new features added

Author: solveditnpc

attendance_opencv_2.0.py

@@ -0,0 +1,106 @@
+# Generalised the code for import of names and face_encodings 
+# Unknown faces are now saved in a folder named unknown_faces in the project directory
+# Fixed the issue where time of the recognition was same for all the faces recognised 
+# Follow the dictionary format in store1.csv ie "name" "image_path" if you import your own file 
+import cv2
+import csv
+import face_recognition
+import numpy as np
+import datetime
+import os
+
+# Create a folder for unknown faces if it doesn't exist already
+unknown_faces_folder = "unknown_faces" 
+os.makedirs(unknown_faces_folder, exist_ok=True)
+
+video_capture = cv2.VideoCapture(0)
+
+# Specify the folder location and csv file location
+database_folder = "paste your database path or the file name if it exists in this projects directory"
+csv_file = "paste your csv file path or the file name if it exists in this projects directory"
+
+# Store the faceencodings and names of the people in the database
+known_face_encodings = []
+known_face_names = []
+
+# Read the CSV file and load face encodings
+with open(csv_file, newline='') as csvfile:
+    reader = csv.DictReader(csvfile)
+    for row in reader:
+        image_path = os.path.join(database_folder, row['image_path'])
+        image = face_recognition.load_image_file(image_path)
+        face_encoding = face_recognition.face_encodings(image)[0]
+        known_face_encodings.append(face_encoding)
+        known_face_names.append(row['name'])
+
+# Creating a copy of the names list
+students = known_face_names.copy()
+
+# Get the current date for the CSV filename
+current_date = datetime.datetime.now().strftime("%Y-%m-%d")
+
+# Open the CSV file for writing, or create it 
+f = open(f"{current_date}.csv", "w+", newline="")
+lnwriter = csv.writer(f)
+
+# Initialize a counter for unknown faces
+unknown_face_counter = 1
+
+#Check if the unknown faces in the webcam feed are already in the unknown folder  
+def is_face_unique(face_encoding, folder_path):
+    for filename in os.listdir(folder_path):
+        if filename.endswith(".jpg"):
+            saved_image = face_recognition.load_image_file(os.path.join(folder_path, filename))
+            saved_face_encodings = face_recognition.face_encodings(saved_image)
+            if saved_face_encodings:
+                saved_face_encoding = saved_face_encodings[0]
+                matches = face_recognition.compare_faces([saved_face_encoding], face_encoding)
+                if matches[0]:
+                    return False
+    return True
+
+# Explained in the last version
+while True:
+    ret, frame = video_capture.read()
+    rgb_frame = frame[:, :, ::-1]
+
+    face_locations = face_recognition.face_locations(rgb_frame)
+    face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)
+
+    for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
+        matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
+        
+        name = "Unknown"
+
+        face_distance = face_recognition.face_distance(known_face_encodings, face_encoding)
+        best_match_index = np.argmin(face_distance)
+        if matches[best_match_index]:
+            name = known_face_names[best_match_index]
+         
+        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
+        
+        if name == "Unknown":
+            # Add the unknown faces not already in the unknown folder to the unknown folder 
+            if is_face_unique(face_encoding, unknown_faces_folder):
+                face_image = frame[top:bottom, left:right]
+                face_filename = f"{unknown_faces_folder}/unknown{unknown_face_counter}.jpg"
+                cv2.imwrite(face_filename, face_image)
+                unknown_face_counter += 1
+
+        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
+        font = cv2.FONT_HERSHEY_DUPLEX
+        cv2.putText(frame, name, (left + 6, bottom - 6), font, 0.6, (255, 255, 255), 1)
+
+        if name in students:
+            students.remove(name)
+            current_time = datetime.datetime.now().strftime("%H:%M:%S")
+            lnwriter.writerow([name, current_time])
+
+    cv2.imshow('Video', frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+video_capture.release()
+cv2.destroyAllWindows()
+f.close()