- improved

git-svn-id: http://moon:8086/svn/software/trunk/projects/opencv@323 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
2016-09-28 19:18:18 +00:00
parent 869ff43a45
commit 5434b0a16e
2 changed files with 177 additions and 167 deletions
+21 -12
View File
@@ -14,8 +14,24 @@ class PiVideoStream:
self.camera.exposure_mode = 'auto'
# self.camera.image_effect = 'colorbalance'
# self.camera.image_effect_params = (0,1,1,1,0,0)
self.camera.exposure_mode = 'auto'
self.camera.awb_mode = 'off'
self.camera.awb_gains = (1.5, 1.5)
# self.camera.analog_gain = 1.75
# self.camera.digital_gain = 1.00
self.rawCapture = PiRGBArray(self.camera, size=resolution)
self.stream = self.camera.capture_continuous(self.rawCapture,
format="bgr", use_video_port=True)
# initialize the frame and the variable used to indicate
# if the thread should be stopped
self.frame = None
self.stopped = False
self.fps = None
self.thread = None
self.startup = True
def printSettings(self):
awb_gains = self.camera.awb_gains
print ("sensor_mode : " + str(self.camera.sensor_mode))
print ("resolution : " + str(self.camera.resolution))
@@ -38,18 +54,6 @@ class PiVideoStream:
print ("image_effect_params : " + str(self.camera.image_effect_params))
print ("sharpness : " + str(self.camera.sharpness))
self.rawCapture = PiRGBArray(self.camera, size=resolution)
self.stream = self.camera.capture_continuous(self.rawCapture,
format="bgr", use_video_port=True)
# initialize the frame and the variable used to indicate
# if the thread should be stopped
self.frame = None
self.stopped = False
self.fps = None
self.thread = None
self.startup = True
def start(self):
# start the thread to read frames from the video stream
self.thread = Thread(target=self.update, args=())
@@ -59,6 +63,11 @@ class PiVideoStream:
def update(self):
# keep looping infinitely until the thread is stopped
for f in self.stream:
if self.camera.exposure_mode == 'auto':
if self.camera.analog_gain > 1.75 and self.camera.digital_gain == 1.0:
self.camera.exposure_mode = 'off'
self.printSettings()
if self.startup:
self.fps = FPS().start()
self.startup = False
+26 -25
View File
@@ -62,7 +62,8 @@ class FindObjects():
temp_objects = []
objectsCandIds = []
if hierachy is not None:
try:
if hierachy.any():
while count != -1:
family = FindObjects.getFamily([], count, hierachy)
@@ -111,6 +112,8 @@ class FindObjects():
self.meanThickness = int(abs(obj[0]['diameter'] - obj[1]['diameter'])/2)
objects.append({'thickness' : self.meanThickness, 'members' : obj})
except:
pass
return objects
@@ -175,15 +178,18 @@ if args["calibrate"] == 'on':
params.append(0)
cv2.imwrite("lens_corr.png", np.uint8(lens_corr*127.0), params)
cv2.imwrite("lens_shot.png", frame, params)
sys.exit()
fps.stop()
if videoFile == "piCamera":
vs.stop()
else:
frame = np.ones((height, width, 3), np.float32)
lens_corr = np.float32(cv2.imread("lens_corr.png"))/128.0
frame = np.ones((height, width, 3), np.float32)
lens_corr = np.float32(cv2.imread("lens_corr.png"))/140.0
# loop over some frames...this time using the threaded stream
while fps._numFrames < args["num_frames"]:
# 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":
@@ -203,9 +209,9 @@ while fps._numFrames < args["num_frames"]:
img1_canny = cv2.Canny(gray_blurred, 100, 50)
# Thresholding
# ret,img1_thr = cv2.threshold(gray_blurred,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
# img1_thr = cv2.adaptiveThreshold(gray_blurred,255,cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,11,2)
# img1_thr = cv2.adaptiveThreshold(gray_blurred,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
# ret,img1_thr = cv2.threshold(gray_blurred,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
# img1_thr = cv2.adaptiveThreshold(gray_blurred,255,cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY,11,2)
# img1_thr = cv2.adaptiveThreshold(gray_blurred,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
# Contours
(_, contours, hierachy) = cv2.findContours(img1_canny.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
@@ -214,7 +220,7 @@ while fps._numFrames < args["num_frames"]:
objects = findObjects.find(contours, hierachy)
# print (ids)
# print (ids)
img1_objects = frame.copy()
img1_colors = np.zeros((height,width,3), np.uint8)
@@ -240,7 +246,7 @@ 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]/255, mean_color[1]/255, mean_color[2]/255]})
# 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)
@@ -276,26 +282,24 @@ while fps._numFrames < args["num_frames"]:
if videoFile == "piCamera":
cv2.waitKey(1)
else:
# cv2.waitKey(0)
# cv2.waitKey(0)
cv2.waitKey(int(1000.0/framerate))
# update the FPS counter
fps.update()
# stop the timer and display FPS information
fps.stop()
if videoFile == "piCamera":
# stop the timer and display FPS information
fps.stop()
if videoFile == "piCamera":
vs.stop()
print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
if videoFile == "piCamera":
print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
if videoFile == "piCamera":
print("[INFO] Camera : elasped time: {:.2f}".format(vs.getfps().elapsed()))
print("[INFO] Camera: approx. FPS: {:.2f}".format(vs.getfps().fps()))
if numColorClasses:
# Output stats
findObjects.printStats()
@@ -318,7 +322,7 @@ if numColorClasses:
# Define criteria = ( type, max_iter, epsilon )
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.1)
ret,label,center=cv2.kmeans(np.float32(plotColors), numColorClasses, None, criteria, 10, cv2.KMEANS_PP_CENTERS)
ret,label,center=cv2.kmeans(Z,numColorClasses,None,criteria,10,cv2.KMEANS_PP_CENTERS)
print (center)
@@ -341,9 +345,6 @@ if numColorClasses:
plt.show()
else:
print("Sorry, no colors have been detected")
# do a bit of cleanup
cv2.destroyAllWindows()