etc: add motion_crop

+import cv2
+import numpy as np
+
+cap = cv2.VideoCapture('./videos/test.mp4') #load video
+count1 = 0 #counts number of frames
+
+#capture two frames
+rval, frame1 = cap.read()
+rval, frame2 = cap.read()
+
+while cap.isOpened():
+
+    diff = cv2.absdiff(frame1, frame2)  #difference of two frames
+    gray = cv2.cvtColor(diff,cv2.COLOR_BGR2GRAY)    #convert diff into greyscale
+
+    blur = cv2.GaussianBlur(gray, (5,5), 0) #blur image to reduce noise
+    _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY) #set threshold
+    dilated = cv2.dilate(thresh, None, iterations=3) #fill holes in the thresholded image
+    
+    #find contour
+    contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+
+    count2 = 0  #counts number of motions in a frame 
+
+    #further implementation(removing, rectangle)
+    for contour in contours:
+        (x, y, w, h) = cv2.boundingRect(contour)    #values of contour
+
+        if cv2.contourArea(contour) < 7000:    #to remove small unnecessary contours, (modify number for better results)
+            continue
+        
+        filename = "clip{}-{}.jpg".format(count1,count2)
+
+        motion = frame1[y:y+h, x:x+w]
+        cv2.imwrite(filename, motion)
+
+        count2 += 1
+        #cv2.rectangle(frame1, (x, y), (x+w, y+h), (0, 0, 255), 2)   #draw rectangle on frame1
+
+    count1 += 1
+
+    #show results
+    #cv2.imshow("feed", frame1)  
+    
+    #change to next frame
+    frame1 = frame2 
+    rval, frame2 = cap.read()
+
+    #incase of error
+    if cv2.waitKey(40) == 27:
+        break
+
+cap.release()
+cv2.destroyAllWindows()
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