linny006
diff --git a/‎face_detection/face_detect.py‎
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+import cv2 
+cap=cv2.VideoCapture(0)
+face_cascade =cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
+
+while True:
+    ## capture camera frame, and ret store true and false
+    r, frame= cap.read()
+    gray_frame =cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
+    
+    if r==False:
+        continue
+    faces=face_cascade.detectMultiScale(gray_frame,1.3,5)
+  
+    ## """ The first argument is the image, the second is the 
+    ## scalefactor (how much the image size will be reduced at each image scale), 
+    ## and the third is the minNeighbors (how many neighbors each rectangle should have)"""
+    
+    for(x,y,w,h) in faces:
+        cv2.rectangle(frame,(x,y),(x+w,y+h),(255,125,0),2)## color and width 
+        cv2.putText(frame,"DETECTED",(x,y-10),cv2.FONT_HERSHEY_SIMPLEX,1,(100,125,255),1,cv2.LINE_AA)
+    cv2.imshow("video frame",frame)
+    key_pressed =cv2.waitKey(1) & 0xFF
+    
+    ## """cv2.waitKey() returns a 32 Bit integer value (might be dependent on the platform). 
+    ## The key input is in ASCII which is an 8 Bit integer value. So you only care
+    ## about these 8 bits and want all other bits to be 0. This you can achieve with:0xFF"""
+    
+    ### ord converts characters in unicode
+    if key_pressed ==ord('n'):
+        break
+        
+cap.release()
+cv2.destroyAllWindows()