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facedetection.py

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+import cv2
+import numpy as np
+import time
+
+faceClassifier = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+videoCam = cv2.VideoCapture(0)
+
+if not videoCam.isOpened():
+    print("Camera cannot be accessed")
+    exit()
+
+qPressed = False
+while (qPressed == False):
+    ret, frame = videoCam.read()
+
+    if ret == True:
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        faces = faceClassifier.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=2)
+
+        for (x, y, w, h) in faces:
+            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+        # print("Number of detected faces: ", len(faces))
+        text = "Number of Detected Faces = " + str(len(faces))
+
+        font = cv2.FONT_HERSHEY_SIMPLEX
+        cv2.putText(frame, text, (0, 30), font, 1, (255, 0, 0), 1)
+
+        cv2.imshow("Result", frame)
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            qPressed = True
+            break
+
+videoCam.release()
+cv2.destroyAllWindows()

facetracking.py

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+import cv2
+from cvzone.FaceDetectionModule import FaceDetector
+import numpy as np
+import time
+
+cap = cv2.VideoCapture(0)
+ws, hs = 1280, 720
+cap.set(3, ws)
+cap.set(4, hs)
+
+if not cap.isOpened():
+    print("Camera couldn't Access!!!")
+    exit()
+
+detector = FaceDetector()
+prev_face_x, prev_face_y = None, None
+prev_time = time.time()
+
+while True:
+    success, img = cap.read()
+    img, bboxs = detector.findFaces(img, draw=False)
+
+    if bboxs:
+        # Get the head position (top-center of the bounding box)
+        head_x = bboxs[0]["bbox"][0] + bboxs[0]["bbox"][2] // 2
+        head_y = bboxs[0]["bbox"][1]
+
+        # Draw the red circle at the head position
+        cv2.circle(img, (head_x, head_y), 80, (0, 0, 255), 2)
+        cv2.circle(img, (head_x, head_y), 15, (0, 0, 255), cv2.FILLED)
+        cv2.putText(img, "TARGET LOCKED", (850, 50), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)
+
+        # Calculate face motion trajectory and speed
+        if prev_face_x is not None and prev_face_y is not None:
+            # Calculate motion trajectory
+            trajectory = np.sqrt((head_x - prev_face_x) ** 2 + (head_y - prev_face_y) ** 2)
+
+            # Calculate time difference
+            current_time = time.time()
+            time_diff = current_time - prev_time
+
+            # Calculate speed
+            speed = trajectory / time_diff
+
+            # Print motion trajectory and speed
+            print("Motion Trajectory:", trajectory)
+            print("Speed:", speed, "pixels per second")
+
+            # Draw motion trajectory line
+            cv2.line(img, (prev_face_x, prev_face_y), (head_x, head_y), (0, 255, 0), 2)
+
+            # Draw arrow to indicate direction of motion
+            cv2.arrowedLine(img, (prev_face_x, prev_face_y), (head_x, head_y), (255, 0, 0), 2)
+
+            # Display speed value
+            cv2.putText(img, f"Speed: {speed:.2f} pixels per second", (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1,
+                        (255, 255, 255), 2)
+
+            # Update previous face position and time
+            prev_face_x, prev_face_y = head_x, head_y
+            prev_time = current_time
+        else:
+            # Initialize previous face position and time
+            prev_face_x, prev_face_y = head_x, head_y
+            prev_time = time.time()
+    else:
+        cv2.putText(img, "NO TARGET", (880, 50), cv2.FONT_HERSHEY_PLAIN, 3, (0, 0, 255), 3)
+        cv2.circle(img, (640, 360), 80, (0, 0, 255), 2)
+        cv2.circle(img, (640, 360), 15, (0, 0, 255), cv2.FILLED)
+
+    cv2.imshow("Image", img)
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()