File size: 1,532 Bytes
9bc98d9 | 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 | import os
from pathlib import Path
import rasterio
from rasterio.transform import from_bounds
from src.process.io import prepare_dirs, unzip, upload
from src.process.processor import process_tif
# === Step 1: Set up local and drive directories ===
local_processed_dir, drive_download_dir, drive_processed_dir = (
prepare_dirs("esdac", Path(__file__).parent.stem)
)
# === Step 2: Unzip all ZIP files from drive/download to local/processed ===
unzip(local_processed_dir, drive_download_dir, zip_files=None)
os.system("mv src/esdac/glosem/processed/Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/"
"Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/SOIL_DISPLACEMENT_ESTIMATE_2019.tif.ovr "
"src/esdac/glosem/processed/Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/"
"Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1/SOIL_DISPLACEMENT_ESTIMATE_2019.tif")
# === Step 3: Process all TIFF files under local/processed ===
move_list = []
for tif_path in sorted(local_processed_dir.rglob("*.tif")):
move_list = process_tif(tif_path, move_list)
f = local_processed_dir / "Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1" / \
"Data2_SOIL_DISPLACEMENT_ESTIMATE_2019_1" / "SOIL_DISPLACEMENT_ESTIMATE_2019.standardized.tif"
with rasterio.open(f, "r+") as ds:
ds.crs = "EPSG:4326"
ds.transform = from_bounds(-180, -90, 180, 90, ds.width, ds.height)
print("✅ CRS and transform fixed:", f)
# === Step 4: Upload processed files to drive/processed and clean up local ===
upload(local_processed_dir, drive_processed_dir, move_list)
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