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Extract images into jpg, have a multiplier & size threshold

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This commit is contained in:
James Betker 2020-09-21 12:36:03 -06:00
parent bde35ced47
commit 384e3d54cc
1 changed files with 20 additions and 14 deletions
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34
codes/data_scripts/extract_subimages.py
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@ -16,15 +16,17 @@ def main():
split_img = False
opt = {}
opt['n_thread'] = 20
opt['compression_level'] = 3 # 3 is the default value in cv2
opt['compression_level'] = 90
# CV_IMWRITE_PNG_COMPRESSION from 0 to 9. A higher value means a smaller size and longer
# compression time. If read raw images during training, use 0 for faster IO speed.
if mode == 'single':
opt['input_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\images'
opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\square_context'
opt['crop_sz'] = 4096 # the size of each sub-image
opt['step'] = 4096 # step of the sliding crop window
opt['thres_sz'] = 256 # size threshold
full_multiplier = .25
opt['input_folder'] = 'F:\\4k6k\\datasets\\images\\goodeats\\hq\\new_season\\lr_hr_enc\\lr\\images'
opt['save_folder'] = 'F:\\4k6k\\datasets\\images\\goodeats\\hq\\new_season\\lr_hr_enc\\lr\\images_tiled'
opt['crop_sz'] = int(256 * full_multiplier) # the size of each sub-image
opt['step'] = int(128 * full_multiplier) # step of the sliding crop window
opt['thres_sz'] = int(64 * full_multiplier) # size threshold
opt['image_minimum_size_threshold'] = int(1024 * full_multiplier) # Minimum size of input image in height dim. Images under this size will not be processed.
opt['resize_final_img'] = .5
opt['only_resize'] = False
extract_single(opt, split_img)
@ -90,15 +92,19 @@ def extract_single(opt, split_img=False):
pbar = ProgressBar(len(img_list))
pool = Pool(opt['n_thread'])
pool = Pool(opt['n_thread']) if opt['n_thread'] >= 1 else None
for path in img_list:
# If this fails, change it and the imwrite below to the write extension.
assert ".jpg" in path
if split_img:
pool.apply_async(worker, args=(path, opt, True, False), callback=update)
pool.apply_async(worker, args=(path, opt, True, True), callback=update)
if pool:
if split_img:
pool.apply_async(worker, args=(path, opt, True, False), callback=update)
pool.apply_async(worker, args=(path, opt, True, True), callback=update)
else:
pool.apply_async(worker, args=(path, opt), callback=update)
else:
pool.apply_async(worker, args=(path, opt), callback=update)
assert not split_img
worker(path, opt)
pool.close()
pool.join()
print('All subprocesses done.')
@ -121,7 +127,7 @@ def worker(path, opt, split_mode=False, left_img=True):
raise ValueError('Wrong image shape - {}'.format(n_channels))
# Uncomment to filter any image that doesnt meet a threshold size.
if min(h,w) < 1024:
if min(h,w) < opt['image_minimum_size_threshold']:
return
left = 0
right = w
@ -171,8 +177,8 @@ def worker(path, opt, split_mode=False, left_img=True):
crop_img = cv2.resize(crop_img, dsize, interpolation = cv2.INTER_AREA)
cv2.imwrite(
osp.join(opt['save_folder'],
img_name.replace('.jpg', '_l{:05d}_s{:03d}.png'.format(left, index))), crop_img,
[cv2.IMWRITE_PNG_COMPRESSION, opt['compression_level']])
img_name.replace('.jpg', '_l{:05d}_s{:03d}.jpg'.format(left, index))), crop_img,
[cv2.IMWRITE_JPEG_QUALITY, opt['compression_level']])
return 'Processing {:s} ...'.format(img_name)