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Author: Jivan052

Day10(objectdetection).py

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+import cv2
+
+#  pre-trained Haar cascade for face detection
+face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+
+cap = cv2.VideoCapture(0)
+
+prev_frame = None
+
+while True:
+    #frame-by-frame capturing
+    ret, frame = cap.read()
+
+    
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    # face detection
+    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
+
+    # draw rectangles around the faces
+    for (x, y, w, h) in faces:
+        cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
+
+  
+    if prev_frame is not None:
+       
+        frame_diff = cv2.absdiff(prev_frame, gray)
+        
+       
+        _, frame_diff_thresh = cv2.threshold(frame_diff, 30, 255, cv2.THRESH_BINARY)
+
+        
+        contours, _ = cv2.findContours(frame_diff_thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+      
+        for contour in contours:
+            if cv2.contourArea(contour) > 50:
+                x, y, w, h = cv2.boundingRect(contour)
+                cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+    cv2.imshow('Video', frame)
+
+    # frame store for next iteration
+    prev_frame = gray
+
+    # exit with 'q'
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+#release
+cap.release()
+cv2.destroyAllWindows()