app.py

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()