 = gr.Image(label='Output', height=300) #.style(height=300, full_width=True, full_height=True)
-    
-    sl = gr.Slider(0.3, 1, step=0.05, value=0.5, label='Face Matching Threshold')
-    text = gr.Text(label="Output", interactive=False)
-    with gr.Row():
-        btn = gr.Button(value="Run")
-        btn_clean = gr.ClearButton([im1, im2, im3, im4])
-    btn.click(fn=face_search, inputs=[im1, im2, sl], outputs=[im3, im4, text])
-    # btn2 = gr.Button(value="Check", link="https://manhduy160396.wixsite.com/vtech")
-
-    # example
-    gr.Examples(
-        examples=[[
-            os.path.join(os.path.dirname(__file__), "example/ronaldo.jpg"),
-            os.path.join(os.path.dirname(__file__), "example/face2.jpg")
-        ]],
-        inputs=[im1, im2]
-
-    )
-
-with gr.Blocks() as face_analyze:
-    with gr.Row():
-        im1 = gr.Image(shape=(300, 300), type='filepath', height=300, container=True)
-        im2 = gr.Image(shape=(300, 300), height=300, container=True)
-
-    with gr.Row():
-        with gr.Column():
-            area = gr.Radio(["Asia", "Europe/America"], label="Area?", value="Asia")
-            cb_age = gr.Checkbox(label="Age", value=True)
-            cb_gender = gr.Checkbox(label="Gender", value=True)
-            cb_emotion = gr.Checkbox(label="Emotion", value=True)
-            sl = gr.Slider(0, 1, step=0.05, value=0.65, label='Confidence Threshold')
-        
-        with gr.Column():
-            js = gr.JSON(label="json")
-    
-    with gr.Row():
-        btn = gr.Button(value="Run")
-        btn_clean = gr.ClearButton([im1, im2])
-
-    btn.click(fn=analyze, inputs=[im1, sl, area, cb_age, cb_gender, cb_emotion], outputs=[im2, js])
-    # btn2 = gr.Button(value="Check", link="https://manhduy160396.wixsite.com/vtech")
-
-
-with gr.Blocks() as demo:
-    gr.Markdown('<h1 style="text-align: center;">V-FaceSDK</h1>')
-    gr.Markdown("*Chọn chức năng bạn muốn trải nghiệm")
-    gr.TabbedInterface([face_analyze, face_compare], ["Face Analyze", "Face Compare"])
-
 
 if __name__ == "__main__":
     demo = gr.load("VTechAI/Face_demo", src="spaces", hf_token=token)