File size: 3,413 Bytes
3cb1822 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | import json
import os
import subprocess
import time
import zipfile
# Load dataset information
with open('datasets_info.json', 'r') as f:
datasets = json.load(f)
# Filter datasets under 512MB, excluding existing ones
existing_datasets = []
datasets_to_download = [d for d in datasets if d['size_mb'] < 512 and d['id'] not in existing_datasets]
print(f"Will download and organize {len(datasets_to_download)} datasets")
# Process each dataset
for i, dataset in enumerate(datasets_to_download):
dataset_id = dataset['id']
print(f"\n[{i+1}/{len(datasets_to_download)}] Processing {dataset_id}...")
# Create directory structure
os.makedirs(f"sci_volume_data/{dataset_id}/data", exist_ok=True)
# Download the dataset
url = dataset['download_url']
output_file = f"sci_volume_data/{dataset_id}/data/{dataset['filename']}"
if not os.path.exists(output_file):
print(f" Downloading {dataset['filename']} ({dataset['size_str']})...")
result = subprocess.run(['curl', '-o', output_file, url], capture_output=True)
if result.returncode != 0:
print(f" ERROR downloading {dataset_id}")
continue
time.sleep(0.5) # Be nice to the server
else:
print(f" File already exists, skipping download")
# Create metadata file
metadata_file = f"sci_volume_data/{dataset_id}/data/{dataset_id}.txt"
with open(metadata_file, 'w') as f:
f.write(f"{dataset['name']}\n")
f.write(f"Description: {dataset['description']}\n")
f.write(f"Data Type: {dataset['data_type']}\n")
f.write(f"Data Byte Order: little Endian\n")
f.write(f"Data Spacing: {dataset['spacing']}\n")
f.write(f"Data Extent: {dataset['dimensions']}\n")
print(f" Created directory structure and metadata")
print(f"\nCompleted processing {len(datasets_to_download)} datasets")
# Download BBBC012 dataset for napari_mcp_evals
print(f"\nDownloading BBBC012 dataset for napari_mcp_evals...")
# Create the napari_mcp_evals/data directory
napari_data_dir = "napari_mcp_evals/data"
os.makedirs(napari_data_dir, exist_ok=True)
# Download the BBBC012 dataset
bbbc_url = "https://data.broadinstitute.org/bbbc/BBBC012/BBBC012_v1_images.zip"
bbbc_zip_file = os.path.join(napari_data_dir, "BBBC012_v1_images.zip")
if not os.path.exists(os.path.join(napari_data_dir, "BBBC012_v1_images")):
print(f" Downloading BBBC012_v1_images.zip...")
result = subprocess.run(['curl', '-o', bbbc_zip_file, bbbc_url], capture_output=True)
if result.returncode == 0:
print(f" Download completed successfully")
# Unzip the file
print(f" Extracting BBBC012_v1_images.zip...")
try:
with zipfile.ZipFile(bbbc_zip_file, 'r') as zip_ref:
zip_ref.extractall(napari_data_dir)
print(f" Extraction completed")
# Delete the zip file
os.remove(bbbc_zip_file)
print(f" Cleaned up zip file")
except zipfile.BadZipFile:
print(f" ERROR: Downloaded file is not a valid zip archive")
except Exception as e:
print(f" ERROR during extraction: {e}")
else:
print(f" ERROR downloading BBBC012 dataset")
else:
print(f" BBBC012 dataset already exists, skipping download")
print(f"\nAll processing completed!") |