from model_utils import detect_face import gradio as gr import numpy as np import os # Function to run the app def set_image(image): return gr.Image.update(value=image[0][0]) def run_model(image: np.ndarray): return gr.Image.update(value=detect_face(image)) def interface() -> None: """ Create and launch the graphical user interface face detection app. """ # Create the blocks for the interface with gr.Blocks() as app: # Add a title and opening HTML element gr.HTML( """

Face Detection App 👤

""" ) with gr.Group(): with gr.Tabs(): with gr.TabItem("Image input 🖼️"): with gr.Row(): with gr.Column(): with gr.Row(): image_in = gr.Image( label="Image input", interactive=True) with gr.Row(): paths = [["examples/" + example] for example in os.listdir("examples")] example_images = gr.Dataset(components=([image_in]), label="Example images", samples=[[path] for path in paths]) with gr.Row(): detect_image_button = gr.Button( value="Detect face 👤") with gr.Column(): with gr.Row(): face_detected_image_out = gr.Image( label="Face detected", interactive=False) example_images.click(fn=set_image, inputs=[ example_images], outputs=[image_in]) detect_image_button.click(fn=run_model, inputs=[ image_in], outputs=face_detected_image_out) with gr.TabItem("Webcam input 📷"): with gr.Row(): with gr.Column(): with gr.Row(): webcam_image_in = gr.Webcam( label="Webcam input") with gr.Row(): gr.Text( label="⚠️ Reminder ", value="Do not forget to click the camera button to freeze and get the webcam image 📷!", interactive=False) with gr.Row(): detect_button = gr.Button( value="Detect face 👤") with gr.Column(): with gr.Row(): face_detected_webcam_out = gr.Image( label="Face detected", interactive=False) detect_button.click(fn=run_model, inputs=[ webcam_image_in], outputs=face_detected_webcam_out) app.launch() app.cache_examples() if __name__ == '__main__': interface() # Run the interface