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188 | def process_with_tiles(ept_file, tile_size, output_path, metric, voxel_size, buffer_size=0.1, srs=None, hag=False,
hag_dtm=False, dtm=None, bounds=None):
"""
Processes a large EPT point cloud by tiling, calculates CHM or other metrics for each tile,
and writes the results to the specified output path.
:param ept_file: Path to the EPT file containing the point cloud data.
:param tile_size: Tuple (tile_width, tile_height) specifying the size of each tile.
:param output_path: Directory where the output files will be saved.
:param metric: Metric to compute ("chm", "fhd", or "pai").
:param voxel_size: Tuple specifying the voxel resolution (x_resolution, y_resolution, z_resolution).
:param buffer_size: Fractional buffer size relative to tile size (e.g., 0.1 for 10% buffer).
:param srs: Spatial reference system (optional).
:param hag: Boolean indicating whether to compute Height Above Ground using Delaunay triangulation.
:param hag_dtm: Boolean indicating whether to compute Height Above Ground using a provided DTM raster.
:param dtm: Path to the DTM raster file (required if hag_dtm is True).
"""
min_x, max_x, min_y, max_y = get_bounds(ept_file)
num_tiles_x = int(np.ceil((max_x - min_x) / tile_size[0]))
num_tiles_y = int(np.ceil((max_y - min_y) / tile_size[1]))
total_tiles = num_tiles_x * num_tiles_y
if not os.path.exists(output_path):
os.makedirs(output_path)
with tqdm(total=total_tiles, desc="Processing tiles") as pbar:
for i in range(num_tiles_x):
for j in range(num_tiles_y):
if metric == "chm":
current_buffer_size = buffer_size
else:
current_buffer_size = 0.0
buffer_x = current_buffer_size * tile_size[0]
buffer_y = current_buffer_size * tile_size[1]
tile_min_x = min_x + i * tile_size[0] - buffer_x
tile_max_x = min_x + (i + 1) * tile_size[0] + buffer_x
tile_min_y = min_y + j * tile_size[1] - buffer_y
tile_max_y = min_y + (j + 1) * tile_size[1] + buffer_y
tile_min_x = max(min_x, tile_min_x)
tile_max_x = min(max_x, tile_max_x)
tile_min_y = max(min_y, tile_min_y)
tile_max_y = min(max_y, tile_max_y)
if tile_max_x <= tile_min_x or tile_max_y <= tile_min_y:
print(f"Warning: Skipping tile ({i}, {j}) due to invalid spatial extent.")
pbar.update(1)
continue
tile_pipeline_stages = [
{
"type": "filters.crop",
"bounds": f"([{tile_min_x},{tile_max_x}], [{tile_min_y},{tile_max_y}])"
}
]
if hag:
tile_pipeline_stages.append(_hag_delaunay())
elif hag_dtm:
if not dtm or not os.path.isfile(dtm):
raise FileNotFoundError(f"DTM file is required for HAG calculation using DTM: {dtm}")
tile_pipeline_stages.append(_hag_raster(dtm))
base_pipeline = {"type": "readers.ept", "filename": ept_file}
if bounds:
base_pipeline["bounds"] = f"{bounds}"
tile_pipeline_json = {
"pipeline": [base_pipeline] + tile_pipeline_stages
}
tile_pipeline = pdal.Pipeline(json.dumps(tile_pipeline_json))
tile_pipeline.execute()
tile_points = tile_pipeline.arrays[0]
if tile_points.size == 0:
print(f"Warning: No data in tile ({i}, {j}). Skipping.")
pbar.update(1)
continue
buffer_pixels_x = int(np.ceil(buffer_x / voxel_size[0]))
buffer_pixels_y = int(np.ceil(buffer_y / voxel_size[1]))
if metric == "chm":
chm, extent = calculate_chm(tile_points, voxel_size)
if buffer_pixels_x * 2 >= chm.shape[1] or buffer_pixels_y * 2 >= chm.shape[0]:
print(
f"Warning: Buffer size exceeds CHM dimensions for tile ({i}, {j}). Adjusting buffer size.")
buffer_pixels_x = max(0, chm.shape[1] // 2 - 1)
buffer_pixels_y = max(0, chm.shape[0] // 2 - 1)
chm = chm[buffer_pixels_y:-buffer_pixels_y, buffer_pixels_x:-buffer_pixels_x]
core_extent = (
tile_min_x + buffer_x,
tile_max_x - buffer_x,
tile_min_y + buffer_y,
tile_max_y - buffer_y,
)
result_file = os.path.join(output_path, f"tile_{i}_{j}_chm.tif")
create_geotiff(chm, result_file, srs, core_extent)
elif metric in ["fhd", "pai"]:
voxels, spatial_extent = assign_voxels(tile_points, voxel_size)
if metric == "fhd":
result = calculate_fhd(voxels)
elif metric == "pai":
pad = calculate_pad(voxels, voxel_size[-1])
if np.all(pad == 0):
result = np.zeros((pad.shape[0], pad.shape[1]))
else:
result = calculate_pai(pad)
result = np.where(np.isfinite(result), result, 0)
if current_buffer_size > 0:
if buffer_pixels_x * 2 >= result.shape[1] or buffer_pixels_y * 2 >= result.shape[0]:
print(
f"Warning: Buffer size exceeds {metric.upper()} dimensions for tile ({i}, {j}). Adjusting buffer size.")
buffer_pixels_x = max(0, result.shape[1] // 2 - 1)
buffer_pixels_y = max(0, result.shape[0] // 2 - 1)
result = result[buffer_pixels_y:-buffer_pixels_y, buffer_pixels_x:-buffer_pixels_x]
core_extent = (
tile_min_x + buffer_x,
tile_max_x - buffer_x,
tile_min_y + buffer_y,
tile_max_y - buffer_y,
)
if core_extent[1] <= core_extent[0] or core_extent[3] <= core_extent[2]:
print(f"Warning: Invalid core extent for tile ({i}, {j}): {core_extent}. Skipping.")
pbar.update(1)
continue
result_file = os.path.join(output_path, f"tile_{i}_{j}_{metric}.tif")
create_geotiff(result, result_file, srs, core_extent)
else:
raise ValueError(f"Unsupported metric: {metric}")
pbar.update(1)
|