def rider_reformat(path):
"""Combine riders' bboxes with the nearest motorcycle/bicycle"""
for filename in glob.iglob(path + '\**\*.json', recursive=True):
images = decode_annot_array(filename)
for i in range(0, len(images)):
image = images[i]
to_delete = []
for j in range(0, len(image.labels)):
label = image.labels[j]
if not (label.category == 'rider'):
continue
rider = label
nearest_idx = _find_nearest_cycle(image, label, to_delete)
if nearest_idx < 0:
continue
to_delete.append(nearest_idx)
cycle = image.labels[nearest_idx]
rider.box = _get_common_box(rider.box, cycle.box)
to_delete.sort(reverse=True)
for idx in to_delete:
del image.labels[idx]
encode_annot_array(images, filename, '_rider')
def common_category_names(path):
cat_dict = get_category_sets_dict()
for filename in glob.iglob(path + '\**\*.json', recursive=True):
images = decode_annot_array(filename)
for i in range(0, len(images)):
image = images[i]
for j in range(0, len(image.labels)):
label = image.labels[j]
common_category = cat_dict.get(frozenset(get_category_set(label.category)))
label.category = common_category
encode_annot_array(images, filename, '_common')
def load_folder(self, path, size_new):
images = []
print(path)
for filename in glob.iglob(path + '/**/*.json', recursive=True):
images_new = decode_annot_array(filename)
print(len(images_new))
# # resize bounding boxes
# print(path + ' ' + images_new[0].name)
# img = next(glob.iglob(path + '/**/' + images_new[0].name, recursive=True))
# height, width, _ = img.shape
# i# mages_new = self.resize_bboxes(images_new, (height, width), size_new)
images.extend(images_new)
return images
def crop_bbox_correction(path, x_offset):
for filename in glob.iglob(path + '/**/*.json', recursive=True):
print(filename)
images = decode_annot_array(filename)
for i in range(0, len(images)):
image = images[i]
print(image.name)
for j in range(0, len(image.labels)):
box = image.labels[j].box
box.x1 -= x_offset
box.x2 -= x_offset
encode_annot_array(images, filename)
def cityscapes_citypersons_union(path):
subfolders = ['both', 'train', 'val']
for subfolder in subfolders:
sub_path = os.path.join(path, subfolder)
images_both = []
for filename in glob.iglob(sub_path + '\**\*.json', recursive=True):
images_both.append(decode_annot_array(filename))
images_first = {}
for image in images_both[0]:
images_first.update({image.name: image})
for i in range(0, len(images_both[1])):
images_both[1][i].labels.extend(images_first.get(images_both[1][i].name).labels)
encode_annot_array(images_both[1], os.path.join(sub_path, 'cs_2.json'))
def crop_dataset(path, x_offset, width, height, only_json=False):
images_path = os.path.join(path, "images")
if not only_json:
for filename in glob.iglob(images_path + '/**/*.png', recursive=True):
print(filename)
img = cv2.imread(filename)
crop_img = img[0:height, x_offset:x_offset + width]
splitted = os.path.splitext(filename)
cv2.imwrite(splitted[0] + '_cropped' + splitted[1], crop_img)
for filename in glob.iglob(path + '/**/*.json', recursive=True):
print(filename)
images = decode_annot_array(filename)
for i in range(0, len(images)):
image = images[i]
print(image.name)
to_delete = []
for j in range(0, len(image.labels)):
box = image.labels[j].box
if (float(box.x1) < x_offset and float(box.x2) < x_offset) or (float(box.x1) > x_offset + width and float(box.x2) > x_offset + width):
to_delete.append(j)
continue
box.x1 = max(x_offset, float(box.x1))
box.x2 = max(x_offset, float(box.x2))
box.x1 = min(x_offset + width, float(box.x1))
box.x2 = min(x_offset + width, float(box.x2))
box.y1 = min(height, float(box.y1))
box.y2 = min(height, float(box.y2))
to_delete.sort(reverse=True)
for idx in to_delete:
del image.labels[idx]
encode_annot_array(images, filename)
def keep_only_needed_categories(path, categories):
cats = set([])
for category in categories:
print(category)
cats = cats.union(get_category_set(category))
for filename in glob.iglob(path + '\**\*.json', recursive=True):
images = decode_annot_array(filename)
for i in range(0, len(images)):
image = images[i]
labels_to_delete = []
for j in range(0, len(image.labels)):
label = image.labels[j]
if not (label.category in cats):
labels_to_delete.append(j)
labels_to_delete.sort(reverse=True)
for idx in labels_to_delete:
del image.labels[idx]
encode_annot_array(images, filename, '_needed')
def keep_only_images_w_categories(path):
"""Remove images where there were no trains/trams annotated"""
for filename in glob.iglob(path + '/**/*.json', recursive=True):
categories = [['person', 'person_group'], ['two_wheeler'], ['on_rails'], ['car'], ['truck']]
for cat in categories:
cats = set([])
for category in cat:
print(category)
cats = cats.union(get_category_set(category))
images = decode_annot_array(filename)
images_w_cats = []
for image in images:
for label in image.labels:
if label.category in cats:
images_w_cats.append(image)
break
postfix = ''
for category in cat:
postfix += '_' + category
encode_annot_array(images_w_cats, filename, postfix)