Create app.py

app.py

@@ -0,0 +1,41 @@
+import cv2
+import gradio as gr
+from deepface import DeepFace
+
+def analyze_fn(img_path):
+    # Load the image only once for better performance
+    img = cv2.imread(img_path)
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    
+    objs = DeepFace.analyze(img_path=img_path, actions=['age', 'gender', 'race', 'emotion'])
+    obj = objs[0]
+    
+    age = obj["age"]
+    gender = obj["dominant_gender"]
+    race = obj["dominant_race"]
+    emotion = obj["dominant_emotion"]
+    
+    region = obj["region"]
+    x, y, w, h = region["x"], region["y"], region["w"], region["h"]
+    
+    # Draw the rectangle on the image
+    cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)
+    
+    return [img, age, gender, race, emotion]
+
+with gr.Blocks() as demo:
+    title = """<p><h1 align="center" style="font-size: 36px;">Facial Attribute Analyzer</h1></p>"""
+    gr.HTML(title)
+    with gr.Row():
+        with gr.Column():
+            image = gr.Image(label="Upload Image", type="filepath")
+            analyze = gr.Button("Analyze")
+        with gr.Column():
+            age_box = gr.Textbox(label="Age")
+            gender_box = gr.Textbox(label="Gender")
+            race_box = gr.Textbox(label="Race")
+            emotion_box = gr.Textbox(label="Emotion")
+    
+            analyze.click(fn=analyze_fn, inputs=image, outputs=[image, age_box, gender_box, race_box, emotion_box], api_name="greet")
+
+demo.launch()