def _parse_keypoints_skeleton(self, image_filename):
keypoints, skeleton = [], []
if self.anno_type == 'keypoints':
img_id = dataset_util.get_image_id(image_filename)
mask_file = self.get_src_label_filepath(img_id)
mask_anno = JsonParserIO.from_file(mask_file)
keypoints, skeleton = mask_anno.keypoints, mask_anno.skeleton
return keypoints, skeleton
def generate_labels(self, image_list, label_intervals):
logging.info('generate segmentation ...')
label_list = []
mode = 'SegmentationClassAug'
for srcfile in tqdm(
image_list[label_intervals[mode][0]:label_intervals[mode][1]]):
img_id = dataset_util.get_image_id(srcfile)
self._gen_seg_obj(img_id, label_list)
mode = 'SegmentationClass'
for srcfile in tqdm(
image_list[label_intervals[mode][0]:label_intervals[mode][1]]):
img_id = dataset_util.get_image_id(srcfile)
self._gen_mask_image_with_palette(img_id)
logging.info('label list {0}'.format(label_list))
dataset_util.write_label_id_color_file(label_list,
self.paths['output'])
def _build_label_infos(self, image_list, intervals):
label_list = []
keypoints, skeleton = self._parse_keypoints_skeleton(image_list[0])
for mode in self.label_modes:
for i in tqdm(range(intervals[mode][0], intervals[mode][1])):
img_id = dataset_util.get_image_id(image_list[i])
self._parse_single_label_file(img_id, mode, label_list,
keypoints, skeleton)
return label_list, keypoints, skeleton
def _copy_images_per_mode(self, src_path, images_sublist, mode, dest_path):
for srcfile in tqdm(images_sublist):
img_id = dataset_util.get_image_id(srcfile)
img_in = cv2.imread(os.path.join(src_path, srcfile))
if img_in is None:
print('Failed to read image file', srcfile)
continue
new_name = self.get_dest_mode_filename(mode, img_id)
area = dataset_util.get_area(img_in.shape, *self.get_image_size())
dataset_util.copy_image(area, img_in,
os.path.join(dest_path, new_name),
self.background_color)
def generate_labels(self, image_list, label_intervals):
print('generate labels ...')
label_list = []
for image_mode in self.image_modes:
for i in range(label_intervals[image_mode][0],
label_intervals[image_mode][1]):
img_id = dataset_util.get_image_id(image_list[i])
label_mode = image_mode.replace(self.image_folder,
self.label_folder)
self.generate_labels_per_mode(label_mode, img_id, label_list)
dataset_util.write_label_id_color_file(label_list,
self.get_root_path())
print('cityscape format done')
def _copy_depth_per_mode(self, src_path, images_sublist, mode, dest_path):
for srcfile in tqdm(images_sublist):
img_id = dataset_util.get_image_id(srcfile)
depth_srcfile = dataset_util.get_same_name_file(src_path, srcfile)
img_in = cv2.imread(os.path.join(src_path, depth_srcfile),
cv2.IMREAD_UNCHANGED)
if img_in is None:
print('Failed to read depth file', srcfile)
continue
new_name = self.get_dest_mode_filename(
mode, img_id, suffix=os.path.splitext(depth_srcfile)[1])
area = dataset_util.get_area(img_in.shape, *self.get_image_size())
dataset_util.copy_image(area, img_in,
os.path.join(dest_path, new_name),
self.background_color)
def write_file_list(self, image_list, split_intervals):
for image_mode in self.image_modes:
images_sublist = image_list[
split_intervals[image_mode][0]:split_intervals[image_mode][1]]
imglist_file_lines = []
for srcfile in images_sublist:
img_id = dataset_util.get_image_id(srcfile)
origin_img_path = self.get_cs_relative_image_path(
image_mode, img_id)
label_mode = image_mode.replace(self.image_folder,
self.label_folder)
gtFine_img_path = self.get_cs_relative_gtFine_mask_path(
label_mode, img_id)
imglist_single_line = str(
self._images_num
) + '\t' + origin_img_path + '\t' + gtFine_img_path + '\n'
imglist_file_lines.append(imglist_single_line)
self._images_num += 1
split_mode = image_mode.replace(self.image_folder,
self.split_folder)
with open(self.get_cs_imglist_filepath(split_mode), 'w') as f_lst:
f_lst.writelines(imglist_file_lines)
def _build_image_infos(self, image_list, intervals):
for split_type in self.label_modes:
for i in range(intervals[split_type][0], intervals[split_type][1]):
img_id = dataset_util.get_image_id(image_list[i])
image_msg = self._set_image_msg(img_id, split_type)
self._images[split_type].append(image_msg)