def _remove_small_objects(self, items):
filtered_item = []
for item in items:
m = np.array(Image.open(item['mask_path']))
if util.change_coordinates(m, 8.0, 0.0).sum() > 2: ##相当于对mask进行下采样到32倍，下采样后的大小变为(13, 17)，然后判断下采样的图片的像素值之和是否大于2
filtered_item.append(item) # 将大于2的图片放入filtered_item中,删掉小的图片
return filtered_item # 365个
def _remove_small_objects(self, items):
filtered_item = []
for item in items:
mask = item.read_mask()
if util.change_coordinates(mask, 32.0, 0.0).sum() > 2:
filtered_item.append(item)
return filtered_item
def _remove_small_objects(self, items):
filtered_item = []
for item in items:
mask = item.read_mask() #(366, 500)
if util.change_coordinates(mask, 32.0, 0.0).sum(
) > 2: ##相当于对mask进行下采样到32倍，下采样后的大小变为(13, 17)，然后判断下采样的图片的像素值之和是否大于2
filtered_item.append(item) #将大于2的图片放入filtered_item中,删掉小的图片
return filtered_item #365个
def _remove_small_objects(self, items):
'''
移除一些目标较小的目标
:param items: 以DBPascalItem为数据格式list
:return: 移除小目标后的list, 元素任然是DBPascalItem
'''
filtered_item = []
for item in items:
mask = item.read_mask()
if util.change_coordinates(mask, 32.0, 0.0).sum() > 2:
filtered_item.append(item)
return filtered_item
def load_frame(self, player, first_index, second_index):
cprint(
'Loading pair = ' + player.name + ', ' + str(first_index) + ', ' +
str(second_index), bcolors.WARNING)
if second_index in first_index:
return None
images1 = []
labels1 = []
image_path = []
shape1 = self.first_shape
for ind in first_index:
frame1_dict = player.get_frame(ind)
image1, label1, shape1 = self.__prepross(frame1_dict, shape1)
images1.append(image1.transpose((2, 0, 1)))
labels1.append(label1)
image_path.append(frame1_dict['image_path'])
item = dict(first_img=images1, image1_path=image_path)
if second_index is not None:
frame2_dict = player.get_frame(second_index)
image2, label2, shape = self.__prepross(frame2_dict,
self.second_shape)
item['second_img'] = [image2.transpose((2, 0, 1))]
item['image2_path'] = [
frame2_dict['image_path'],
]
if self.deploy_mode:
first_semantic_labels = []
first_mask_orig = []
first_img_orig = []
for ind in first_index:
a, b, c = self.__get_deploy_info(player, ind)
first_semantic_labels.append(a)
first_mask_orig.append(b)
first_img_orig.append(c)
deploy_info = dict(seq_name=player.name,
first_index=first_index,
first_img_orig=first_img_orig,
first_mask_orig=first_mask_orig,
first_semantic_labels=first_semantic_labels)
if second_index is not None:
second_semantic_labels, second_mask_orig, second_img_orig = self.__get_deploy_info(
player, second_index)
deploy_info.update(
second_index=second_index,
second_img_orig=second_img_orig,
second_mask_orig=second_mask_orig,
second_semantic_labels=second_semantic_labels)
item['deploy_info'] = deploy_info
#create first_labels
for i in range(len(self.first_label_params)):
name, down_scale, offset = self.first_label_params[i]
item[name] = []
for label1 in labels1:
nlabel1 = util.change_coordinates(label1, down_scale, offset)
nlabel1 = (nlabel1 -
self.first_label_mean) * self.first_label_scale
assert (self.__is_integer(nlabel1))
item[name].append(nlabel1.reshape((1, ) + nlabel1.shape))
if second_index is not None:
#create second_labels
for i in range(len(self.second_label_params)):
name, down_scale, offset = self.second_label_params[i]
nlabel2 = util.change_coordinates(label2, down_scale, offset)
assert (self.__is_integer(nlabel2))
item[name] = [nlabel2.reshape((1, ) + nlabel2.shape)]
if self.has_cont:
item['cont'] = [0] + [1] * (len(first_index) - 1)
return item
def load_frame(self, player1, player2, first_index_1, first_index_2,
second_index):
# cprint('Loading pair = ' + player.name + ', ' + str(first_index) + ', ' + str(second_index), bcolors.WARNING)
# if second_index in first_index:
# return None
images1 = []
labels1 = []
image_path_1 = []
images2 = []
labels2 = []
image_path_2 = []
shape1 = self.first_shape
for ind1, ind2 in zip(first_index_1, first_index_2):
frame1_dict_1 = player1.get_frame(ind1)
frame1_dict_2 = player2.get_frame(ind2)
image1, label1, shape1 = self.__prepross(frame1_dict_1, shape1)
image2, label2, shape1 = self.__prepross(frame1_dict_2, shape1)
images1.append(image1.transpose((2, 0, 1)))
images2.append(image2.transpose((2, 0, 1)))
labels1.append(label1)
labels2.append(label2)
image_path_1.append(frame1_dict_1['image_path'])
image_path_2.append(frame1_dict_2['image_path'])
item = dict(first_img=[images1, images2],
image1_path=[image_path_1, image_path_2])
if second_index is not None:
frame2_dict = player1.get_frame(second_index)
image_q, label_q, shape = self.__prepross(frame2_dict,
self.second_shape)
item['second_img'] = [image_q.transpose((2, 0, 1))]
item['image2_path'] = [
frame2_dict['image_path'],
]
if self.deploy_mode:
# first_semantic_labels=[]
# first_mask_orig=[]
# first_img_orig=[]
# for ind in first_index:
# a,b,c = self.__get_deploy_info(player, ind)
# first_semantic_labels.append(a)
# first_mask_orig.append(b)
# first_img_orig.append(c)
#
# deploy_info = dict(seq_name=player.name,
# first_index=first_index,
# first_img_orig=first_img_orig,
# first_mask_orig=first_mask_orig,
# first_semantic_labels=first_semantic_labels)
deploy_info = {}
if second_index is not None:
second_semantic_labels, second_mask_orig, second_img_orig = self.__get_deploy_info(
player1, second_index)
deploy_info.update(
second_index=second_index,
second_img_orig=second_img_orig,
second_mask_orig=second_mask_orig,
second_semantic_labels=second_semantic_labels)
item['deploy_info'] = deploy_info
# create first_labels
for i in range(len(self.first_label_params)):
name, down_scale, offset = self.first_label_params[i]
item[name] = []
class_one = []
class_two = []
for label1 in labels1:
nlabel1 = util.change_coordinates(label1, down_scale, offset)
nlabel1 = (nlabel1 -
self.first_label_mean) * self.first_label_scale
class_one.append(nlabel1.reshape((1, ) + nlabel1.shape))
item[name].append(class_one)
for label2 in labels2:
assert (self.__is_integer(nlabel1))
nlabel2 = util.change_coordinates(label2, down_scale, offset)
nlabel2 = (nlabel2 -
self.first_label_mean) * self.first_label_scale
assert (self.__is_integer(nlabel2))
class_two.append(nlabel2.reshape((1, ) + nlabel2.shape))
item[name].append(class_two)
if second_index is not None:
# create second_labels
for i in range(len(self.second_label_params)):
name, down_scale, offset = self.second_label_params[i]
nlabel_q = util.change_coordinates(label_q, down_scale, offset)
assert (self.__is_integer(nlabel_q))
item[name] = [nlabel_q.reshape((1, ) + nlabel_q.shape)]
# if self.has_cont:
# item['cont'] = [0] + [1] * (len(first_index) - 1)
return item
