import buteo as beo

OUTDIR = "path/to/output/dir"

vector_file_correct_projection = "path/to/vector/file.gpkg"
raster_files_wrong_projection = "path/to/raster/files/*.tif:glob"

paths_to_reprojected_rasters = beo.reproject_raster(
    raster_files_with_wrong_projection,
    vector_file_with_correct_projection,
    out_path=outdir
)

paths_to_reprojected_rasters
>>> [path/to/output/dir/file1.tif, path/to/output/dir/file2.tif, ...]

import buteo as beo

SRCDIR = "path/to/src/dir/"

paths_to_aligned_rasters_in_memory = beo.align_rasters(
    SRCDIR + "*.tif:glob",
)

stacked_numpy_arrays = beo.raster_to_array(
    paths_to_aligned_rasters_in_memory,
)

patches = beo.array_to_patches(
    stacked_numpy_arrays,
    256,
    offsets_y=1, # 1 overlap at 1/2 patch size (128)
    offsets_x=1, # 1 overlap at 1/2 patch size (128)
)

# patches_nr, height, width, channels
patches
>>> np.ndarray([10000, 256, 256, 9])

import buteo as beo

RASTER_PATH = "path/to/raster/raster.tif"
RASTER_OUT_PATH = "path/to/raster/raster_pred.tif"

array = beo.raster_to_array(RASTER_PATH)

callback = model.predict # from pytorch, keras, etc..

# Predict the raster using overlaps, and borders.
# Merge using different methods. (median, mad, mean, mode, ...)
predicted = predict_array(
    array,
    callback,
    tile_size=256,
)

# Write the predicted raster to disk
beo.array_to_raster(
    predicted,
    reference=RASTER_PATH,
    out_path=RASTER_OUT_PATH,
)
# Path to the predicted raster
>>> "path/to/raster/raster_pred.tif"