kopia lustrzana https://github.com/OpenDroneMap/ODM
Piero Toffanin
rodzic
61fc871ca2
commit
6e0440b559
|
|
@ -6,7 +6,10 @@ from opendm.concurrency import get_max_memory
|
|||
import math
|
||||
import numpy as np
|
||||
import rasterio
|
||||
import fiona
|
||||
from scipy import ndimage
|
||||
from rasterio.transform import Affine, rowcol
|
||||
from rasterio.mask import mask
|
||||
from opendm import io
|
||||
|
||||
def get_orthophoto_vars(args):
|
||||
|
|
@ -49,7 +52,49 @@ def post_orthophoto_steps(args, bounds_file_path, orthophoto_file):
|
|||
if args.orthophoto_png:
|
||||
generate_png(orthophoto_file)
|
||||
|
||||
def merge(input_ortho_and_cutlines, output_orthophoto, blend_distance=20, orthophoto_vars={}):
|
||||
|
||||
def compute_mask_raster(input_raster, vector_mask, output_raster, blend_distance=20, only_max_coords_feature=False):
|
||||
if not os.path.exists(input_raster):
|
||||
log.ODM_WARNING("Cannot mask raster, %s does not exist" % input_raster)
|
||||
return
|
||||
|
||||
if not os.path.exists(vector_mask):
|
||||
log.ODM_WARNING("Cannot mask raster, %s does not exist" % vector_mask)
|
||||
return
|
||||
|
||||
with rasterio.open(input_raster, 'r') as rast:
|
||||
with fiona.open(vector_mask) as src:
|
||||
burn_features = src
|
||||
|
||||
if only_max_coords_feature:
|
||||
max_coords_count = 0
|
||||
max_coords_feature = None
|
||||
for feature in src:
|
||||
if feature is not None:
|
||||
# No complex shapes
|
||||
if len(feature['geometry']['coordinates'][0]) > max_coords_count:
|
||||
max_coords_count = len(feature['geometry']['coordinates'][0])
|
||||
max_coords_feature = feature
|
||||
if max_coords_feature is not None:
|
||||
burn_features = [max_coords_feature]
|
||||
|
||||
shapes = [feature["geometry"] for feature in burn_features]
|
||||
out_image, out_transform = mask(rast, shapes, nodata=0)
|
||||
|
||||
if blend_distance > 0:
|
||||
alpha_band = out_image[3]
|
||||
dist_t = ndimage.distance_transform_edt(alpha_band)
|
||||
dist_t[dist_t <= blend_distance] /= blend_distance
|
||||
dist_t[dist_t > blend_distance] = 1
|
||||
np.multiply(alpha_band, dist_t, out=alpha_band, casting="unsafe")
|
||||
|
||||
with rasterio.open(output_raster, 'w', **rast.profile) as dst:
|
||||
dst.write(out_image)
|
||||
|
||||
return output_raster
|
||||
|
||||
|
||||
def merge(input_ortho_and_ortho_cuts, output_orthophoto, orthophoto_vars={}):
|
||||
"""
|
||||
Based on https://github.com/mapbox/rio-merge-rgba/
|
||||
Merge orthophotos around cutlines using a blend buffer.
|
||||
|
|
@ -58,7 +103,7 @@ def merge(input_ortho_and_cutlines, output_orthophoto, blend_distance=20, orthop
|
|||
bounds=None
|
||||
precision=7
|
||||
|
||||
for o, c in input_ortho_and_cutlines:
|
||||
for o, c in input_ortho_and_ortho_cuts:
|
||||
if not io.file_exists(o):
|
||||
log.ODM_WARNING("%s does not exist. Will skip from merged orthophoto." % o)
|
||||
continue
|
||||
|
|
@ -72,24 +117,23 @@ def merge(input_ortho_and_cutlines, output_orthophoto, blend_distance=20, orthop
|
|||
return
|
||||
|
||||
with rasterio.open(inputs[0][0]) as first:
|
||||
src_nodata = first.nodatavals[0] # TODO: this is None
|
||||
res = first.res
|
||||
dtype = first.dtypes[0]
|
||||
profile = first.profile
|
||||
|
||||
log.ODM_INFO("%s valid orthophoto rasters to merge" % len(inputs))
|
||||
sources = [(rasterio.open(o)) for o,_ in inputs]
|
||||
sources = [(rasterio.open(o), rasterio.open(c)) for o,c in inputs]
|
||||
|
||||
# scan input files.
|
||||
# while we're at it, validate assumptions about inputs
|
||||
xs = []
|
||||
ys = []
|
||||
for src in sources:
|
||||
for src, _ in sources:
|
||||
left, bottom, right, top = src.bounds
|
||||
xs.extend([left, right])
|
||||
ys.extend([bottom, top])
|
||||
# if src.profile["count"] != 1 or src.profile["count"] != 1:
|
||||
# raise ValueError("Inputs must be 1-band rasters")
|
||||
if src.profile["count"] != 4:
|
||||
raise ValueError("Inputs must be 4-band rasters")
|
||||
dst_w, dst_s, dst_e, dst_n = min(xs), min(ys), max(xs), max(ys)
|
||||
log.ODM_INFO("Output bounds: %r %r %r %r" % (dst_w, dst_s, dst_e, dst_n))
|
||||
|
||||
|
|
@ -115,7 +159,6 @@ def merge(input_ortho_and_cutlines, output_orthophoto, blend_distance=20, orthop
|
|||
profile["compress"] = orthophoto_vars.get('COMPRESS', 'LZW')
|
||||
profile["predictor"] = orthophoto_vars.get('PREDICTOR', '2')
|
||||
profile["bigtiff"] = orthophoto_vars.get('BIGTIFF', 'IF_SAFER')
|
||||
profile["nodata"] = src_nodata
|
||||
profile.update()
|
||||
|
||||
# create destination file
|
||||
|
|
@ -130,23 +173,10 @@ def merge(input_ortho_and_cutlines, output_orthophoto, blend_distance=20, orthop
|
|||
dst_count = first.count
|
||||
dst_shape = (dst_count, dst_rows, dst_cols)
|
||||
|
||||
# First pass, write all rasters naively
|
||||
dstarr = np.zeros(dst_shape, dtype=dtype)
|
||||
distsum = np.zeros(dst_shape, dtype=dtype)
|
||||
|
||||
for src in sources:
|
||||
# The full_cover behavior is problematic here as it includes
|
||||
# extra pixels along the bottom right when the sources are
|
||||
# slightly misaligned
|
||||
#
|
||||
# src_window = get_window(left, bottom, right, top,
|
||||
# src.transform, precision=precision)
|
||||
#
|
||||
# With rio merge this just adds an extra row, but when the
|
||||
# imprecision occurs at each block, you get artifacts
|
||||
|
||||
nodata = src.nodatavals[0]
|
||||
|
||||
# Alternative, custom get_window using rounding
|
||||
for src, _ in sources:
|
||||
src_window = tuple(zip(rowcol(
|
||||
src.transform, left, top, op=round, precision=precision
|
||||
), rowcol(
|
||||
|
|
@ -168,6 +198,25 @@ def merge(input_ortho_and_cutlines, output_orthophoto, blend_distance=20, orthop
|
|||
if np.count_nonzero(dstarr[3]) == blocksize:
|
||||
break
|
||||
|
||||
# Second pass, write cut rasters
|
||||
for _, cut in sources:
|
||||
src_window = tuple(zip(rowcol(
|
||||
cut.transform, left, top, op=round, precision=precision
|
||||
), rowcol(
|
||||
cut.transform, right, bottom, op=round, precision=precision
|
||||
)))
|
||||
|
||||
temp = np.zeros(dst_shape, dtype=dtype)
|
||||
temp = cut.read(
|
||||
out=temp, window=src_window, boundless=True, masked=False
|
||||
)
|
||||
|
||||
# For each band, average alpha values between
|
||||
# destination raster and cut raster
|
||||
for b in range(0, 3):
|
||||
blended = temp[3] / 255.0 * temp[b] + (1 - temp[3] / 255.0) * dstarr[b]
|
||||
np.copyto(dstarr[b], blended, casting='unsafe', where=temp[3]!=0)
|
||||
|
||||
dstrast.write(dstarr, window=dst_window)
|
||||
|
||||
return output_orthophoto
|
||||
|
|
|
|||
|
|
@ -501,6 +501,7 @@ class ToolchainTask(Task):
|
|||
"opensfm/exif/empty"],
|
||||
outputs=["odm_orthophoto/odm_orthophoto.tif",
|
||||
"odm_orthophoto/cutline.gpkg",
|
||||
"odm_orthophoto/odm_orthophoto_cut.tif",
|
||||
"odm_dem",
|
||||
"odm_georeferencing"])
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -108,13 +108,19 @@ class ODMOrthoPhotoStage(types.ODM_Stage):
|
|||
# Cutline computation, before cropping
|
||||
# We want to use the full orthophoto, not the cropped one.
|
||||
if args.orthophoto_cutline:
|
||||
cutline_file = os.path.join(tree.odm_orthophoto, "cutline.gpkg")
|
||||
|
||||
compute_cutline(tree.odm_orthophoto_tif,
|
||||
bounds_file_path,
|
||||
os.path.join(tree.odm_orthophoto, "cutline.gpkg"),
|
||||
cutline_file,
|
||||
args.max_concurrency,
|
||||
tmpdir=os.path.join(tree.odm_orthophoto, "grass_cutline_tmpdir"),
|
||||
scale=0.25)
|
||||
|
||||
orthophoto.compute_mask_raster(tree.odm_orthophoto_tif, cutline_file,
|
||||
os.path.join(tree.odm_orthophoto, "odm_orthophoto_cut.tif"),
|
||||
blend_distance=20, only_max_coords_feature=True)
|
||||
|
||||
orthophoto.post_orthophoto_steps(args, bounds_file_path, tree.odm_orthophoto_tif)
|
||||
|
||||
geotiffcreated = True
|
||||
|
|
|
|||
|
|
@ -217,72 +217,22 @@ class ODMMergeStage(types.ODM_Stage):
|
|||
system.mkdir_p(tree.odm_orthophoto)
|
||||
|
||||
if not io.file_exists(tree.odm_orthophoto_tif) or self.rerun():
|
||||
all_orthos_and_cutlines = get_all_submodel_paths(tree.submodels_path,
|
||||
all_orthos_and_ortho_cuts = get_all_submodel_paths(tree.submodels_path,
|
||||
os.path.join("odm_orthophoto", "odm_orthophoto.tif"),
|
||||
os.path.join("odm_orthophoto", "cutline.gpkg"),
|
||||
os.path.join("odm_orthophoto", "odm_orthophoto_cut.tif"),
|
||||
)
|
||||
|
||||
if len(all_orthos_and_cutlines) > 1:
|
||||
if len(all_orthos_and_ortho_cuts) > 1:
|
||||
log.ODM_INFO("Found %s submodels with valid orthophotos and cutlines" % len(all_orthos_and_cutlines))
|
||||
|
||||
# TODO: histogram matching via rasterio
|
||||
# currently parts have different color tones
|
||||
|
||||
merged_geotiff = os.path.join(tree.odm_orthophoto, "odm_orthophoto.merged.tif")
|
||||
|
||||
kwargs = {
|
||||
'orthophoto_merged': merged_geotiff,
|
||||
'input_files': ' '.join(map(lambda i: quote(i[0]), all_orthos_and_cutlines)),
|
||||
'max_memory': get_max_memory(),
|
||||
'threads': args.max_concurrency,
|
||||
}
|
||||
|
||||
# use bounds as cutlines (blending)
|
||||
if io.file_exists(merged_geotiff):
|
||||
os.remove(merged_geotiff)
|
||||
|
||||
system.run('gdal_merge.py -o {orthophoto_merged} '
|
||||
#'-createonly '
|
||||
'-co "BIGTIFF=YES" '
|
||||
'-co "BLOCKXSIZE=512" '
|
||||
'-co "BLOCKYSIZE=512" '
|
||||
'--config GDAL_CACHEMAX {max_memory}% '
|
||||
'{input_files} '.format(**kwargs)
|
||||
)
|
||||
|
||||
for ortho_cutline in all_orthos_and_cutlines:
|
||||
kwargs['input_file'], kwargs['cutline'] = ortho_cutline
|
||||
|
||||
# Note: cblend has a high performance penalty
|
||||
system.run('gdalwarp -cutline {cutline} '
|
||||
'-cblend 20 '
|
||||
'-r bilinear -multi '
|
||||
'-wo NUM_THREADS={threads} '
|
||||
'--config GDAL_CACHEMAX {max_memory}% '
|
||||
'{input_file} {orthophoto_merged}'.format(**kwargs)
|
||||
)
|
||||
|
||||
# Apply orthophoto settings (compression, tiling, etc.)
|
||||
orthophoto_vars = orthophoto.get_orthophoto_vars(args)
|
||||
|
||||
if io.file_exists(tree.odm_orthophoto_tif):
|
||||
os.remove(tree.odm_orthophoto_tif)
|
||||
|
||||
kwargs = {
|
||||
'vars': ' '.join(['-co %s=%s' % (k, orthophoto_vars[k]) for k in orthophoto_vars]),
|
||||
'max_memory': get_max_memory(),
|
||||
'merged': merged_geotiff,
|
||||
'log': tree.odm_orthophoto_tif_log,
|
||||
'orthophoto': tree.odm_orthophoto_tif,
|
||||
}
|
||||
|
||||
system.run('gdal_translate '
|
||||
'{vars} '
|
||||
'--config GDAL_CACHEMAX {max_memory}% '
|
||||
'{merged} {orthophoto} > {log}'.format(**kwargs))
|
||||
|
||||
os.remove(merged_geotiff)
|
||||
|
||||
orthophoto_vars = orthophoto.get_orthophoto_vars(args)
|
||||
orthophoto.merge(all_orthos_and_ortho_cuts, tree.odm_orthophoto_tif, orthophoto_vars)
|
||||
orthophoto.post_orthophoto_steps(args, merged_bounds_file, tree.odm_orthophoto_tif)
|
||||
elif len(all_orthos_and_cutlines) == 1:
|
||||
# Simply copy
|
||||
|
|
|
|||
Ładowanie…
Reference in New Issue