diff --git a/.DS_Store b/.DS_Store
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index 0000000..89c8aa1
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diff --git a/._.DS_Store b/._.DS_Store
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index 0000000..4be07d1
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diff --git a/.gitignore b/.gitignore
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index 0000000..a5fd33c
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+# env folder
+env/
+faces/
\ No newline at end of file
diff --git a/app.py b/app.py
index 63b5a1b..2695cfa 100644
--- a/app.py
+++ b/app.py
@@ -2,42 +2,31 @@ import face_recognition
 import cv2
 import os
 
-image_to_scan = 'image1.jpg'
-image_dataset_folder = 'faces'
+image_load = 'image1.jpg'
+# image_data = 'faces/rika.png'
+image_data = 'faces/rika.png'
 
-# Load the image to scan
-image = face_recognition.load_image_file(image_to_scan)
+# Load the images
+image_load_path = os.path.join(os.getcwd(), image_load)
+image_data_path = os.path.join(os.getcwd(), image_data)
+image_load = face_recognition.load_image_file(image_load_path)
+image_data = face_recognition.load_image_file(image_data_path)
 
-# Detect the faces in the image
-face_locations = face_recognition.face_locations(image)
+# Find the face locations and encodings in each image
+image_load_face_locations = face_recognition.face_locations(image_load)
+image_load_face_encodings = face_recognition.face_encodings(image_load, image_load_face_locations)
+image_data_face_locations = face_recognition.face_locations(image_data)
+image_data_face_encodings = face_recognition.face_encodings(image_data, image_data_face_locations)
 
-# Draw a rectangle around each detected face using OpenCV
-for (top, right, bottom, left) in face_locations:
-    cv2.rectangle(image, (left, top), (right, bottom), (0, 255, 0), 2)
+# Compare the face encodings
+matches = face_recognition.compare_faces(image_data_face_encodings, image_load_face_encodings[0])
 
-# Display the image with the detected faces in a window
-cv2.imshow('Faces', image)
+# Draw boxes around the faces in the image_load image
+for (top, right, bottom, left), match in zip(image_load_face_locations, matches):
+    if match:
+        cv2.rectangle(image_load, (left, top), (right, bottom), (0, 0, 255), 2)
+
+# Display the image with the boxes around the matching faces
+cv2.imshow('Image', image_load)
 cv2.waitKey(0)
-
-# Load the images from the 'faces' folder and store them in a list
-images = []
-for filename in os.listdir(image_dataset_folder):
-    # if the file name ends with '.jpg' or '.png'
-    if filename.endswith('.jpg') or filename.endswith('.png'):
-        images.append(face_recognition.load_image_file(os.path.join(image_dataset_folder, filename)))
-
-# Loop through the list of images and detect the faces in each image using face_recognition
-for image in images:
-    # Detect the faces in the image
-    face_locations = face_recognition.face_locations(image)
-
-    # Draw a rectangle around each detected face using OpenCV
-    for (top, right, bottom, left) in face_locations:
-        cv2.rectangle(image, (left, top), (right, bottom), (0, 255, 0), 2)
-
-    # Display the images with the detected faces in a window
-    cv2.imshow('Faces', image)
-    cv2.waitKey(0)
-
-# Wait for the user to press a key to exit the program
 cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/app2.py b/app2.py
new file mode 100755
index 0000000..e51df36
--- /dev/null
+++ b/app2.py
@@ -0,0 +1,35 @@
+import face_recognition
+import cv2
+import os
+
+image_load = 'image1.jpg'
+image_data_folder = 'faces/'
+
+# Load the images in the image_data_folder and save their face encodings in a list
+image_dataset = []
+for filename in os.listdir(image_data_folder):
+    image_data_path = os.path.join(os.getcwd(), image_data_folder, filename)
+    image_data = face_recognition.load_image_file(image_data_path)
+    image_data_encoding = face_recognition.face_encodings(image_data)[0]
+    image_dataset.append((filename, image_data_encoding))
+
+# Load the image_load and find the face locations and encodings
+image_load_path = os.path.join(os.getcwd(), image_load)
+image_load = face_recognition.load_image_file(image_load_path)
+image_load_face_locations = face_recognition.face_locations(image_load)
+image_load_face_encodings = face_recognition.face_encodings(image_load, image_load_face_locations)
+
+# Compare the face encodings in image_load to the face encodings in image_dataset
+for (top, right, bottom, left), face_encoding in zip(image_load_face_locations, image_load_face_encodings):
+    matches = face_recognition.compare_faces([x[1] for x in image_dataset], face_encoding, tolerance=0.55)
+    if True in matches:
+        # Find the name of the matching face
+        name = image_dataset[matches.index(True)][0]
+        # Draw a box around the face and show the name on the top right of the box
+        cv2.rectangle(image_load, (left, top), (right, bottom), (0, 0, 255), 2)
+        cv2.putText(image_load, name, (right, top), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
+
+# Display the image with the boxes and names around the matching faces
+cv2.imshow('Image', image_load)
+cv2.waitKey(0)
+cv2.destroyAllWindows()
\ No newline at end of file
diff --git a/image1.jpg b/image1.jpg
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diff --git a/image2.jpg b/image2.jpg
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diff --git a/image3.jpg b/image3.jpg
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