commit d8a9a310bb51d31494804161f69d2d63fdc57e70
Author: Jaiwin prince <56401289+Jaiwin21@users.noreply.github.com>
Date:   Fri Jun 2 19:44:21 2023 +0100

    Add files via upload

diff --git a/main.py b/main.py
new file mode 100644
index 0000000..794e001
--- /dev/null
+++ b/main.py
@@ -0,0 +1,58 @@
+import cv2
+import time
+
+# Load the face and eye cascades from the OpenCV library. This will be the cornerstone of this software.
+face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml")
+eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_eye.xml")
+
+# Load the video footage into the IDE. Realistically, the user should have to upload it through a GUI but it was not implemented.
+cap = cv2.VideoCapture("test1.mp4")
+
+# Initialization of variables
+frame_count = 0
+last_increment_time = time.time()
+eye_contact_count = 0
+face_rectangles = []
+eye_rectangles = []
+
+while True:
+    # Infinite loop that keeps reading frames from the video footage until there are no more frames
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    # Convert the frame to grayscale
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # Find all faces in the frame, with the use of pythons OpenCV library
+    face_rectangles = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+
+    # Iterate over each face
+    for face_rect in face_rectangles:
+        # Find all eyes within the face rectangle
+        x, y, w, h = face_rect
+        eye_rectangles = eye_cascade.detectMultiScale(gray[y:y+h, x:x+w], scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+
+        # Check if both eyes are within the face rectangle
+        if len(eye_rectangles) == 2 and all([x > 0 and y > 0 and x + w < frame.shape[1] and y + h < frame.shape[0] for x, y, w, h in eye_rectangles]):
+            # Check if 1 second has passed since the last increment
+            current_time = time.time()
+            if current_time - last_increment_time >= 1:
+                # Increment the eye contact count and update the last increment time
+                eye_contact_count += 1
+                last_increment_time = current_time
+
+    # Increment the frame count
+    frame_count += 1
+
+    # Show the video feed with the eye contact count
+    cv2.putText(frame, "Eye contact count: {}".format(eye_contact_count), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
+    cv2.imshow("Eye Tracking", frame)
+
+    # Exit if the 'q' key is pressed
+    if cv2.waitKey(1) & 0xFF == ord('w'):
+        break
+
+# Release the video capture and close all windows
+cap.release()
+cv2.destroyAllWindows()