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##############################################################################
# Name: download_sound_and_img_pairs.py
#
# - Downloads sound and image pairs from huggingface
# - https://huggingface.co/datasets/MVRL/iSoundNat
###############################################################################
import os
import itertools
import requests
import time
import threading
import ffmpeg
import pandas as pd
from concurrent.futures import ThreadPoolExecutor, as_completed
from tqdm import tqdm # progress bar
from PIL import Image
##############################
# SETUP: DIRECTORIES & DATASET
##############################
mode = "train" # or "validation" or "test"
# Define which split to use and CSV paths.
splits = {
'train': 'train_df.csv',
'validation': 'val_df.csv',
'test': 'test_df.csv'
}
# Here we load the training CSV; adjust as needed.
df = pd.read_csv("hf://datasets/MVRL/iSoundNat/" + splits[mode])
# If you want to skip to a specific row (for example, row index 19000),
# then slice the DataFrame accordingly.
start_index = 0
if start_index > 0:
df = df.iloc[start_index:].reset_index(drop=True)
# Directories for saving images and audio files
image_save_dir = f"/mnt/hdd/inat2021_ds/sound_{mode}/images"
audio_save_dir = f"/mnt/hdd/inat2021_ds/sound_{mode}/sounds_mp3"
os.makedirs(image_save_dir, exist_ok=True)
os.makedirs(audio_save_dir, exist_ok=True)
# Convert dataframe rows to a list of dictionaries for iteration.
rows = df.to_dict("records")
num_rows = len(rows)
# Dictionaries to record failures for pairs (keyed by id)
image_failures = {}
audio_failures = {}
# Global progress bar and lock (one update per pair processed)
pbar = tqdm(total=num_rows, desc="Pairs Processed")
progress_lock = threading.Lock()
##############################
# HELPER FUNCTIONS
##############################
def convert_image_to_jpeg(temp_path, final_path):
"""
Opens the image at temp_path using Pillow.
If its format is not JPEG, converts it.
Saves the image as JPEG to final_path.
"""
try:
with Image.open(temp_path) as im:
if im.format != "JPEG":
rgb_im = im.convert("RGB")
rgb_im.save(final_path, "JPEG")
else:
# If already JPEG, simply rename the file.
os.rename(temp_path, final_path)
except Exception as e:
print(f"Error converting image {temp_path}: {e}")
raise e
def is_audio_corrupted(file_path):
"""
Uses ffmpeg.probe() to check if an audio file is readable.
Returns True if the file is corrupted or unreadable.
"""
try:
ffmpeg.probe(file_path)
return False
except ffmpeg.Error as e:
print(f"Error probing audio '{file_path}': {e}")
return True
def is_mp3_format(file_path):
"""
Probes the file and checks whether 'mp3' is part of the format name.
"""
try:
info = ffmpeg.probe(file_path)
format_name = info.get("format", {}).get("format_name", "")
return "mp3" in format_name
except Exception as e:
print(f"Error checking mp3 format for '{file_path}': {e}")
return False
def convert_to_mp3(input_file, output_file):
"""
Converts the input audio file to MP3 using the libmp3lame codec.
"""
try:
stream = ffmpeg.input(input_file)
stream = ffmpeg.output(stream, output_file, acodec="libmp3lame")
ffmpeg.run(stream, quiet=True)
except ffmpeg.Error as e:
print(f"Error converting audio '{input_file}' to MP3: {e}")
raise e
##############################
# DOWNLOAD FUNCTIONS WITH RETRIES
##############################
def download_image(row, image_url, image_id, image_save_path):
"""
Downloads the image from row["image_url"].
Saves a temporary file then converts (if needed) to JPEG as {id}.
"""
temp_path = image_save_path + ".temp"
headers = {
"User-Agent": (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/115.0.0.0 Safari/537.36"
)
}
max_retries = 3
success = False
for attempt in range(1, max_retries + 1):
try:
response = requests.get(image_url, headers=headers, timeout=10)
response.raise_for_status()
with open(temp_path, "wb") as f:
f.write(response.content)
success = True
break # Exit loop on success.
except Exception as e:
if attempt < max_retries:
time.sleep(2)
else:
print(f"FAILURE: Could not download image {image_id} from {image_url} after {max_retries} attempts")
success = False
if not success:
if os.path.exists(temp_path):
try:
os.remove(temp_path)
except Exception:
pass
return False
try:
convert_image_to_jpeg(temp_path, image_save_path)
except Exception as e:
print(f"Error processing image {image_id}: {e}")
if os.path.exists(temp_path):
try:
os.remove(temp_path)
except Exception:
pass
if os.path.exists(image_save_path):
try:
os.remove(image_save_path)
except Exception:
pass
return False
finally:
if os.path.exists(temp_path):
try:
os.remove(temp_path)
except Exception:
pass
return os.path.exists(image_save_path)
def download_audio(row, audio_url, audio_id, audio_save_path):
"""
Downloads the audio file from row["sound_url"].
Saves it to a temporary file, checks for corruption, and if needed converts it to MP3
as {id}.mp3 using ffmpeg-python.
"""
# temp_path = os.path.join(audio_save_dir, f"{audio_id}_temp")
temp_path = audio_save_path + ".temp"
headers = {
"User-Agent": (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/115.0.0.0 Safari/537.36"
)
}
max_retries = 5
success = False
for attempt in range(1, max_retries + 1):
try:
response = requests.get(audio_url, headers=headers, timeout=10)
response.raise_for_status()
with open(temp_path, "wb") as f:
f.write(response.content)
success = True
break
except Exception as e:
if attempt < max_retries:
time.sleep(2)
else:
print(f"FAILURE: Could not download audio {audio_id} from {audio_url} after {max_retries} attempts")
success = False
if not success:
if os.path.exists(temp_path):
try:
os.remove(temp_path)
except Exception:
pass
return False
# Check if the downloaded audio is corrupted.
if is_audio_corrupted(temp_path):
print(f"Audio file {audio_id} is corrupted.")
try:
os.remove(temp_path)
except Exception:
pass
return False
# Check if the audio is already in MP3 format.
if is_mp3_format(temp_path):
try:
os.rename(temp_path, audio_save_path)
except Exception as e:
print(f"Error renaming audio {audio_id}: {e}")
try:
os.remove(temp_path)
except Exception:
pass
return False
return True
else:
try:
convert_to_mp3(temp_path, audio_save_path)
except Exception as e:
print(f"Error converting audio {audio_id}: {e}")
try:
os.remove(temp_path)
except Exception:
pass
return False
finally:
if os.path.exists(temp_path):
try:
os.remove(temp_path)
except Exception:
pass
return os.path.exists(audio_save_path)
def download_pair(row):
"""
Downloads both the image and audio for a given row.
If either download/conversion fails, deletes any successfully downloaded file
and marks the pair as a failure.
"""
# If the final image already exists, assume it's already downloaded.
image_url = row["image_url"]
image_id = row["id"]
img_save_path = os.path.join(image_save_dir, f"{image_id}.jpg")
img_exists = False
if os.path.exists(img_save_path):
img_exists = True
# If the final audio already exists, assume it's already downloaded.
audio_url = row["sound_url"]
audio_id = row["id"]
audio_save_path = os.path.join(audio_save_dir, f"{audio_id}.mp3")
audio_exists = False
if os.path.exists(audio_save_path):
audio_exists = True
# Skip the download if both files already exist.
if not (img_exists and audio_exists):
image_success = download_image(row, image_url, image_id, img_save_path)
audio_success = download_audio(row, audio_url, audio_id, audio_save_path)
# If either download failed, delete any successfully downloaded file.
if not (image_success and audio_success):
image_failures[row["id"]] = row["image_url"]
audio_failures[row["id"]] = row["sound_url"]
success = False
else:
success = True
else:
success = True
print(f"SKIPPED: Image {image_id} and Audio {audio_id} already exists.")
with progress_lock:
pbar.update(1)
return success
def chunked_iterator(iterable, chunk_size):
"""
Yields successive chunks of size chunk_size from the iterable.
"""
iterator = iter(iterable)
while True:
chunk = list(itertools.islice(iterator, chunk_size))
if not chunk:
break
yield chunk
##############################
# PROCESS THE DATASET IN CHUNKS
##############################
chunk_size = 999999 # Adjust based on memory and dataset size.
max_workers = 8 # Number of threads for parallel downloads.
# Process rows in chunks using multi-threading.
try:
for chunk in chunked_iterator(rows, chunk_size):
with ThreadPoolExecutor(max_workers=max_workers) as executor:
futures = {executor.submit(download_pair, row): row for row in chunk}
for future in as_completed(futures):
try:
future.result() # True if both downloads succeeded.
except Exception as e:
row = futures[future]
print(f"Error processing row {row['id']}: {e}")
except Exception as e:
print(f"An error occurred during processing: {e}")
pbar.close()
print("Image download failures:", image_failures)
print("Audio download failures:", audio_failures)
print("len(image_failures):", len(image_failures))
print("len(audio_failures):", len(audio_failures))
##############################
# REMOVE FAILURE ROWS FROM ORIGINAL DATAFRAME AND EXPORT
##############################
# Combine IDs from both failure dictionaries.
failure_ids = set(image_failures.keys()).union(set(audio_failures.keys()))
print(f"Total failed pairs: {len(failure_ids)}")
# Remove failed rows from the original dataframe (preserving original order).
successful_df = df[~df["id"].isin(failure_ids)]
output_csv = f"/mnt/hdd/inat2021_ds/sound_{mode}/sound_image_pairs_filtered.csv"
successful_df.to_csv(output_csv, index=False)
print(f"Exported {len(successful_df)} successful rows to {output_csv}")
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