- improved camera calibration
git-svn-id: http://moon:8086/svn/software/trunk/projects/opencv@320 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
+61
-78
@@ -61,54 +61,56 @@ class FindObjects():
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objects = []
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temp_objects = []
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objectsCandIds = []
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while count != -1:
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family = FindObjects.getFamily([], count, hierachy)
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dupDict = {}
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members = []
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for member in family:
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x,y,w,h = cv2.boundingRect(contours[member]);
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key = str([x,y,w,h]) + '.key'
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if not key in dupDict:
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dupDict[key] = member
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members.append({ 'id' : member, 'bbox' : [x,y,w,h]})
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objectsCandIds.append(members)
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count = hierachy[0][count][0]
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if hierachy.any():
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while count != -1:
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family = FindObjects.getFamily([], count, hierachy)
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for family in objectsCandIds:
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obj = []
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for member in family:
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area = cv2.contourArea(contours[member['id']])
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perimeter = cv2.arcLength(contours[member['id']], True)
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pi = 3.14159265359
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Q = 0
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if (area > 10):
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Q = 4*pi*area/(perimeter*perimeter)
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if Q > 0.7:
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diameter = max(member['bbox'][2], member['bbox'][3])
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self.maxDiameter = max(self.maxDiameter, diameter)
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self.minDiameter = min(self.minDiameter, diameter)
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member['diameter'] = diameter
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member['pos'] = (int(member['bbox'][0] + member['bbox'][2]/2), int(member['bbox'][1] + member['bbox'][3]/2))
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obj.append(member)
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if obj:
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temp_objects.append(obj)
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for obj in temp_objects:
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for member in obj:
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if member['diameter'] < self.innerOuterRatio*self.maxDiameter:
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member['isHole'] = True
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else:
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member['isHole'] = False
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if len(obj) == 2:
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self.meanThickness = int(abs(obj[0]['diameter'] - obj[1]['diameter'])/2)
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objects.append({'thickness' : self.meanThickness, 'members' : obj})
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dupDict = {}
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members = []
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for member in family:
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x,y,w,h = cv2.boundingRect(contours[member]);
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key = str([x,y,w,h]) + '.key'
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if not key in dupDict:
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dupDict[key] = member
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members.append({ 'id' : member, 'bbox' : [x,y,w,h]})
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objectsCandIds.append(members)
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count = hierachy[0][count][0]
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for family in objectsCandIds:
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obj = []
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for member in family:
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area = cv2.contourArea(contours[member['id']])
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perimeter = cv2.arcLength(contours[member['id']], True)
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pi = 3.14159265359
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Q = 0
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if (area > 10):
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Q = 4*pi*area/(perimeter*perimeter)
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if Q > 0.7:
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diameter = max(member['bbox'][2], member['bbox'][3])
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self.maxDiameter = max(self.maxDiameter, diameter)
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self.minDiameter = min(self.minDiameter, diameter)
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member['diameter'] = diameter
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member['pos'] = (int(member['bbox'][0] + member['bbox'][2]/2), int(member['bbox'][1] + member['bbox'][3]/2))
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obj.append(member)
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if obj:
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temp_objects.append(obj)
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for obj in temp_objects:
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for member in obj:
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if member['diameter'] < self.innerOuterRatio*self.maxDiameter:
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member['isHole'] = True
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else:
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member['isHole'] = False
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if len(obj) == 2:
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self.meanThickness = int(abs(obj[0]['diameter'] - obj[1]['diameter'])/2)
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objects.append({'thickness' : self.meanThickness, 'members' : obj})
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return objects
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@@ -126,7 +128,9 @@ ap.add_argument("-r", "--framerate", type=int, default=30,
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ap.add_argument("-f", "--filename", type=str, default='piCamera',
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help="Whether or not frames should be displayed")
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ap.add_argument("-c", "--calibrate", type=str, default='off',
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help="Whether or not frames should be displayed")
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help="Whether calibration shall be performed")
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ap.add_argument("-u", "--use-calibration", type=str, default='off',
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help="Whether calibration shall be used")
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args = vars(ap.parse_args())
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videoFile = args["filename"]
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@@ -138,7 +142,7 @@ if videoFile == "piCamera":
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from PiVideoStream import PiVideoStream
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from picamera.array import PiRGBArray
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from picamera import PiCamera
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vs = PiVideoStream(resolution=(2*width,2*height), framerate=framerate).start()
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vs = PiVideoStream(resolution=(width,height), framerate=framerate).start()
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time.sleep(5.0)
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else:
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vs = cv2.VideoCapture(videoFile)
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@@ -161,54 +165,34 @@ if args["calibrate"] == 'on':
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ret, frame = vs.read()
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Z = np.float32(frame)
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print (frame.dtype)
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print (frame.shape)
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print (lens_corr.dtype)
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print (lens_corr.shape)
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print (Z.dtype)
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print (Z.shape)
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ref_color = Z[height/2, width/2, :]
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ref_color = cv2.mean(Z[int(height/2-8):int(height/2+8), int(width/2-8):int(width/2+8), :])
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print (ref_color)
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for c in range (0, 3):
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lens_corr[:,:,c] = cv2.divide(ref_color[c], Z[:,:,c])
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lens_corr = cv2.divide(ref_color, Z)
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params = list()
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params.append(cv2.IMWRITE_PNG_COMPRESSION)
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params.append(0)
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for c in range (0, 3):
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lens_corr[:,:,c] = cv2.multiply(128, lens_corr[:,:,c])
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cv2.imwrite("lens_corr.png", np.uint8(lens_corr), params)
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cv2.imwrite("lens_corr.png", np.uint8(lens_corr*127.0), params)
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sys.exit()
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frame = np.ones((height, width, 3), np.float32)
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lens_corr = np.float32(cv2.imread("lens_corr.png"))
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lens_corr = np.float32(cv2.imread("lens_corr.png"))/140.0
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# loop over some frames...this time using the threaded stream
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while fps._numFrames < args["num_frames"]:
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# grab the frame from the threaded video stream
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if videoFile == "piCamera":
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frame8 = vs.read()[int(height/2):int(height/2+height), int(width/2):int(width/2)+width]
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frame = vs.read()
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else:
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ret, frame8 = vs.read()
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ret, frame = vs.read()
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if 0:
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frame32 = np.float32(frame8)
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print (frame.dtype)
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print (frame.shape)
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print (lens_corr.dtype)
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print (lens_corr.shape)
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for c in range (0, 3):
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frame32[:,:,c] = cv2.multiply(lens_corr[:,:,c], frame32[:,:,c], 1.0/255)
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frame = np.uint8(frame32)
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else:
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frame = frame8
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if args["use_calibration"] == 'on':
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frame = np.uint8(cv2.multiply(lens_corr, np.float32(frame)))
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kernel = np.ones((3,3),np.uint8)
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frame_dilated = cv2.dilate(frame,kernel,iterations = 1)
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@@ -284,7 +268,6 @@ while fps._numFrames < args["num_frames"]:
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print("Found " + str(numColorClasses) + " color classes")
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cv2.imshow('Raw',frame8)
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cv2.imshow('Corrected', frame)
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cv2.imshow('Contours', frame_dilated)
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cv2.imshow('Colors', img1_colors)
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