def _create_train_test(self, force_augmentation, kwargs):
slide_window_params = {
'displace': kwargs['displace'],
'size_x': kwargs['size_x'],
'size_y': kwargs['size_y'],
'people_thr': kwargs['people_thr']
}
noise_params = {'augment_noise': kwargs['augment_noise']}
light_params = {
'augment_light': kwargs['augment_light'],
'bright': kwargs['bright'],
'contrast': kwargs['contrast']
}
#shanghaiTech part A
self.augmented_dir_partA = osp.join(self.ori_dir_partA,
self.signature())
augment_data_A = False
if osp.exists(self.augmented_dir_partA):
print("'{}' already exists".format(self.augmented_dir_partA))
if force_augmentation:
augment_data_A = True
print("augmenting data anyway")
else:
augment_data_A = False
print("will not augmenting data")
else:
augment_data_A = True
os.makedirs(self.augmented_dir_partA)
aug_dir_partA_img = osp.join(self.augmented_dir_partA, "train_img")
aug_dir_partA_den = osp.join(self.augmented_dir_partA, "train_den")
aug_dir_partA_lab = osp.join(self.augmented_dir_partA, "train_lab")
test_dir_partA_img = osp.join(self.augmented_dir_partA, 'test_img')
test_dir_partA_den = osp.join(self.augmented_dir_partA, 'test_den')
test_dir_partA_lab = osp.join(self.augmented_dir_partA, 'test_lab')
mkdir_if_missing(aug_dir_partA_img)
mkdir_if_missing(aug_dir_partA_den)
mkdir_if_missing(aug_dir_partA_lab)
mkdir_if_missing(test_dir_partA_img)
mkdir_if_missing(test_dir_partA_den)
mkdir_if_missing(test_dir_partA_lab)
kwargs['name'] = 'shanghai-partA'
part_A_train_test = train_test_unit(aug_dir_partA_img,
aug_dir_partA_den,
test_dir_partA_img,
test_dir_partA_den, kwargs.copy())
self.train_test_set.append(part_A_train_test)
if augment_data_A:
ori_img_paths = [
osp.join(self.ori_dir_partA_train_img, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partA_train_img))
]
ori_lab_paths = [
osp.join(self.ori_dir_partA_train_lab, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partA_train_lab))
]
ori_den_paths = [
osp.join(self.ori_dir_partA_train_den, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partA_train_den))
]
augment(ori_img_paths, ori_lab_paths, ori_den_paths,
aug_dir_partA_img, aug_dir_partA_lab, aug_dir_partA_den,
slide_window_params, noise_params, light_params)
test_img_paths = [
osp.join(self.ori_dir_partA_test_img,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partA_test_img))
]
test_lab_paths = [
osp.join(self.ori_dir_partA_test_lab,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partA_test_lab))
]
test_den_paths = [
osp.join(self.ori_dir_partA_test_den,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partA_test_den))
]
copy_to_directory(test_img_paths, test_dir_partA_img)
copy_to_directory(test_lab_paths, test_dir_partA_lab)
copy_to_directory(test_den_paths, test_dir_partA_den)
#shanghaiTech part B
self.augmented_dir_partB = osp.join(self.ori_dir_partB,
self.signature())
augment_data_B = False
if osp.exists(self.augmented_dir_partB):
print("'{}' already exists".format(self.augmented_dir_partB))
if force_augmentation:
augment_data_B = True
print("augmenting data anyway")
else:
augment_data_B = False
print("will not augmenting data")
else:
augment_data_B = True
os.makedirs(self.augmented_dir_partB)
aug_dir_partB_img = osp.join(self.augmented_dir_partB, "train_img")
aug_dir_partB_den = osp.join(self.augmented_dir_partB, "train_den")
aug_dir_partB_lab = osp.join(self.augmented_dir_partB, "train_lab")
test_dir_partB_img = osp.join(self.augmented_dir_partB, 'test_img')
test_dir_partB_den = osp.join(self.augmented_dir_partB, 'test_den')
test_dir_partB_lab = osp.join(self.augmented_dir_partB, 'test_lab')
mkdir_if_missing(aug_dir_partB_img)
mkdir_if_missing(aug_dir_partB_den)
mkdir_if_missing(aug_dir_partB_lab)
mkdir_if_missing(test_dir_partB_img)
mkdir_if_missing(test_dir_partB_den)
mkdir_if_missing(test_dir_partB_lab)
kwargs['name'] = 'shanghai-partB'
part_B_train_test = train_test_unit(aug_dir_partB_img,
aug_dir_partB_den,
test_dir_partB_img,
test_dir_partB_den, kwargs.copy())
self.train_test_set.append(part_B_train_test)
if augment_data_B:
ori_img_paths = [
osp.join(self.ori_dir_partB_train_img, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partB_train_img))
]
ori_lab_paths = [
osp.join(self.ori_dir_partB_train_lab, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partB_train_lab))
]
ori_den_paths = [
osp.join(self.ori_dir_partB_train_den, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partB_train_den))
]
augment(ori_img_paths, ori_lab_paths, ori_den_paths,
aug_dir_partB_img, aug_dir_partB_lab, aug_dir_partB_den,
slide_window_params, noise_params, light_params)
test_img_paths = [
osp.join(self.ori_dir_partB_test_img,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partB_test_img))
]
test_lab_paths = [
osp.join(self.ori_dir_partB_test_lab,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partB_test_lab))
]
test_den_paths = [
osp.join(self.ori_dir_partB_test_den,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partB_test_den))
]
copy_to_directory(test_img_paths, test_dir_partB_img)
copy_to_directory(test_lab_paths, test_dir_partB_lab)
copy_to_directory(test_den_paths, test_dir_partB_den)
def _create_train_test(self, force_augmentation, **kwargs):
slide_window_params = {
'displace': kwargs['displace'],
'size_x': kwargs['size_x'],
'size_y': kwargs['size_y'],
'people_thr': kwargs['people_thr']
}
noise_params = {'augment_noise': kwargs['augment_noise']}
light_params = {
'augment_light': kwargs['augment_light'],
'bright': kwargs['bright'],
'contrast': kwargs['contrast']
}
self.augmented_dir = osp.join(self.root, self.signature())
# check if augmented data exists
augment_data = False
if osp.exists(self.augmented_dir):
print("'{}' already exists".format(self.augmented_dir))
if force_augmentation:
augment_data = True
print("augmenting data anyway, since force_augmentantion=True")
else:
augment_data = False
print("skipping augmentation, since force_augmentantion=False")
else:
augment_data = True
os.makedirs(self.augmented_dir)
#create new directories for augmentations
aug_dir_train_img = osp.join(self.augmented_dir, "train_img")
aug_dir_train_den = osp.join(self.augmented_dir, "train_den")
aug_dir_train_lab = osp.join(self.augmented_dir, "train_lab")
test_dir_img = osp.join(self.augmented_dir, "test_img")
test_dir_den = osp.join(self.augmented_dir, "test_den")
test_dir_lab = osp.join(self.augmented_dir, "test_lab")
val_dir_img = osp.join(self.augmented_dir, "val_img")
val_dir_den = osp.join(self.augmented_dir, "val_den")
val_dir_lab = osp.join(self.augmented_dir, "val_lab")
mkdir_if_missing(aug_dir_train_img)
mkdir_if_missing(aug_dir_train_den)
mkdir_if_missing(aug_dir_train_lab)
mkdir_if_missing(test_dir_img)
mkdir_if_missing(test_dir_den)
mkdir_if_missing(test_dir_lab)
mkdir_if_missing(val_dir_img)
mkdir_if_missing(val_dir_den)
mkdir_if_missing(val_dir_lab)
kwargs['name'] = 'jhu_crowd'
kwargs["val"] = True
kwargs["val_dir_img"] = val_dir_img
kwargs["val_dir_den"] = val_dir_den
train_test = train_test_unit(aug_dir_train_img, aug_dir_train_den,
test_dir_img, test_dir_den, kwargs.copy())
if augment_data and not (kwargs["skip_dir_check"]):
ori_img_paths = [
osp.join(self.ori_train_img, file_name)
for file_name in sorted(os.listdir(self.ori_train_img))
]
ori_lab_paths = [
osp.join(self.ori_train_lab, file_name)
for file_name in sorted(os.listdir(self.ori_train_lab))
]
ori_den_paths = [
osp.join(self.ori_train_den, file_name)
for file_name in sorted(os.listdir(self.ori_train_den))
]
augment(ori_img_paths, ori_lab_paths, ori_den_paths,
aug_dir_train_img, aug_dir_train_lab, aug_dir_train_den,
slide_window_params, noise_params, light_params)
test_img_paths = [
osp.join(self.ori_test_img, file_name)
for file_name in sorted(os.listdir(self.ori_test_img))
]
test_lab_paths = [
osp.join(self.ori_test_lab, file_name)
for file_name in sorted(os.listdir(self.ori_test_lab))
]
test_den_paths = [
osp.join(self.ori_test_den, file_name)
for file_name in sorted(os.listdir(self.ori_test_den))
]
copy_to_directory(test_img_paths, test_dir_img)
copy_to_directory(test_lab_paths, test_dir_lab)
copy_to_directory(test_den_paths, test_dir_den)
val_img_paths = [
osp.join(self.ori_val_img, file_name)
for file_name in sorted(os.listdir(self.ori_val_img))
]
val_lab_paths = [
osp.join(self.ori_val_lab, file_name)
for file_name in sorted(os.listdir(self.ori_val_lab))
]
val_den_paths = [
osp.join(self.ori_val_den, file_name)
for file_name in sorted(os.listdir(self.ori_val_den))
]
copy_to_directory(val_img_paths, val_dir_img)
copy_to_directory(val_lab_paths, val_dir_lab)
copy_to_directory(val_den_paths, val_dir_den)
self.train_test_set.append(train_test)
def _create_train_test(self, force_augmentation, kwargs):
slide_window_params = {
'displace': kwargs['displace'],
'size_x': kwargs['size_x'],
'size_y': kwargs['size_y'],
'people_thr': kwargs['people_thr']
}
noise_params = {'augment_noise': kwargs['augment_noise']}
light_params = {
'augment_light': kwargs['augment_light'],
'bright': kwargs['bright'],
'contrast': kwargs['contrast']
}
file_names = os.listdir(self.ori_dir_img)
file_names.sort()
img_names = []
img_ids = []
for file_name in file_names:
file_extention = file_name.split('.')[-1]
file_id = file_name[:len(file_name) - len(file_extention)]
if file_extention != 'png' and file_extention != 'jpg':
continue
img_names.append(file_name)
img_ids.append(file_id)
if len(img_names) != 50:
raise RuntimeError(
"UCF_CC_50 dataset expects 50 images, {} found".format(
len(img_names)))
self.augmented_dir = osp.join(self.root, self.signature())
augment_data = False
if osp.exists(self.augmented_dir):
print("'{}' already exists".format(self.augmented_dir))
if force_augmentation:
augment_data = True
print("augmenting data anyway")
else:
augment_data = False
print("will not augmenting data")
else:
augment_data = True
os.makedirs(self.augmented_dir)
#using 5 fold cross validation protocol
for fold in range(5):
fold_dir = osp.join(self.augmented_dir, 'fold{}'.format(fold + 1))
aug_train_dir_img = osp.join(fold_dir, 'train_img')
aug_train_dir_den = osp.join(fold_dir, 'train_den')
aug_train_dir_lab = osp.join(fold_dir, 'train_lab')
fold_test_dir_img = osp.join(fold_dir, 'test_img')
fold_test_dir_den = osp.join(fold_dir, 'test_den')
fold_test_dir_lab = osp.join(fold_dir, 'test_lab')
mkdir_if_missing(aug_train_dir_img)
mkdir_if_missing(aug_train_dir_den)
mkdir_if_missing(aug_train_dir_lab)
mkdir_if_missing(fold_test_dir_img)
mkdir_if_missing(fold_test_dir_den)
mkdir_if_missing(fold_test_dir_lab)
kwargs['name'] = 'ucf-fold{}'.format(fold + 1)
train_test = train_test_unit(aug_train_dir_img, aug_train_dir_den,
fold_test_dir_img, fold_test_dir_den,
kwargs.copy())
self.train_test_set.append(train_test)
if augment_data:
test_img = img_names[fold * 10:(fold + 1) * 10]
test_ids = img_ids[fold * 10:(fold + 1) * 10]
test_den_paths = [
osp.join(self.ori_dir_den, img_id + 'npy')
for img_id in test_ids
]
test_lab_paths = [
osp.join(self.ori_dir_lab, img_id + 'json')
for img_id in test_ids
]
test_img_paths = [
osp.join(self.ori_dir_img, img) for img in test_img
]
train_img = sorted(list(set(img_names) - set(test_img)))
train_ids = sorted(list(set(img_ids) - set(test_ids)))
train_den_paths = [
osp.join(self.ori_dir_den, img_id + 'npy')
for img_id in train_ids
]
train_lab_paths = [
osp.join(self.ori_dir_lab, img_id + 'json')
for img_id in train_ids
]
train_img_paths = [
osp.join(self.ori_dir_img, img) for img in train_img
]
#augment train data
print("Augmenting {}".format(kwargs['name']))
augment(train_img_paths, train_lab_paths, train_den_paths,
aug_train_dir_img, aug_train_dir_lab,
aug_train_dir_den, slide_window_params, noise_params,
light_params)
copy_to_directory(test_den_paths, fold_test_dir_den)
copy_to_directory(test_lab_paths, fold_test_dir_lab)
copy_to_directory(test_img_paths, fold_test_dir_img)
def _create_train_test(self, force_augmentation, kwargs):
slide_window_params = {
'displace': kwargs['displace'],
'size_x': kwargs['size_x'],
'size_y': kwargs['size_y'],
'people_thr': kwargs['people_thr']
}
noise_params = {'augment_noise': kwargs['augment_noise']}
light_params = {
'augment_light': kwargs['augment_light'],
'bright': kwargs['bright'],
'contrast': kwargs['contrast']
}
downscale = kwargs['downscale']
ten_crop = kwargs['ten_crop_mode']
if downscale and ten_crop:
raise Exception(
'five crop and dowscale mode cannot be used at the same time, choose one.'
)
#shanghaiTech part A
self.augmented_dir_partA = osp.join(self.ori_dir_partA,
self.signature())
augment_data_A = False
if osp.exists(self.augmented_dir_partA):
print("'{}' already exists".format(self.augmented_dir_partA))
if force_augmentation:
augment_data_A = True
print("augmenting data anyway")
else:
augment_data_A = False
print("will not augmenting data")
else:
augment_data_A = True
os.makedirs(self.augmented_dir_partA)
aug_dir_partA_img = osp.join(self.augmented_dir_partA, "train_img")
aug_dir_partA_den = osp.join(self.augmented_dir_partA, "train_den")
aug_dir_partA_lab = osp.join(self.augmented_dir_partA, "train_lab")
test_dir_partA_img = osp.join(self.augmented_dir_partA, 'test_img')
test_dir_partA_den = osp.join(self.augmented_dir_partA, 'test_den')
test_dir_partA_lab = osp.join(self.augmented_dir_partA, 'test_lab')
mkdir_if_missing(aug_dir_partA_img)
mkdir_if_missing(aug_dir_partA_den)
mkdir_if_missing(aug_dir_partA_lab)
mkdir_if_missing(test_dir_partA_img)
mkdir_if_missing(test_dir_partA_den)
mkdir_if_missing(test_dir_partA_lab)
kwargs['name'] = 'shanghai-partA'
kwargs["val"] = False
part_A_train_test = train_test_unit(aug_dir_partA_img,
aug_dir_partA_den,
test_dir_partA_img,
test_dir_partA_den, kwargs.copy())
self.train_test_set.append(part_A_train_test)
if augment_data_A:
ori_img_paths = [
osp.join(self.ori_dir_partA_train_img, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partA_train_img))
]
ori_lab_paths = [
osp.join(self.ori_dir_partA_train_lab, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partA_train_lab))
]
ori_den_paths = [
osp.join(self.ori_dir_partA_train_den, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partA_train_den))
]
augment(ori_img_paths,
ori_lab_paths,
ori_den_paths,
aug_dir_partA_img,
aug_dir_partA_lab,
aug_dir_partA_den,
slide_window_params,
noise_params,
light_params,
downscale_img=downscale,
ten_crop=ten_crop)
test_img_paths = [
osp.join(self.ori_dir_partA_test_img,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partA_test_img))
]
test_lab_paths = [
osp.join(self.ori_dir_partA_test_lab,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partA_test_lab))
]
test_den_paths = [
osp.join(self.ori_dir_partA_test_den,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partA_test_den))
]
if downscale:
downscale_test_images(test_img_paths, test_dir_partA_img,
test_lab_paths, test_dir_partA_lab,
test_den_paths, test_dir_partA_den,
slide_window_params['size_x'],
slide_window_params['size_y'])
elif ten_crop:
resize_test_img_ten_crop_mode(
test_img_paths, test_dir_partA_img, test_lab_paths,
test_dir_partA_lab, test_den_paths, test_dir_partA_den)
else:
copy_to_directory(test_img_paths, test_dir_partA_img)
copy_to_directory(test_lab_paths, test_dir_partA_lab)
copy_to_directory(test_den_paths, test_dir_partA_den)
#shanghaiTech part B
self.augmented_dir_partB = osp.join(self.ori_dir_partB,
self.signature())
augment_data_B = False
if osp.exists(self.augmented_dir_partB):
print("'{}' already exists".format(self.augmented_dir_partB))
if force_augmentation:
augment_data_B = True
print("augmenting data anyway")
else:
augment_data_B = False
print("will not augmenting data")
else:
augment_data_B = True
os.makedirs(self.augmented_dir_partB)
aug_dir_partB_img = osp.join(self.augmented_dir_partB, "train_img")
aug_dir_partB_den = osp.join(self.augmented_dir_partB, "train_den")
aug_dir_partB_lab = osp.join(self.augmented_dir_partB, "train_lab")
test_dir_partB_img = osp.join(self.augmented_dir_partB, 'test_img')
test_dir_partB_den = osp.join(self.augmented_dir_partB, 'test_den')
test_dir_partB_lab = osp.join(self.augmented_dir_partB, 'test_lab')
mkdir_if_missing(aug_dir_partB_img)
mkdir_if_missing(aug_dir_partB_den)
mkdir_if_missing(aug_dir_partB_lab)
mkdir_if_missing(test_dir_partB_img)
mkdir_if_missing(test_dir_partB_den)
mkdir_if_missing(test_dir_partB_lab)
kwargs['name'] = 'shanghai-partB'
kwargs["val"] = False
part_B_train_test = train_test_unit(aug_dir_partB_img,
aug_dir_partB_den,
test_dir_partB_img,
test_dir_partB_den, kwargs.copy())
self.train_test_set.append(part_B_train_test)
if augment_data_B:
ori_img_paths = [
osp.join(self.ori_dir_partB_train_img, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partB_train_img))
]
ori_lab_paths = [
osp.join(self.ori_dir_partB_train_lab, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partB_train_lab))
]
ori_den_paths = [
osp.join(self.ori_dir_partB_train_den, file_name)
for file_name in sorted(
os.listdir(self.ori_dir_partB_train_den))
]
augment(ori_img_paths,
ori_lab_paths,
ori_den_paths,
aug_dir_partB_img,
aug_dir_partB_lab,
aug_dir_partB_den,
slide_window_params,
noise_params,
light_params,
downscale_img=downscale,
ten_crop=ten_crop)
test_img_paths = [
osp.join(self.ori_dir_partB_test_img,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partB_test_img))
]
test_lab_paths = [
osp.join(self.ori_dir_partB_test_lab,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partB_test_lab))
]
test_den_paths = [
osp.join(self.ori_dir_partB_test_den,
file_name) for file_name in sorted(
os.listdir(self.ori_dir_partB_test_den))
]
if downscale:
downscale_test_images(test_img_paths, test_dir_partB_img,
test_lab_paths, test_dir_partB_lab,
test_den_paths, test_dir_partB_den,
slide_window_params['size_x'],
slide_window_params['size_y'])
elif ten_crop:
resize_test_img_ten_crop_mode(
test_img_paths, test_dir_partB_img, test_lab_paths,
test_dir_partB_lab, test_den_paths, test_dir_partB_den)
else:
copy_to_directory(test_img_paths, test_dir_partB_img)
copy_to_directory(test_lab_paths, test_dir_partB_lab)
copy_to_directory(test_den_paths, test_dir_partB_den)