Track multiple yellow objects

Author: abidrahmank

Other_Examples/single_color_multiple_points_track.py

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+'''single_color_multiple_points_track.py
+
+	Before reading this code make sure you are thorough with track_yellow_draw_line.py and example_8_3.py. It is a combination of both plus use of new function and new ideas. This code shows how you can use contours to track multiple object. A new function cv.BoundingRect also used here to draw bounding rectangles of contours.
+
+	In track_yellow_draw_line.py, we tracked a single yellow object. And we didn't use contours there. Here we track multiple yellow objects. ie the name, single_color_multiple_points_track.py. That is the main function.
+	
+	Plus, as earlier, i have kept drawing function also there, to see a nice output. And i have uploaded a picture scmpt.png to show you what output i got.
+	
+	Always remember, i am following an hierarchy from simple to complex, and i always put path above. Follow it. 
+	
+Written by Abid.K	--mail me at [email protected]  '''
+
+###############################################################################################################################
+
+import cv
+posx=0
+posy=0
+def getthresholdedimg(im):
+	'''this function take RGB image.Then convert it into HSV for easy colour detection and threshold it with yellow part as white and all other regions as black.Then return that image'''
+	imghsv=cv.CreateImage(cv.GetSize(im),8,3)
+	cv.CvtColor(im,imghsv,cv.CV_BGR2HSV)				# Convert image from RGB to HSV
+	imgthreshold=cv.CreateImage(cv.GetSize(im),8,1)
+	cv.InRangeS(imghsv,cv.Scalar(20,100,100),cv.Scalar(30,255,255),imgthreshold)	# Select a range of yellow color
+	return imgthreshold
+
+
+capture=cv.CaptureFromCAM(0)
+frame = cv.QueryFrame(capture)
+frame_size = cv.GetSize(frame)
+grey_image = cv.CreateImage(cv.GetSize(frame), cv.IPL_DEPTH_8U, 1)
+test=cv.CreateImage(cv.GetSize(frame),8,3)
+cv.NamedWindow("Real")
+cv.NamedWindow("Threshold")
+while(1):
+	color_image = cv.QueryFrame(capture)
+	imdraw=cv.CreateImage(cv.GetSize(frame),8,3)
+	cv.Flip(color_image,color_image,1)
+	cv.Smooth(color_image, color_image, cv.CV_GAUSSIAN, 3, 0)
+	imgyellowthresh=getthresholdedimg(color_image)
+	cv.Erode(imgyellowthresh,imgyellowthresh,None,3)
+	cv.Dilate(imgyellowthresh,imgyellowthresh,None,10)
+
+	storage = cv.CreateMemStorage(0)
+	contour = cv.FindContours(imgyellowthresh, storage, cv.CV_RETR_CCOMP, cv.CV_CHAIN_APPROX_SIMPLE)
+	points = []	
+
+#	This is the new part here. ie Use of cv.BoundingRect()
+	while contour:
+		# Draw bounding rectangles
+		bound_rect = cv.BoundingRect(list(contour))
+		contour = contour.h_next()
+		
+		# for more details about cv.BoundingRect,see documentation
+		pt1 = (bound_rect[0], bound_rect[1])
+		pt2 = (bound_rect[0] + bound_rect[2], bound_rect[1] + bound_rect[3])
+		points.append(pt1)
+		points.append(pt2)
+		cv.Rectangle(color_image, pt1, pt2, cv.CV_RGB(255,0,0), 1)
+		lastx=posx
+		lasty=posy
+		posx=cv.Round((pt1[0]+pt2[0])/2)
+		posy=cv.Round((pt1[1]+pt2[1])/2)
+		if lastx!=0 and lasty!=0:
+			cv.Line(imdraw,(posx,posy),(lastx,lasty),(0,255,255))
+			cv.Circle(imdraw,(posx,posy),5,(0,255,255),-1)
+	cv.Add(test,imdraw,test)
+
+	cv.ShowImage("Real",color_image)
+	cv.ShowImage("Threshold",test)
+	if cv.WaitKey(33)==1048603:
+		cv.DestroyWindow("Real")
+		cv.DestroyWindow("Threshold")
+		break