- also process video file instead of live camera. can be choosen by command line

- added command line parameters filename and framerate. Removed display parameter
- show computet contours
- show color distances
- added axis labels to scatter plot

git-svn-id: http://moon:8086/svn/software/trunk/projects/opencv@316 b431acfa-c32f-4a4a-93f1-934dc6c82436

beadDetect.py

@@ -1,12 +1,10 @@
 # import the necessary packages
 from __future__ import print_function
-from PiVideoStream import PiVideoStream
+
 from imutils.video import FPS
-from picamera.array import PiRGBArray
-from picamera import PiCamera
+
 import numpy as np
 import argparse
-import imutils
 import time
 import cv2
 import pprint
@@ -16,6 +14,14 @@ from mpl_toolkits.mplot3d import Axes3D
 width = 320
 height = 240
 
+def colordistance(color1, color2):
+	
+	d0 = (color1[0]-color2[0])
+	d1 = (color1[1]-color2[1])
+	d2 = (color1[2]-color2[2])
+	return np.math.sqrt(d0*d0 + d1*d1 + d2*d2)
+
+
 class FindObjects():
 	def __init__(self):
 		self.innerOuterRatio = 0.6	# const
@@ -40,10 +46,8 @@ class FindObjects():
 		count = 0
 		objects = []
 		temp_objects = []
-		objectsIds = []
 		objectsCandIds = []
-		for cnt in contours:
-			if hierachy[0][count][3] == -1:
+		while count != -1:
 			family = FindObjects.getFamily([], count, hierachy)
 
 			dupDict = {}
@@ -57,7 +61,7 @@ class FindObjects():
 
 			objectsCandIds.append(members)
 
-			count += 1
+			count = hierachy[0][count][0]
 	
 		for family in objectsCandIds:
 			obj = []
@@ -69,7 +73,7 @@ class FindObjects():
 				if (perimeter > 0):
 					Q = 4*pi*area/(perimeter*perimeter)
 
-				if Q >= 0.7:
+				if Q > 0.7:
 					diameter = max(member['bbox'][2], member['bbox'][3])
 					self.maxDiameter = max(self.maxDiameter, diameter)
 					self.minDiameter = min(self.minDiameter, diameter)
@@ -103,15 +107,27 @@ class FindObjects():
 ap = argparse.ArgumentParser()
 ap.add_argument("-n", "--num-frames", type=int, default=100,
 	help="# of frames to loop over for FPS test")
-ap.add_argument("-d", "--display", type=int, default=-1,
+ap.add_argument("-r", "--framerate", type=int, default=30,
+	help="# of frames to loop over for FPS test")
+ap.add_argument("-f", "--filename", type=str, default='piCamera',
 	help="Whether or not frames should be displayed")
 args = vars(ap.parse_args())
 
+videoFile = args["filename"]
+framerate = args["framerate"]
+
 # created a *threaded *video stream, allow the camera sensor to warmup,
 # and start the FPS counter
-print("[INFO] sampling THREADED frames from `picamera` module...")
-vs = PiVideoStream(resolution=(width,height), framerate=30).start()
-time.sleep(2.0)
+if videoFile == "piCamera":
+	from PiVideoStream import PiVideoStream
+	from picamera.array import PiRGBArray
+	from picamera import PiCamera
+	vs = PiVideoStream(resolution=(width,height), framerate=framerate).start()
+	time.sleep(2.0)
+else:
+	vs = cv2.VideoCapture(videoFile)
+
+print("[INFO] sampling THREADED frames from `" + videoFile + "` at " + str(framerate) + " frame/s")
 fps = FPS().start()
 findObjects = FindObjects()
 
@@ -120,7 +136,11 @@ beadColors = []
 # loop over some frames...this time using the threaded stream
 while fps._numFrames < args["num_frames"]:
 	# grab the frame from the threaded video stream
+	if videoFile == "piCamera":
 		frame = vs.read()
+	else:
+		ret, frame = vs.read()
+
 	gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
 	gray_blurred = cv2.medianBlur(gray,5)
 
@@ -137,6 +157,8 @@ while fps._numFrames < args["num_frames"]:
 
 	# Contours
 	(_, contours, hierachy) = cv2.findContours(img1_canny.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
+	img1_contours = np.zeros((height,width,3), np.uint8)
+	img1_contours = cv2.drawContours(img1_contours, contours, -1, (0,255,0), 1)
 	
 	objects = findObjects.find(contours, hierachy)
 	
@@ -166,7 +188,7 @@ while fps._numFrames < args["num_frames"]:
 					mean_color = cv2.mean(roi)
 					img1_colors = cv2.circle(img1_colors,(int(pos[0]),int(pos[1])),int(diameter/2),mean_color,-1)
 					beads.append({'pos' : pos, 'diameter' : diameter, 'color' : mean_color[0:3]})
-					img1_objects = cv2.circle(img1_objects,member['pos'],int(diameter/2),(255,255,255),thickness)
+#					img1_objects = cv2.circle(img1_objects,member['pos'],int(diameter/2),(255,255,255),thickness)
 			else:
 				img1_objects = cv2.rectangle(img1_objects,(x,y),(x+w,y+h),(0,0,255),2)
 
@@ -176,21 +198,30 @@ while fps._numFrames < args["num_frames"]:
 		beadColors.append(bead['color'])
 
 #	cv2.imshow('Thresholded',img1_thr)
-	cv2.imshow('detected colors', img1_colors)
+	cv2.imshow('Contours', img1_contours)
+	cv2.imshow('Colors', img1_colors)
 	cv2.imshow('Canny',img1_canny)
 	cv2.imshow('Objects',img1_objects)
+	if videoFile == "piCamera":	
 		cv2.waitKey(1)
+	else:
+#		cv2.waitKey(0)
+		cv2.waitKey(int(1000.0/framerate))
+		
 
 	# update the FPS counter
 	fps.update()
 
 # stop the timer and display FPS information
 fps.stop()
-vs.stop()
+if videoFile == "piCamera":
+	vs.stop()
+
 print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
 print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
-print("[INFO] Camera : elasped time: {:.2f}".format(vs.getfps().elapsed()))
-print("[INFO] Camera: approx. FPS: {:.2f}".format(vs.getfps().fps()))
+if videoFile == "piCamera":
+	print("[INFO] Camera : elasped time: {:.2f}".format(vs.getfps().elapsed()))
+	print("[INFO] Camera: approx. FPS: {:.2f}".format(vs.getfps().fps()))
 
 # Output stats
 findObjects.printStats()
@@ -218,9 +249,20 @@ ret,label,center=cv2.kmeans(Z,10,None,criteria,10,cv2.KMEANS_PP_CENTERS)
 
 print (center)
 
+cnt1 = 0
+for c1 in center:
+	cnt2 = 0
+	for c2 in center:
+		print ("Color distance["+ str(cnt1) + "," + str(cnt2) + "] = " + str(colordistance(c1, c2)))
+		cnt2 += 1
+	cnt1 += 1	
+		
 # Scatter plot of colors
 fig = plt.figure()
 ax = fig.add_subplot(111, projection='3d')
+ax.set_xlabel('blue')
+ax.set_ylabel('green')
+ax.set_zlabel('red')
 ax.scatter(blue, green, red, zdir='z', s=10, c=(0,0,0), lw = 0, depthshade=True)
 ax.scatter(center[:,2], center[:,1], center[:,0], zdir='z', s=500, facecolors=center, lw = 1, depthshade=True)