def callback(self, obst_list, image):
self.publisher_bblinelist.publish(
self.bbmarker) # since a single publish is likely to get lost
# print "CALLBACK HERE"
if (self.show_marker):
marker_list = self.visualizer.visualize_marker(obst_list)
self.publisher_marker.publish(marker_list)
# 4. EVENTUALLY DISPLAY IMAGE
if (self.show_image):
obst_image = CompressedImage()
obst_image.header.stamp = image.header.stamp
obst_image.format = "jpeg"
obst_image.data = self.visualizer.visualize_image(
rectify(rgb_from_ros(image), self.intrinsics), obst_list)
self.publisher_img.publish(obst_image.data)
def ProcessRawImage(self, img_raw):
# rectify image
img_undistorted = dt.rectify(dt.rgb_from_ros(img_raw), self.intrinsics)
# compute grayscale image
img_gray = cv2.cvtColor(img_undistorted, cv2.COLOR_RGB2GRAY)
# detect edges
img_canny = cv2.Canny(img_gray, self.canny_lower_threshold, self.canny_upper_threshold,
apertureSize=self.canny_aperture_size)
# apply mask
img_mask = cv2.bitwise_and(img_canny,self.mask_visible)
# pad image to avoid running into borders
img_processed = cv2.copyMakeBorder(img_mask, self.line_search_length, self.line_search_length,
self.line_search_length, self.line_search_length, cv2.BORDER_CONSTANT,
value=0)
return img_processed, img_gray
def callback(self, image):
if not self.active:
return
if not self.thread_lock.acquire(False):
return
#start = time.time()
obst_list = PoseArray()
marker_list = MarkerArray()
# pass RECTIFIED IMAGE TO DETECTOR MODULE
#1. EXTRACT OBSTACLES and return the pose array
obst_list = self.detector.process_image(
rectify(rgb_from_ros(image), self.intrinsics))
obst_list.header.stamp = image.header.stamp #for synchronization
#interessant um zu schauen ob stau oder nicht!!!!
#print image.header.stamp.to_sec()
self.publisher_arr.publish(obst_list)
#EXPLANATION: (x,y) is world coordinates of obstacle, z is radius of obstacle
#QUATERNION HAS NO MEANING!!!!
#3. VISUALIZE POSE ARRAY IN TF
if (self.show_marker):
marker_list = self.visualizer.visualize_marker(obst_list)
self.publisher_marker.publish(marker_list)
#4. EVENTUALLY DISPLAY !!!!CROPPED!!!!!! IMAGE
if (self.show_image):
obst_image = CompressedImage()
obst_image.header.stamp = image.header.stamp
obst_image.format = "jpeg"
obst_image.data = self.visualizer.visualize_image(
rectify(rgb_from_ros(image), self.intrinsics), obst_list)
#here i want to display cropped image
rgb_image = rgb_from_ros(obst_image.data)
obst_image.data = d8_compressed_image_from_cv_image(
rgb_image[self.detector.crop:, :, ::-1])
#THIS part only to visualize the cropped version -> somehow a little inefficient but keeps
#the visualizer.py modular!!!
self.publisher_img.publish(obst_image.data)
if (self.show_bird_perspective):
bird_perspective_image = CompressedImage()
bird_perspective_image.header.stamp = image.header.stamp
bird_perspective_image.format = "jpeg"
bird_perspective_image.data = self.visualizer.visualize_bird_perspective(
rectify(rgb_from_ros(image), self.intrinsics), obst_list)
#here i want to display cropped image
rgb_image = rgb_from_ros(obst_image.data)
obst_image.data = d8_compressed_image_from_cv_image(rgb_image)
#THIS part only to visualize the cropped version -> somehow a little inefficient but keeps
#the visualizer.py modular!!!
self.publisher_img_bird_perspective.publish(obst_image.data)
#end = time.time()
#print "OBST DETECTION TOOK: s"
#print(end - start)
self.r.sleep()
self.thread_lock.release()
#cv2.imwrite(dir+ '/' + str(i) + '.jpg',im1)
nummer = 1
while (True):
filename = im_path + '/' + str(nummer) + '.jpg'
im1 = cv2.imread(filename) #reads BGR
if (im1 is None):
#stop it!
break
else: #START MODIFYING THE IMAGE!!!
#-------------HERE GOES THE REAL CODE-----------------------------------------------------------
#-----------------------------------------------------------------------------------------------
obst_list = detector.process_image(rectify(im1[:, :, ::-1],
intrinsics))
obst_image = CompressedImage()
obst_image.format = "jpeg"
obst_image.data = visualizer.visualize_image(
rectify(im1[:, :, ::-1], intrinsics), obst_list)
#here i want to display cropped image
image = rgb_from_ros(obst_image.data)
image = image[crop:, :, :]
#THIS part only to visualize the cropped version -> somehow a little inefficient but keeps
#the visualizer.py modular!!!
#plt.imshow(image[detector.crop:,:,:]);plt.show() #the cropped image
#plt.imshow(image);plt.show() #normal sized image
#SAVE THE IMAGE
conv = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
cv2.imwrite(dir_path + '/' + str(nummer) + '.jpg', conv)
nummer += 1
def process_image(self, image):
return d8_compressed_image_from_cv_image(
rectify(image[..., ::-1], self.intrinsics)).data