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