Open-Sora/tools/datasets/resize.py
2024-04-02 16:55:03 +08:00

88 lines
2.1 KiB
Python

import argparse
import os
import cv2
import pandas as pd
from tqdm import tqdm
tqdm.pandas()
try:
from pandarallel import pandarallel
pandarallel.initialize(progress_bar=True)
pandas_has_parallel = True
except ImportError:
pandas_has_parallel = False
def apply(df, func):
if pandas_has_parallel:
return df.parallel_apply(func)
return df.progress_apply(func)
IMG_EXTENSIONS = (
".jpg",
".jpeg",
".png",
".ppm",
".bmp",
".pgm",
".tif",
".tiff",
".webp",
)
def get_new_path(path, input_dir, output):
path_new = os.path.join(output, os.path.relpath(path, input_dir))
os.makedirs(os.path.dirname(path_new), exist_ok=True)
return path_new
def resize(path, length, input_dir, output):
path_new = get_new_path(path, input_dir, output)
ext = os.path.splitext(path)[1].lower()
if ext in IMG_EXTENSIONS:
img = cv2.imread(path)
h, w = img.shape[:2]
if min(h, w) > length:
if h > w:
new_h = length
new_w = int(w * new_h / h)
else:
new_w = length
new_h = int(h * new_w / w)
img = cv2.resize(img, (new_w, new_h))
cv2.imwrite(path_new, img)
else:
pass
return path_new
def main(args):
data = pd.read_csv(args.input)
data["path"] = apply(data["path"], lambda x: resize(x, args.length, args.input_dir, args.output))
output_csv = args.input.replace(".csv", f"_resized{args.length}.csv")
data.to_csv(output_csv, index=False)
print(f"Saved to {output_csv}")
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("input", type=str)
parser.add_argument("input_dir", type=str)
parser.add_argument("output", type=str)
parser.add_argument("--disable-parallel", action="store_true")
parser.add_argument("--length", type=int, default=2160)
args = parser.parse_args()
return args
if __name__ == "__main__":
args = parse_args()
if args.disable_parallel:
pandas_has_parallel = False
main(args)