def extra_files_by_postfix(ori_root,
dest_root,
match_postfix='',
new_postfix=None,
match_ext='*'):
'''
extra files from ori_root to dest_root by match_postfix and match_ext
params:
ori_root: the dir of files that need to be processed
dest_root: the dir for saving matched files
match_postfix: the postfix to be matched
new_postfix: the postfix for matched files
default: None, that is keeping the ori postfix
match_ext: the ext to be matched
'''
if new_postfix is None:
new_postfix = match_postfix
handle_dir(dest_root)
flag_img_list = glob_match(
os.path.join(ori_root, "*{}.{}".format(match_postfix, match_ext)))
for im in flag_img_list:
fname, ext = get_fname_ext(im)
dest_basename = '{}{}.{}'.format(fname[-len(match_postfix):],
new_postfix, ext)
src = im
dst = os.path.join(dest_root, dest_basename)
copy_file(src, dst)
def batch_shift_images(ori_root,
dest_root,
offset_x=0.,
offset_y=0.,
filename_template="{}.png"): # TODO
'''
function:
shifting images by (offset_x, offset_y) on (axis-x, axis-y) in batches
params:
ori_root: string, the dir of images that need to be processed
dest_root: string, the dir to save processed images
offset_x: float, offset pixels on axis-x
positive=left; negative=right
offset_y: float, offset pixels on axis-y
positive=up; negative=down
filename_template: string, the filename template for saving images
'''
handle_dir(dest_root)
offset_x, offset_y = float(offset_x), float(offset_y)
images_fname = sorted(listdir(ori_root))
for imf in images_fname:
img = cv2.imread(os.path.join(ori_root, imf)).astype('float32')
img = image_shift(img, offset_x=offset_x, offset_y=offset_y)
cv2.imwrite(
os.path.join(dest_root,
filename_template.format(get_fname_ext(imf)[0])), img)
print("Image", imf, "shift done !")
def batch_matlab_resize_images(ori_root,
dest_root,
scale=1.0,
method='bicubic',
filename_template="{}.png"):
'''
function:
resizing images in batches, same as matlab2017 imresize
params:
ori_root: string, the dir of images that need to be processed
dest_root: string, the dir to save processed images
scale: float, the resize scale
method: string, the interpolation method,
optional: 'bilinear', 'bicubic'
default: 'bicubic'
filename_template: string, the filename template for saving images
'''
if method != 'bilinear' and method != 'bicubic':
raise Exception('Unknown method!')
handle_dir(dest_root)
scale = float(scale)
images_fname = sorted(listdir(ori_root))
for imf in images_fname:
img = cv2.imread(os.path.join(ori_root, imf)).astype('float32')
img = matlab_imresize(img, scalar_scale=scale, method=method)
cv2.imwrite(
os.path.join(dest_root,
filename_template.format(get_fname_ext(imf)[0])), img)
print("Image", imf, "resize done !")
def add_files_postfix(root, postfix=''):
'''
add postfix to filename
params:
root: the dir of files that need to be processed
postfix: the postfix to be added
'''
img_list = glob_match(os.path.join(root, "*"))
for im in img_list:
fname, ext = get_fname_ext(im)
dest_basename = "{}{}.{}".format(fname, postfix, ext)
src = im
dst = os.path.join(root, dest_basename)
rename_file(src, dst)
def resort_files_index(root, template='{:0>4}', start_idx=0):
'''
resort files' filename using template that index start from start_idx
params:
root: the dir of files that need to be processed
template: the template for processed filename
start_idx: the start index
'''
template = template + '.{}'
img_list = sorted(glob_match(os.path.join(root, "*")))
for i, im in enumerate(img_list):
fname, ext = get_fname_ext(im)
dest_basename = template.format(i + start_idx, ext)
src = im
dst = os.path.join(root, dest_basename)
rename_file(src, dst)
def remove_files_postfix(root, postfix=''):
'''
remove postfix from filename
params:
root: the dir of files that need to be processed
postfix: the postfix to be removed
'''
img_list = glob_match(os.path.join(root, "*"))
for im in img_list:
fname, ext = get_fname_ext(im)
now_postfix = fname[-len(postfix):]
if now_postfix == postfix:
dest_basename = "{}.{}".format(fname[:-len(postfix)], ext)
src = im
dst = os.path.join(root, dest_basename)
rename_file(src, dst)
def save_flow_pt2mat(ori_root, dest_root):
'''
把 ori_root 中视频的 flow 从 pt 文件转换为 mat 文件后保存到 dest_root
保存在 pt 文件中的 flow 的 shape=[1, 2, h, w]
'''
handle_dir(dest_root)
video_list = listdir(ori_root)
for v in video_list:
handle_dir(os.path.join(dest_root, v))
file_list = glob_match(os.path.join(ori_root, v, "*.pt"))
for pt_path in file_list:
fname, ext = get_fname_ext(pt_path)
mat_path = os.path.join(dest_root, v, "{}.mat".format(fname))
try:
flow = torch.load(pt_path)[0].permute(1, 2, 0).cpu().numpy()
flow_dict = {'flow': flow}
scio.savemat(mat_path, flow_dict)
print('save {} to {}'.format(pt_path, mat_path))
except:
print('skip file {}'.format(pt_path))
def batch_cv2_resize_images(ori_root,
dest_root,
scale=1.0,
method='bicubic',
filename_template="{}.png"):
'''
function:
resizing images in batches
params:
ori_root: string, the dir of images that need to be processed
dest_root: string, the dir to save processed images
scale: float, the resize scale
method: string, the interpolation method,
optional: 'nearest', 'bilinear', 'bicubic'
default: 'bicubic'
filename_template: string, the filename template for saving images
'''
if method == 'nearest':
interpolation = cv2.INTER_NEAREST
elif method == 'bilinear':
interpolation = cv2.INTER_LINEAR
elif method == 'bicubic':
interpolation = cv2.INTER_CUBIC
else:
raise Exception('Unknown method!')
handle_dir(dest_root)
scale = float(scale)
images_fname = sorted(listdir(ori_root))
for imf in images_fname:
img = cv2.imread(os.path.join(ori_root, imf)).astype('float32')
img = cv2.resize(img,
dsize=(0, 0),
fx=scale,
fy=scale,
interpolation=interpolation)
cv2.imwrite(
os.path.join(dest_root,
filename_template.format(get_fname_ext(imf)[0])), img)
print("Image", imf, "resize done !")