conceptual-12M-224 / resize.py
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Create resize.py
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from io import BytesIO
import ujson
import webdataset as wds
from PIL import Image
from tqdm import tqdm
import os
import albumentations as A
import cv2
def load_text(txt: bytes):
return txt.decode()
def load_image(jpg):
return Image.open(BytesIO(jpg)).convert('RGB')
load_mapping = {
'jpg': load_image,
'txt': load_text
}
def valid_image(img):
return min(img.size) >= 64
def resize_img(img, max_size=224):
width, height = img.size
if max(width,height) > max_size:
if width < height:
new_height = max_size
new_width = int(max_size * width / height)
else:
new_width = max_size
new_height = int(max_size * height / width)
img = img.resize((new_width, new_height), Image.BICUBIC)
# Pad the image to make it square
width, height = img.size
new_img = Image.new("RGB", (max_size, max_size), (255, 255, 255))
new_img.paste(img, ((max_size - width) // 2, (max_size - height) // 2))
return new_img
def img_to_meta(img):
width, height = img.size
return {
'width': width,
'height': height
}
def get_image(img):
if not valid_image(img):
return None, None
img=resize_img(img)
img_stream = BytesIO()
img.save(img_stream, format='jpeg')
img_stream.seek(0)
return img_stream.read(), ujson.dumps(img_to_meta(img))
change_mapping = {
'jpg': get_image
}
def func(wds_dataset_str, **kwargs):
ds = wds.WebDataset(wds_dataset_str, shardshuffle=False).map_dict(**load_mapping).map_dict(**change_mapping).to_tuple(
'jpg', 'txt')
dl = wds.WebLoader(ds, batch_size=None, num_workers=48, prefetch_factor=16, **kwargs)
writer = wds.ShardWriter('target_path/%05d.tar', 10000)
for img, txt in tqdm(dl):
img_str, meta = img
if img_str is None:
continue
sample = {
'__key__': f'{writer.count:08}',
'jpg': img_str,
'txt': txt,
'json': meta
}
writer.write(sample)
if __name__ == '__main__':
func('path_to_origin_data')