def worker(tile_key):
if len(tiles_map[tile_key]) == 1:
return
image = np.zeros((width, height, bands), np.uint8)
x, y, z = map(int, tile_key)
for i in range(len(tiles_map[tile_key])):
root = os.path.join(splits_path, str(i))
_, path = tile_from_xyz(root, x, y, z)
if not args.label:
split = tile_image_from_file(path)
if args.label:
split = tile_label_from_file(path)
split = split.reshape((width, height, 1)) # H,W -> H,W,C
assert image.shape == split.shape
image[np.where(image == 0)] += split[np.where(image == 0)]
if not args.label and is_nodata(image, args.nodata, args.nodata_threshold, args.keep_borders):
progress.update()
return
tile = mercantile.Tile(x=x, y=y, z=z)
if not args.label:
tile_image_to_file(args.out, tile, image)
if args.label:
tile_label_to_file(args.out, tile, palette, image)
progress.update()
return tile
def worker(tile_key, nodata):
if len(tiles_map[tile_key]) == 1:
return
image = np.zeros((args.ts, args.ts, bands), np.uint8)
x, y, z = map(int, tile_key)
for i in range(len(tiles_map[tile_key])):
root = os.path.join(splits_path, str(i))
_, path = tile_from_xyz(root, x, y, z)
if not args.label:
split = tile_image_from_file(path)
if args.label:
split = tile_label_from_file(path)
split = split.reshape(
(args.ts, args.ts, 1)) # H,W -> H,W,C
assert image.shape == split.shape
image[:, :, :] += split[:, :, :]
if not args.label and skip_nodata(image, nodata["border"],
nodata["value"],
nodata["threshold"]):
progress.update()
return
tile = mercantile.Tile(x=x, y=y, z=z)
if not args.label:
ret = tile_image_to_file(args.out, tile, image)
if args.label:
ret = tile_label_to_file(args.out, tile, palette, image)
if not ret:
sys.exit("Error: Unable to write tile {}.".format(
str(tile_key)))
progress.update()
return tile
def worker(tile_key):
if len(tiles_map[tile_key]) == 1:
return
image = np.zeros((args.ts, args.ts, bands), np.uint8)
x, y, z = map(int, tile_key)
for i in range(len(tiles_map[tile_key])):
root = os.path.join(splits_path, str(i))
_, path = tile_from_xyz(root, x, y, z)
if not args.label:
split = tile_image_from_file(path)
if args.label:
split = tile_label_from_file(path)
split = split.reshape(
(args.ts, args.ts, 1)) # H,W -> H,W,C
assert image.shape == split.shape
image[np.where(image == 0)] += split[np.where(image == 0)]
if not args.label and is_nodata(image,
threshold=args.nodata_threshold):
progress.update()
return
tile = mercantile.Tile(x=x, y=y, z=z)
if not args.label:
ret = tile_image_to_file(args.out, tile, image)
if args.label:
ret = tile_label_to_file(args.out, tile, palette, image)
assert ret, "Unable to write tile {} from raster {}.".format(
str(tile_key))
progress.update()
return tile
def __getitem__(self, i):
tile = None
mask = None
image = None
for channel in self.config["channels"]:
image_channel = None
bands = None if not channel["bands"] else channel["bands"]
if tile is None:
tile, path = self.tiles[channel["name"]][i]
else:
assert tile == self.tiles[
channel["name"]][i][0], "Dataset channel inconsistency"
tile, path = self.tiles[channel["name"]][i]
image_channel = tile_image_from_file(path, bands)
assert image_channel is not None, "Dataset channel {} not retrieved: {}".format(
channel["name"], path)
image = np.concatenate(
(image, image_channel),
axis=2) if image is not None else image_channel
if self.mode == "train":
assert tile == self.tiles["labels"][i][
0], "Dataset mask inconsistency"
mask = tile_label_from_file(self.tiles["labels"][i][1])
assert mask is not None, "Dataset mask not retrieved"
image, mask = to_normalized_tensor(self.config, self.shape_in[1:3],
self.mode, image, mask)
return image, mask, tile
if self.mode == "predict":
image = to_normalized_tensor(self.config, self.shape_in[1:3],
self.mode, image)
return image, torch.IntTensor([tile.x, tile.y, tile.z])