def save_data_list(inpath, outpath, filenames, filename_bbox):
for size in IMG_SIZES:
print('Processing images of size %d' % size)
cnt = 0
images = np.ndarray(shape=(len(filenames), size, size, 3),
dtype=np.uint8)
for idx, key in enumerate(filenames):
bbox = filename_bbox[key]
f_name = '%s/CUB_200_2011/images/%s.jpg' % (inpath, key)
img = get_image(f_name, LOAD_SIZE, is_crop=True, bbox=bbox)
img = img.astype('uint8')
img = img.astype('uint8')
if size != LOAD_SIZE:
img = scipy.misc.imresize(img, [size, size], 'bicubic')
images[idx, :, :, :] = np.array(img)
cnt += 1
if cnt % 100 == 0:
print('\rLoad %d......' % cnt, end="", flush=True)
print('Images processed: %d', len(filenames))
outfile = outpath + str(size) + 'images_cvs.pickle'
joblib.dump(images, outfile)
print('save to: ', outfile)
def save_data_list(inpath, outpath, filenames):
hr_images = []
lr_images = []
lr_size = int(LOAD_SIZE / LR_HR_RETIO)
cnt = 0
for key in filenames:
f_name = '%s/%s.jpg' % (inpath, key)
img = get_image(f_name, LOAD_SIZE, is_crop=False)
img = img.astype('uint8')
hr_images.append(img)
lr_img = scipy.misc.imresize(img, [lr_size, lr_size], 'bicubic')
lr_images.append(lr_img)
cnt += 1
if cnt % 100 == 0:
print('Load %d......' % cnt)
#
print('images', len(hr_images), hr_images[0].shape, lr_images[0].shape)
outfile = outpath + str(LOAD_SIZE) + 'images.pickle'
with open(outfile, 'wb') as f_out:
pickle.dump(hr_images, f_out)
print('save to: ', outfile)
#
outfile = outpath + str(lr_size) + 'images.pickle'
with open(outfile, 'wb') as f_out:
pickle.dump(lr_images, f_out)
print('save to: ', outfile)