Refactored a bit.
This commit is contained in:
Felix Delattre
parent
290c8f8c57
commit
6bbaa4b3eb
8 changed files with 323 additions and 331 deletions
134
efast.py
134
efast.py
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@ -6,28 +6,16 @@ from datetime import datetime, timedelta
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import numpy as np
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import rasterio
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from rasterio.warp import Resampling
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from rasterio.vrt import WarpedVRT
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from scipy import ndimage
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_this_file = Path(__file__).resolve()
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_venv_lib = _this_file.parent.parent / "venv" / "lib"
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_efast_pkg_path = None
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if _venv_lib.exists():
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for py_dir in _venv_lib.glob("python*"):
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candidate = py_dir / "site-packages" / "efast" / "efast.py"
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if candidate.exists():
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_efast_pkg_path = candidate
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break
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RESOLUTION_RATIO = 21
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if _efast_pkg_path and _efast_pkg_path.exists():
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spec = importlib.util.spec_from_file_location(
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"efast_fusion_module", _efast_pkg_path
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)
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efast_fusion = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(efast_fusion)
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else:
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try:
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import efast as efast_fusion
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except ImportError:
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import site
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efast_fusion = None
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for site_pkg in site.getsitepackages():
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candidate = Path(site_pkg) / "efast" / "efast.py"
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if candidate.exists():
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@ -37,23 +25,51 @@ else:
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efast_fusion = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(efast_fusion)
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break
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else:
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if efast_fusion is None:
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raise ImportError(
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"efast package not found. Install with: pip install git+https://github.com/DHI-GRAS/efast.git"
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)
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def _load_clouds(clouds_file):
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clouds = {"s2": set(), "s3": set()}
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if clouds_file.exists():
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clouds_data = json.loads(clouds_file.read_text())
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clouds["s2"] = set(clouds_data.get("s2", []))
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clouds["s3"] = set(clouds_data.get("s3", []))
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return clouds
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def _reproject_to_target(
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data, src_transform, src_crs, target_bounds, target_crs, width, height, resampling
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):
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dst_transform = rasterio.transform.from_bounds(
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target_bounds.left,
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target_bounds.bottom,
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target_bounds.right,
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target_bounds.top,
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width,
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height,
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)
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reprojected, _ = rasterio.warp.reproject(
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source=data,
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destination=np.zeros((data.shape[0], height, width), dtype=data.dtype),
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src_transform=src_transform,
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src_crs=src_crs,
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dst_transform=dst_transform,
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dst_crs=target_crs,
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resampling=resampling,
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)
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return reprojected, dst_transform
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def prepare_s2(season, site_position, site_name, date_range=None):
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s2_dir = Path(f"data/{site_name}/{season}/raw/s2/")
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s3_dir = Path(f"data/{site_name}/{season}/raw/s3/")
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s2_output_dir = Path(f"data/{site_name}/{season}/prepared/s2/")
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clouds_file = Path(f"data/{site_name}/{season}/clouds.json")
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clouds = {"s2": set(), "s3": set()}
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if clouds_file.exists():
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clouds_data = json.loads(clouds_file.read_text())
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clouds["s2"] = set(clouds_data.get("s2", []))
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clouds["s3"] = set(clouds_data.get("s3", []))
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clouds = _load_clouds(clouds_file)
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s2_output_dir.mkdir(parents=True, exist_ok=True)
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@ -66,9 +82,8 @@ def prepare_s2(season, site_position, site_name, date_range=None):
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target_crs = s3_ref.crs
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s3_width = s3_ref.width
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s3_height = s3_ref.height
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ratio = 21
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s2_width = s3_width * ratio
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s2_height = s3_height * ratio
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s2_width = s3_width * RESOLUTION_RATIO
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s2_height = s3_height * RESOLUTION_RATIO
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for s2_file in s2_dir.glob("*.geotiff"):
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if s2_file.name in clouds["s2"]:
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@ -79,25 +94,15 @@ def prepare_s2(season, site_position, site_name, date_range=None):
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if not refl_dst.exists():
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with rasterio.open(s2_file) as src:
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data = src.read().astype("float32") / 10000.0
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s2_res = (target_bounds.right - target_bounds.left) / s2_width
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dst_transform = rasterio.transform.from_bounds(
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target_bounds.left,
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target_bounds.bottom,
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target_bounds.right,
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target_bounds.top,
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reprojected_data, dst_transform = _reproject_to_target(
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data,
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src.transform,
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src.crs,
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target_bounds,
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target_crs,
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s2_width,
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s2_height,
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)
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reprojected_data, _ = rasterio.warp.reproject(
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source=data,
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destination=np.zeros(
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(src.count, s2_height, s2_width), dtype=data.dtype
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),
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src_transform=src.transform,
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src_crs=src.crs,
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dst_transform=dst_transform,
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dst_crs=target_crs,
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resampling=Resampling.cubic,
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Resampling.cubic,
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)
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profile = src.profile.copy()
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profile.update(
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@ -118,30 +123,19 @@ def prepare_s2(season, site_position, site_name, date_range=None):
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with rasterio.open(refl_dst) as src:
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s2_hr = src.read(1)
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mask = s2_hr == 0
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distance_to_cloud_hr = ndimage.distance_transform_edt(~mask)
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distance_to_cloud_hr = np.clip(distance_to_cloud_hr, 0, 255).astype(
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"float32"
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)
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distance_to_cloud_hr = np.clip(
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ndimage.distance_transform_edt(~mask), 0, 255
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).astype("float32")
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s3_res = (target_bounds.right - target_bounds.left) / s3_width
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lr_transform = rasterio.transform.from_bounds(
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target_bounds.left,
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target_bounds.bottom,
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target_bounds.right,
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target_bounds.top,
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distance_to_cloud_lr, lr_transform = _reproject_to_target(
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distance_to_cloud_hr[np.newaxis, :, :],
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src.transform,
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src.crs,
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target_bounds,
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target_crs,
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s3_width,
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s3_height,
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)
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distance_to_cloud_lr, _ = rasterio.warp.reproject(
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source=distance_to_cloud_hr[np.newaxis, :, :],
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destination=np.zeros(
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(1, s3_height, s3_width), dtype=distance_to_cloud_hr.dtype
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),
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src_transform=src.transform,
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src_crs=target_crs,
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dst_transform=lr_transform,
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dst_crs=target_crs,
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resampling=Resampling.average,
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Resampling.average,
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)
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distance_to_cloud_lr = distance_to_cloud_lr[0]
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@ -164,10 +158,7 @@ def prepare_s3(season, site_position, site_name, date_range=None):
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s3_preprocessed_dir = Path(f"data/{site_name}/{season}/prepared/s3/")
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clouds_file = Path(f"data/{site_name}/{season}/clouds.json")
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clouds = {"s3": set()}
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if clouds_file.exists():
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clouds_data = json.loads(clouds_file.read_text())
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clouds["s3"] = set(clouds_data.get("s3", []))
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clouds = _load_clouds(clouds_file)
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s3_preprocessed_dir.mkdir(parents=True, exist_ok=True)
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for s3_file in s3_dir.glob("*.geotiff"):
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@ -193,8 +184,9 @@ def run_efast(season, site_position, site_name, date_range=None):
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print(f"[EFAST] Starting fusion: {site_name} ({lat:.6f}, {lon:.6f}), {season}")
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start_date = datetime.strptime(datetime_range.split("/")[0], "%Y-%m-%d")
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end_date = datetime.strptime(datetime_range.split("/")[1], "%Y-%m-%d")
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start_str, end_str = datetime_range.split("/")
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start_date = datetime.strptime(start_str, "%Y-%m-%d")
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end_date = datetime.strptime(end_str, "%Y-%m-%d")
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current_date = start_date
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while current_date <= end_date:
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@ -216,7 +208,7 @@ def run_efast(season, site_position, site_name, date_range=None):
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max_days=30,
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date_position=2,
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minimum_acquisition_importance=0.0,
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ratio=21,
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ratio=RESOLUTION_RATIO,
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)
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if output_file.exists():
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print(f"[EFAST] Saved: {output_file}")
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