Added comments and removed debug elements from the python code.

camera module/main.py

@@ -38,25 +38,24 @@ def resizeImage(img):
 
 def findMatchingContour(img, objX, objY):
 
-	dilated = img.copy()
-	#dilated = cv2.dilate(img, (5,5), iterations=1)
-	canny = cv2.Canny(dilated, CANNY_LOW_THRES, CANNY_HIGH_THRES)
+	# Apply the canny detector on the image and find the contours.
+	canny = cv2.Canny(img, CANNY_LOW_THRES, CANNY_HIGH_THRES)
 	if MAJOR_VERSION == 3:
 		_, contours, hierarchy = cv2.findContours(canny, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
 	else:
 		contours, hierarchy = cv2.findContours(canny, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
 	
-	#print('len:' + str(len(contours)))
+	# Sort the contours based on their area.
 	contours.sort(key = cv2.contourArea, reverse = True)
 	
-	#cv2.imshow('hey', canny)
+	# Determine which of the detected contours is the drone.
 	for i in range(len(contours)):
 		contour = contours[i]
 		x,y,w,h = cv2.boundingRect(contour)
 
 		area = w*h
 		dist = cv2.pointPolygonTest(contour, (objX,objY), False)
-		#print('dist: ' + str(dist))
+		
 		if area >= MIN_CONTOUR_AREA and area <= MAX_CONTOUR_AREA and dist >= 0:
 			return (True, contour)
 
@@ -66,7 +65,6 @@ def processImage(img):
 
 	# Resize image to the desired height.
 	resized = resizeImage(img)
-	#return removeColors(resized)
 	dim = resized.shape
 
 	# Convert to grayscale.
@@ -100,18 +98,16 @@ def processImage(img):
 	objCenterY = int( (y + y + h) / 2)
 	imgCenterX = int(dim[1]/2)
 	imgCenterY = int(dim[0]/2)
-	#cv2.circle(resized, (objCenterX, objCenterY), 5, BLUE, LINE_THICKNESS)
+	
 	ret, finalContour = findMatchingContour(blur, objCenterX, objCenterY)
 	if (ret == False):
 		return (resized, 0, 0)
 	
-	#cv2.fillPoly(resized, finalContour, BLUE, cv2.LINE_4)
 	x,y,w,h = cv2.boundingRect(finalContour)
 	objCenterX = int( (x + x + w) / 2)
 	objCenterY = int( (y + y + h) / 2)
 
 	# Draw the bounding rectangle  and its centroid to the image.
-	#cv2.circle(resized, (objCenterX, objCenterY), 5, YELLOW, LINE_THICKNESS)
 	cv2.rectangle(resized, (x,y), (x+w,y+h), RED, LINE_THICKNESS)
 	cv2.line(resized, (objCenterX, objCenterY), (imgCenterX, imgCenterY), YELLOW, LINE_THICKNESS)
 
@@ -160,14 +156,13 @@ if (cap.isOpened() == False):
 	print('Error opening stream.')
 	quit()
 
-#cap.set(1, 30*6)
-
 while (cap.isOpened()):
 	try:
 		ret, frame = cap.read()
 		if (ret == True):
 			img, xDir, yDir = processImage(frame)
-			#cv2.imshow('Frame', img)
+			
+			# Encode and send the processed frame.
 			encoded, buffer = cv2.imencode('.jpg', img)
 			jpg_as_text = base64.b64encode(buffer)
 			footage_socket.send(jpg_as_text)