Update main.py

main.py

@@ -1,65 +1,66 @@
-import os
-import warnings
-
-os.environ['TF_ENABLE_ONEDNN_OPTS']=str(0)
-warnings.filterwarnings('ignore')
-
-#import pandas as pd
-import numpy as np
-
-from deepface import DeepFace
-from db import create_db, get_student_row
-from helper_fns import  binary_to_pil, extract_faces
-
-
-
-
-def verify_student(db_path, last_name, matric_no, input_image):
-    data = get_student_row(db_path, last_name, matric_no)
-    
-    if data is not None:
-        binary_image = data['image']
-    else: 
-        raise ValueError('No student having last name {last_name} and matric no: {matric_no} exists in this database.')
-    actual_image =np.array(binary_to_pil(binary_image))
-
-    webcam_image = input_image
-    if webcam_image is None:
-        raise ValueError(f'No image')
-    else:
-        print('Received image')
-    results = DeepFace.verify(webcam_image,
-                            actual_image,
-                            model_name='Facenet',
-                            detector_backend="retinaface",
-                            distance_metric="cosine",
-                            enforce_detection=True,
-                            anti_spoofing=True,
-                            align=True,
-                            normalization="Facenet")
-    result = results['verified']
-    if results['verified'] == True:
-        result = f"Verification check complete! Successfully verified student: {data['last_name']} {data['first_name']} with matriculation number {data['matric_no']}"
-    else:
-        result = f"Verification check complete! You are not student {data['last_name']} {data['first_name']} with matriculation number {data['matric_no']}"
-        
-    cropped_input_image, cropped_returned_image = extract_faces(webcam_image, actual_image, results)
-    return result, cropped_input_image, cropped_returned_image, actual_image
-
-
-def main(last_name, matric_no, input_image):
-
-    #df = pd.read_csv('students_df.csv')
-    db_path = 'students_database.db'
-    #create_db(db_path, df)
-        
-    result, cropped_input_image, cropped_returned_image, actual_image = verify_student(db_path,
-                                                                                        last_name,
-                                                                                        matric_no,
-                                                                                        input_image)
-
-    #os.remove('students_database.db')
-    return result, cropped_input_image, cropped_returned_image, actual_image
-
-if __name__ ==  '__main__':
+import os
+import warnings
+
+os.environ['TF_ENABLE_ONEDNN_OPTS']=str(0)
+warnings.filterwarnings('ignore')
+
+#import pandas as pd
+import numpy as np
+
+from deepface import DeepFace
+from db import create_db, get_student_row
+from helper_fns import  binary_to_pil, extract_faces
+
+
+
+
+def verify_student(db_path, last_name, matric_no, input_image):
+    data = get_student_row(db_path, last_name, matric_no)
+    
+    if data is not None:
+        binary_image = data['image']
+    else: 
+        raise ValueError('No student having last name {last_name} and matric no: {matric_no} exists in this database.')
+    actual_image =np.array(binary_to_pil(binary_image))
+
+    webcam_image = input_image
+    if webcam_image is None:
+        raise ValueError(f'No image')
+    else:
+        print('Received image')
+        print(type(webcam_image))
+    results = DeepFace.verify(webcam_image,
+                            actual_image,
+                            model_name='Facenet',
+                            detector_backend="retinaface",
+                            distance_metric="cosine",
+                            enforce_detection=True,
+                            anti_spoofing=True,
+                            align=True,
+                            normalization="Facenet")
+    result = results['verified']
+    if results['verified'] == True:
+        result = f"Verification check complete! Successfully verified student: {data['last_name']} {data['first_name']} with matriculation number {data['matric_no']}"
+    else:
+        result = f"Verification check complete! You are not student {data['last_name']} {data['first_name']} with matriculation number {data['matric_no']}"
+        
+    cropped_input_image, cropped_returned_image = extract_faces(webcam_image, actual_image, results)
+    return result, cropped_input_image, cropped_returned_image, actual_image
+
+
+def main(last_name, matric_no, input_image):
+
+    #df = pd.read_csv('students_df.csv')
+    db_path = 'students_database.db'
+    #create_db(db_path, df)
+        
+    result, cropped_input_image, cropped_returned_image, actual_image = verify_student(db_path,
+                                                                                        last_name,
+                                                                                        matric_no,
+                                                                                        input_image)
+
+    #os.remove('students_database.db')
+    return result, cropped_input_image, cropped_returned_image, actual_image
+
+if __name__ ==  '__main__':
     main()