def main(src_path, dst_path, image_size):
try:
for file in image_list(src_path):
_, name, ext = split_path(file)
save = os.path.join(dst_path, name + ext)
#save = os.path.join(dst_path, name+'a' + ext)
print(save)
resize_image_file(file, image_size, save)
#rename(file,save)
except IOError:
pass # You can always log it to logger
def rename(img_path, save_path):
img_path = (norm_path(img_path))
save_path = norm_path(save_path)
save_dir, _, _ = split_path(save_path)
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# read image
im = cv2.imread(img_path)
cv2.imwrite(save_path[:-3] + 'png', im)
def main(data_dir, result_dir, image_size):
try:
for file in image_list(data_dir):
_, name, ext = split_path(file)
save = os.path.join(result_dir, name + ext)
print(save)
resize_image_file(file, image_size, save)
make_dataset(data_dir, mask_dir, result_dir)
except IOError:
pass # You can always log it to logger
def resize_image_file(img_path, image_size, save_path):
img_path = (norm_path(img_path))
save_path = norm_path(save_path)
save_dir, _, _ = split_path(save_path)
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# read image
im = cv2.imread(img_path)
# resize image
im = resize_image(im, image_size)
# write image
cv2.imwrite(save_path[:-3] + 'png', im)
def save_tensor_image(input, filename_list=None, path='temp'):
if not os.path.isdir(path):
os.makedirs(path)
image_list = input.cpu().data.numpy()
for i, image in enumerate(image_list):
# get filename
filename = get_increasing_filename() if filename_list is None else filename_list[i]
#print(image.shape)
image = np.transpose(image, axes=[1, 2, 0])
#print(image.shape)
_,file_dir,_ = split_path(filename)
# save image
scipy.misc.imsave(os.path.join(path, file_dir + '.png'), image.squeeze())
def resize_image_file(img_path, image_size, save_path):
img_path = (norm_path(img_path))
save_path = norm_path(save_path)
save_dir, _, _ = split_path(save_path)
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# read image
im = cv2.imread(img_path)
# resize image
im = resize_image(im, image_size)
# # extract gammma image
# greenpath = '/home/bong6/data/mrcnn_cer/classificationdataset_224 (copy)/train/green_type3'
# if np.max(im[:, :, 0]) < 60 and np.max(im[:, :, 2]) < 60:
# if not os.path.exists(greenpath):
# os.makedirs(greenpath)
#
# shutil.move(img_path, greenpath)
# else:
# write image
cv2.imwrite(save_path[:-3] + 'png', im)