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- improved camera calibration

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git-svn-id: http://moon:8086/svn/software/trunk/projects/opencv@320 b431acfa-c32f-4a4a-93f1-934dc6c82436
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jens
2016-09-20 17:17:37 +00:00
parent 3f284cdefd
commit 48674e65f3
1 changed files with 61 additions and 78 deletions
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beadDetect.py
+61 -78
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@@ -61,54 +61,56 @@ class FindObjects():
objects = [] objects = []
temp_objects = [] temp_objects = []
objectsCandIds = [] objectsCandIds = []
while count != -1:
family = FindObjects.getFamily([], count, hierachy) if hierachy.any():
while count != -1:
dupDict = {} family = FindObjects.getFamily([], count, hierachy)
members = []
for member in family:
x,y,w,h = cv2.boundingRect(contours[member]);
key = str([x,y,w,h]) + '.key'
if not key in dupDict:
dupDict[key] = member
members.append({ 'id' : member, 'bbox' : [x,y,w,h]})
objectsCandIds.append(members)
count = hierachy[0][count][0]
for family in objectsCandIds: dupDict = {}
obj = [] members = []
for member in family: for member in family:
area = cv2.contourArea(contours[member['id']]) x,y,w,h = cv2.boundingRect(contours[member]);
perimeter = cv2.arcLength(contours[member['id']], True) key = str([x,y,w,h]) + '.key'
pi = 3.14159265359 if not key in dupDict:
Q = 0 dupDict[key] = member
if (area > 10): members.append({ 'id' : member, 'bbox' : [x,y,w,h]})
Q = 4*pi*area/(perimeter*perimeter)
objectsCandIds.append(members)
if Q > 0.7:
diameter = max(member['bbox'][2], member['bbox'][3]) count = hierachy[0][count][0]
self.maxDiameter = max(self.maxDiameter, diameter)
self.minDiameter = min(self.minDiameter, diameter) for family in objectsCandIds:
member['diameter'] = diameter obj = []
member['pos'] = (int(member['bbox'][0] + member['bbox'][2]/2), int(member['bbox'][1] + member['bbox'][3]/2)) for member in family:
obj.append(member) area = cv2.contourArea(contours[member['id']])
perimeter = cv2.arcLength(contours[member['id']], True)
if obj: pi = 3.14159265359
temp_objects.append(obj) Q = 0
if (area > 10):
for obj in temp_objects: Q = 4*pi*area/(perimeter*perimeter)
for member in obj:
if member['diameter'] < self.innerOuterRatio*self.maxDiameter: if Q > 0.7:
member['isHole'] = True diameter = max(member['bbox'][2], member['bbox'][3])
else: self.maxDiameter = max(self.maxDiameter, diameter)
member['isHole'] = False self.minDiameter = min(self.minDiameter, diameter)
member['diameter'] = diameter
if len(obj) == 2: member['pos'] = (int(member['bbox'][0] + member['bbox'][2]/2), int(member['bbox'][1] + member['bbox'][3]/2))
self.meanThickness = int(abs(obj[0]['diameter'] - obj[1]['diameter'])/2) obj.append(member)
objects.append({'thickness' : self.meanThickness, 'members' : obj}) if obj:
temp_objects.append(obj)
for obj in temp_objects:
for member in obj:
if member['diameter'] < self.innerOuterRatio*self.maxDiameter:
member['isHole'] = True
else:
member['isHole'] = False
if len(obj) == 2:
self.meanThickness = int(abs(obj[0]['diameter'] - obj[1]['diameter'])/2)
objects.append({'thickness' : self.meanThickness, 'members' : obj})
return objects return objects
@@ -126,7 +128,9 @@ ap.add_argument("-r", "--framerate", type=int, default=30,
ap.add_argument("-f", "--filename", type=str, default='piCamera', ap.add_argument("-f", "--filename", type=str, default='piCamera',
help="Whether or not frames should be displayed") help="Whether or not frames should be displayed")
ap.add_argument("-c", "--calibrate", type=str, default='off', ap.add_argument("-c", "--calibrate", type=str, default='off',
help="Whether or not frames should be displayed") help="Whether calibration shall be performed")
ap.add_argument("-u", "--use-calibration", type=str, default='off',
help="Whether calibration shall be used")
args = vars(ap.parse_args()) args = vars(ap.parse_args())
videoFile = args["filename"] videoFile = args["filename"]
@@ -138,7 +142,7 @@ if videoFile == "piCamera":
from PiVideoStream import PiVideoStream from PiVideoStream import PiVideoStream
from picamera.array import PiRGBArray from picamera.array import PiRGBArray
from picamera import PiCamera from picamera import PiCamera
vs = PiVideoStream(resolution=(2*width,2*height), framerate=framerate).start() vs = PiVideoStream(resolution=(width,height), framerate=framerate).start()
time.sleep(5.0) time.sleep(5.0)
else: else:
vs = cv2.VideoCapture(videoFile) vs = cv2.VideoCapture(videoFile)
@@ -161,54 +165,34 @@ if args["calibrate"] == 'on':
ret, frame = vs.read() ret, frame = vs.read()
Z = np.float32(frame) Z = np.float32(frame)
print (frame.dtype) ref_color = cv2.mean(Z[int(height/2-8):int(height/2+8), int(width/2-8):int(width/2+8), :])
print (frame.shape)
print (lens_corr.dtype)
print (lens_corr.shape)
print (Z.dtype)
print (Z.shape)
ref_color = Z[height/2, width/2, :]
print (ref_color) print (ref_color)
for c in range (0, 3): lens_corr = cv2.divide(ref_color, Z)
lens_corr[:,:,c] = cv2.divide(ref_color[c], Z[:,:,c])
params = list() params = list()
params.append(cv2.IMWRITE_PNG_COMPRESSION) params.append(cv2.IMWRITE_PNG_COMPRESSION)
params.append(0) params.append(0)
for c in range (0, 3): cv2.imwrite("lens_corr.png", np.uint8(lens_corr*127.0), params)
lens_corr[:,:,c] = cv2.multiply(128, lens_corr[:,:,c])
cv2.imwrite("lens_corr.png", np.uint8(lens_corr), params)
sys.exit() sys.exit()
frame = np.ones((height, width, 3), np.float32) frame = np.ones((height, width, 3), np.float32)
lens_corr = np.float32(cv2.imread("lens_corr.png")) lens_corr = np.float32(cv2.imread("lens_corr.png"))/140.0
# loop over some frames...this time using the threaded stream # loop over some frames...this time using the threaded stream
while fps._numFrames < args["num_frames"]: while fps._numFrames < args["num_frames"]:
# grab the frame from the threaded video stream # grab the frame from the threaded video stream
if videoFile == "piCamera": if videoFile == "piCamera":
frame8 = vs.read()[int(height/2):int(height/2+height), int(width/2):int(width/2)+width] frame = vs.read()
else: else:
ret, frame8 = vs.read() ret, frame = vs.read()
if 0: if args["use_calibration"] == 'on':
frame32 = np.float32(frame8) frame = np.uint8(cv2.multiply(lens_corr, np.float32(frame)))
print (frame.dtype)
print (frame.shape)
print (lens_corr.dtype)
print (lens_corr.shape)
for c in range (0, 3):
frame32[:,:,c] = cv2.multiply(lens_corr[:,:,c], frame32[:,:,c], 1.0/255)
frame = np.uint8(frame32)
else:
frame = frame8
kernel = np.ones((3,3),np.uint8) kernel = np.ones((3,3),np.uint8)
frame_dilated = cv2.dilate(frame,kernel,iterations = 1) frame_dilated = cv2.dilate(frame,kernel,iterations = 1)
@@ -284,7 +268,6 @@ while fps._numFrames < args["num_frames"]:
print("Found " + str(numColorClasses) + " color classes") print("Found " + str(numColorClasses) + " color classes")
cv2.imshow('Raw',frame8)
cv2.imshow('Corrected', frame) cv2.imshow('Corrected', frame)
cv2.imshow('Contours', frame_dilated) cv2.imshow('Contours', frame_dilated)
cv2.imshow('Colors', img1_colors) cv2.imshow('Colors', img1_colors)