scripts/download_from_commons.py

import pandas as pd
import requests
import os
import argparse
from tqdm import tqdm
from  dataset_utils import resize_square
from PIL import Image
import cairosvg
from io import BytesIO
from dotenv import load_dotenv
import time
import random
load_dotenv()

DATA_DIR = os.environ['DATA_DIR']
original_dir = os.path.join(DATA_DIR, 'original_path')
resized_dir = os.path.join(DATA_DIR, 'resized_path')

def fetch_image(url, max_retries=5):
    headers = {
        'User-Agent': random.choice([
            'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
            'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
            'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
        ])
    }
    
    for attempt in range(max_retries):
        try:
            response = requests.get(url, headers=headers, stream=True)
            if response.status_code == 429:  # Too Many Requests
                retry_after = int(response.headers.get("Retry-After", random.uniform(1, 5)))
                time.sleep(retry_after)
                continue
            response.raise_for_status()
            return response.content
        except requests.exceptions.RequestException as e:
            wait_time = 2 ** attempt + random.uniform(0, 1)  # Exponential backoff
            print(f"Error fetching {url}: {e}, retrying in {wait_time:.2f}s")
            time.sleep(wait_time)
    
    print(f"Failed to fetch {url} after {max_retries} attempts.")
    return None

def main(args):
    df = pd.read_csv(args.csv)
    df['original_path'] = ''
    df['resized_path'] = ''

    errors = 0
    count = 0
    
    for index, row in tqdm(df.iterrows(), total=len(df)):
        image_url = row['image']
        subject = row['subject'].replace(' ', '_').replace('/', '_')
        type_original_dir = os.path.join(original_dir, row['type'])
        type_resized_dir = os.path.join(resized_dir, row['type'])
        os.makedirs(type_original_dir, exist_ok=True)
        os.makedirs(type_resized_dir, exist_ok=True)
        
        image_data = fetch_image(image_url)
        if image_data:
            try:
                if image_url.endswith('.svg'):
                    png_bytes = cairosvg.svg2png(bytestring=image_data)
                    image = Image.open(BytesIO(png_bytes)).convert("RGBA")
                else:
                    image = Image.open(BytesIO(image_data))

                if row['type'] == 'brands':
                    image = image.convert("RGBA")
                    white_bg = Image.new("RGB", image.size, (255, 255, 255))
                    white_bg.paste(image, mask=image.split()[3])
                    image = white_bg
                
                first_letter = subject[0].lower()
                os.makedirs(os.path.join(type_original_dir, first_letter), exist_ok=True)
                original_filepath = os.path.join(type_original_dir, first_letter, f'{subject}.jpg')
                image.save(original_filepath, "JPEG", quality=95)

                im = Image.open(original_filepath)
                im = resize_square(im)
                
                os.makedirs(os.path.join(type_resized_dir, first_letter), exist_ok=True)
                resized_filepath = os.path.join(type_resized_dir, first_letter, f'{subject}.jpg')
                im.save(resized_filepath, im.format)

                df.at[index, 'original_path'] = original_filepath if os.path.exists(original_filepath) else ''
                df.at[index, 'resized_path'] = resized_filepath if os.path.exists(resized_filepath) else ''
                
            except Exception as e:
                errors += 1
                print(Exception(f"Failed to download image {subject}: {str(e)}"))
                continue
        else:
            errors += 1
            continue
        count += 1

    df = df[df['original_path'] != '']
    df = df[df['resized_path'] != '']
    df.to_csv(args.target_df, index=False)
    
    print(f'Finished downloading {count} images with {errors} errors')


def get_exp_parser():
    parser = argparse.ArgumentParser(add_help=False)
    parser.add_argument('--base_df', type=str)
    parser.add_argument('--target_df', type=str)
    parser.add_argument('--width', type=int, default=336)
    return parser


if __name__ == "__main__":
    parser = get_exp_parser()
    args = parser.parse_args()
    main(args)