grapestech/face_analysis

1 2import gradio as gr3from deepface import DeepFace4import cv25import matplotlib.pyplot as plt6import os7 8# Function to compare two specific face images9def compare_two_faces(img1_path, img2_path):10    result = DeepFace.verify(img1_path=img1_path, img2_path=img2_path)11    custom_output = 'Verified' if result['verified'] else 'Not Verified'12    return result, custom_output13 14# Function to verify faces with multiple uploaded files15def verify_faces(img1_path, img2_paths):16    result_text = ""17    for img2_path in img2_paths:18        result = DeepFace.verify(img1_path=img1_path, img2_path=img2_path)19        result_text += f"Comparing {img1_path} with {img2_path}: {'Verified' if result['verified'] else 'Not Verified'}\n"20        if result['verified']:21            img = cv2.imread(img2_path)22            x = result['facial_areas']['img2']['x']23            y = result['facial_areas']['img2']['y']24            w = result['facial_areas']['img2']['w']25            h = result['facial_areas']['img2']['h']26            cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 1)27            img_new = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)28            plt.imshow(img_new)29            plt.axis('off')30            plt.show()31        else:32            result_text += f"No facial areas detected for {img2_path}\n"33    return result_text34 35# Function to analyze a face image36def analyze_face(image_path):37    objs = DeepFace.analyze(img_path=image_path, actions=['age', 'gender', 'race', 'emotion'])38    analysis_result = {39        'Age': objs[0]['age'],40        'Gender': objs[0]['gender'],41        'Race': objs[0]['dominant_race'],42        'Emotion': objs[0]['dominant_emotion']43    }44    return analysis_result45 46# Function to extract faces and count47def extract_faces(image_path):48    face_count = DeepFace.extract_faces(img_path=image_path, detector_backend='mtcnn')49    img = cv2.imread(image_path)50    for face in face_count:51        x = face['facial_area']['x']52        y = face['facial_area']['y']53        w = face['facial_area']['w']54        h = face['facial_area']['h']55        cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 1)56    img_new = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)57    plt.imshow(img_new)58    plt.axis('off')59    plt.show()60    return len(face_count)61 62# Gradio Interface63with gr.Blocks() as demo:64    with gr.Tabs():65        with gr.TabItem("Compare Two Faces"):66            img1_path = gr.Image(type="filepath", label="Face Image 1")67            img2_path = gr.Image(type="filepath", label="Face Image 2")68            compare_btn = gr.Button("Compare")69            compare_output = gr.Textbox(label="Comparison Result")70            compare_custom_output = gr.Textbox(label="Custom Output")71            72            compare_btn.click(compare_two_faces, inputs=[img1_path, img2_path], outputs=[compare_output, compare_custom_output])73 74        with gr.TabItem("Verify Faces with Multiple Files"):75            img1_path = gr.Image(type="filepath", label="Face Image")76            img2_paths = gr.File(label="Upload Multiple Images for Verification", file_count="multiple")77            verify_btn = gr.Button("Verify")78            verify_output = gr.Textbox(label="Verification Results")79            80            verify_btn.click(verify_faces, inputs=[img1_path, img2_paths], outputs=verify_output)81 82        with gr.TabItem("Analyze Face"):83            img_path = gr.Image(type="filepath", label="Face Image")84            analyze_btn = gr.Button("Analyze")85            analysis_output = gr.Textbox(label="Analysis Results")86            87            analyze_btn.click(analyze_face, inputs=img_path, outputs=analysis_output)88 89        with gr.TabItem("Extract and Count Faces"):90            img_path_count = gr.Image(type="filepath", label="Group Face Image")91            extract_btn = gr.Button("Extract Faces")92            count_output = gr.Textbox(label="Number of Faces Detected")93            94            extract_btn.click(extract_faces, inputs=img_path_count, outputs=count_output)95 96demo.launch()97