Update model/face_verification_script.py

model/face_verification_script.py

@@ -1,37 +1,36 @@
 from deepface import DeepFace
-from flask import Flask, request, jsonify
+from PIL import Image
+import requests
+import tempfile
+import os
+
+def verify_faces(img1_url, img2_url):
+    # Download the images from the URLs
+    response1 = requests.get(img1_url)
+    response2 = requests.get(img2_url)
+
+    # Check if the requests were successful
+    if response1.status_code == 200 and response2.status_code == 200:
+        # Create temporary files to store the downloaded images
+        with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as img1_tempfile:
+            img1_tempfile.write(response1.content)
+            img1_path = img1_tempfile.name
+
+        with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as img2_tempfile:
+            img2_tempfile.write(response2.content)
+            img2_path = img2_tempfile.name
+
+        # Perform facial recognition with deep_face
+        result = DeepFace.verify(img1_path=img1_path, img2_path=img2_path, model_name='VGG-Face')
+    
+        # Delete the temporary files when done
+        os.remove(img1_path)
+        os.remove(img2_path)
+        
+        if result["verified"]:
+            return "RESULT: Faces Matched!"
+        else:
+            return "RESULT: Faces Don't Match"
 
-app = Flask(__name__)
-
-def compare_images(image1_path, image2_path):
-    result = DeepFace.verify(image1_path, image2_path, model_name='VGG-Face', distance_metric='euclidean_l2')
-    return result['distance']
-
-@app.route('/predict', methods=['POST'])
-def predict():
-    if 'file1' not in request.files or 'file2' not in request.files:
-        return jsonify({'error': 'Please provide two image files.'}), 400
-
-    file1 = request.files['file1']
-    file2 = request.files['file2']
-
-    # Save uploaded files
-    file1_path = 'temp/file1.jpg'
-    file2_path = 'temp/file2.jpg'
-    file1.save(file1_path)
-    file2.save(file2_path)
-
-    # Compare images
-    distance = compare_images(file1_path, file2_path)
-
-    # You can set a threshold to decide if the faces are considered similar or not
-    threshold = 0.6  # Adjust as needed
-    if distance < threshold:
-        result = {'prediction': 'Similar faces', 'distance': distance}
     else:
-        result = {'prediction': 'Dissimilar faces', 'distance': distance}
-
-    return jsonify(result)
-
-if __name__ == "__main__":
-    app.run(host='0.0.0.0', port=5000)
+        return "Failed to download one or both of the images from the URLs."