pantierra/efast-phenocam-validation
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Fixed efast more.

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This commit is contained in:
Felix Delattre 2026-01-11 00:51:12 +01:00
parent 51e1e32049
commit b14aab37a8
3 changed files with 31 additions and 16 deletions
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13
efast.py → call_efast.py
View file

@ -9,11 +9,14 @@ from rasterio.warp import Resampling
from rasterio.vrt import WarpedVRT from rasterio.vrt import WarpedVRT
from rasterio import shutil as rio_shutil from rasterio import shutil as rio_shutil
try: def _import_efast():
"""Lazy import of efast to avoid import errors when not using efast functions."""
try:
import efast import efast
from efast.s2_processing import distance_to_clouds from efast.s2_processing import distance_to_clouds
from efast.s3_processing import reproject_and_crop_s3 from efast.s3_processing import reproject_and_crop_s3
except ImportError: return efast, distance_to_clouds, reproject_and_crop_s3
except ImportError:
raise ImportError( raise ImportError(
"efast package not found. Install with: pip install git+https://github.com/DHI-GRAS/efast.git" "efast package not found. Install with: pip install git+https://github.com/DHI-GRAS/efast.git"
) )
@ -46,8 +49,8 @@ def _reproject_raster_to_target(src_path, dst_path, target_bounds, target_crs, w
} }
with WarpedVRT(src, **vrt_options) as vrt: with WarpedVRT(src, **vrt_options) as vrt:
profile = vrt.profile.copy() profile = vrt.profile.copy()
profile.update({"dtype": "float32", "nodata": 0}) profile.update({"dtype": "float32", "nodata": 0, "driver": "GTiff"})
rio_shutil.copy(vrt, dst_path, driver="GTiff", **profile) rio_shutil.copy(vrt, dst_path, **profile)
def prepare_s2(season, site_position, site_name, date_range=None): def prepare_s2(season, site_position, site_name, date_range=None):
@ -88,6 +91,7 @@ def prepare_s2(season, site_position, site_name, date_range=None):
_reproject_raster_to_target(temp_normalized, refl_dst, target_bounds, target_crs, s2_width, s2_height) _reproject_raster_to_target(temp_normalized, refl_dst, target_bounds, target_crs, s2_width, s2_height)
temp_normalized.unlink() temp_normalized.unlink()
_, distance_to_clouds, _ = _import_efast()
distance_to_clouds(s2_output_dir, ratio=RESOLUTION_RATIO) distance_to_clouds(s2_output_dir, ratio=RESOLUTION_RATIO)
@ -128,6 +132,7 @@ def prepare_s3(season, site_position, site_name, date_range=None):
with rasterio.open(composite_path, "w", **profile) as dst: with rasterio.open(composite_path, "w", **profile) as dst:
dst.write(composite) dst.write(composite)
_, _, reproject_and_crop_s3 = _import_efast()
reproject_and_crop_s3(temp_composite_dir, s2_prepared_dir, s3_preprocessed_dir) reproject_and_crop_s3(temp_composite_dir, s2_prepared_dir, s3_preprocessed_dir)
shutil.rmtree(temp_composite_dir) shutil.rmtree(temp_composite_dir)

10
ndvi.py
View file

@ -94,6 +94,16 @@ def _process_ndvi_files(
return return
for geotiff_file in geotiff_files: for geotiff_file in geotiff_files:
# Check if file has enough bands (need at least 4 for RED and NIR)
try:
with rasterio.open(geotiff_file) as src:
if src.count < 4:
print(f"[NDVI-{source_name}] Skipping {geotiff_file.name} (only {src.count} band(s), need 4+)")
continue
except Exception as e:
print(f"[NDVI-{source_name}] Skipping {geotiff_file.name} (error reading: {e})")
continue
output_file = output_dir / ( output_file = output_dir / (
output_namer(geotiff_file) if output_namer else geotiff_file.name output_namer(geotiff_file) if output_namer else geotiff_file.name
) )

12
run.py
View file

@ -1,4 +1,4 @@
from efast import run_efast, prepare_s2, prepare_s3 from call_efast import run_efast, prepare_s2, prepare_s3
from ndvi import ( from ndvi import (
generate_ndvi_raw, generate_ndvi_raw,
create_ndvi_timeseries_raw, create_ndvi_timeseries_raw,
@ -12,8 +12,8 @@ from clouds import detect_clouds
def run_pipeline(season, site_position, site_name): def run_pipeline(season, site_position, site_name):
try: try:
print(f"Downloading data for {site_name}, {season}") # print(f"Downloading data for {site_name}, {season}")
download_s2(season, site_position, site_name) # download_s2(season, site_position, site_name)
# download_s3(season, site_position, site_name) # download_s3(season, site_position, site_name)
# print(f"Generating NDVI for raw data: {site_name}, {season}") # print(f"Generating NDVI for raw data: {site_name}, {season}")
@ -23,7 +23,7 @@ def run_pipeline(season, site_position, site_name):
# print(f"Detecting clouds for {site_name}, {season}") # print(f"Detecting clouds for {site_name}, {season}")
# detect_clouds(season, site_name) # detect_clouds(season, site_name)
# print(f"Preparing data for EFAST fusion for {site_name}, {season}") print(f"Preparing data for EFAST fusion for {site_name}, {season}")
# prepare_s2(season, site_position, site_name) # prepare_s2(season, site_position, site_name)
# prepare_s3(season, site_position, site_name) # prepare_s3(season, site_position, site_name)
@ -31,8 +31,8 @@ def run_pipeline(season, site_position, site_name):
# run_efast(season, site_position, site_name) # run_efast(season, site_position, site_name)
# print(f"Generating NDVI for prepared outputs: {site_name}, {season}") # print(f"Generating NDVI for prepared outputs: {site_name}, {season}")
# generate_ndvi_prepared(season, site_position, site_name) generate_ndvi_prepared(season, site_position, site_name)
# create_ndvi_timeseries_prepared(season, site_position, site_name) create_ndvi_timeseries_prepared(season, site_position, site_name)
except Exception as e: except Exception as e:
print(f"Error: {e}") print(f"Error: {e}")