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| # -*- coding: utf-8 -*- | |
| """ | |
| download_images | |
| Script to retrieve images for the 2023 FathomNet out-of-sample challenge as part of FGVC 10. | |
| Assumes COCO formated annotation file has been download from http://www.kaggle.com/competitions/fathomnet-out-of-sample-detection | |
| """ | |
| # Author: Eric Orenstein (eorenstein@mbari.org) | |
| import os | |
| import sys | |
| import glob | |
| import json | |
| import requests | |
| import logging | |
| import argparse | |
| import progressbar | |
| import pandas as pd | |
| from shutil import copyfileobj | |
| def download_imgs(imgs, outdir=None): | |
| """ | |
| Download images to an output dir | |
| :param imgs: list of urls | |
| :param outdir: desired directory [default to working directory] | |
| :return : | |
| """ | |
| # set the out directory to default if not specified | |
| if not outdir: | |
| outdir = os.path.join(os.getcwd(), 'images') | |
| # make the directory if it does not exist | |
| if not os.path.exists(outdir): | |
| os.mkdir(outdir) | |
| logging.info(f"Created directory {outdir}") | |
| flag = 0 # keep track of how many image downloaded | |
| for name, url in progressbar.progressbar(imgs): | |
| file_name = os.path.join( | |
| outdir, name | |
| ) | |
| # only download if the image does not exist in the outdir | |
| if not os.path.exists(file_name): | |
| resp = requests.get(url, stream=True) | |
| resp.raw.decode_content = True | |
| with open(file_name, 'wb') as f: | |
| copyfileobj(resp.raw, f) | |
| flag += 1 | |
| logging.info(f"Downloaded {flag} new images to {outdir}") | |
| if __name__=="__main__": | |
| parser = argparse.ArgumentParser(description="Download images from a COCO annotation file") | |
| parser.add_argument('dataset', type=str, help='Path to json COCO annotation file') | |
| parser.add_argument('--outpath', type=str, default=None, help='Path to desired output folder') | |
| args = parser.parse_args() | |
| logging.basicConfig(level=logging.INFO) | |
| logging.info(f'opening {args.dataset}') | |
| with open(args.dataset, 'r') as ff: | |
| dataset = json.load(ff) | |
| ims = pd.DataFrame(dataset['images']) | |
| logging.info(f'retrieving {ims.shape[0]} images') | |
| ims = zip(ims['file_name'].to_list(), ims['coco_url'].to_list()) | |
| # download images | |
| download_imgs(ims, outdir=args.outpath) | |