Datasets:
Size:
10K<n<100K
License:
import io | |
from PIL import Image | |
from datasets import GeneratorBasedBuilder, DatasetInfo, Features, SplitGenerator, Value, Array2D, Split | |
import datasets | |
import OpenEXR | |
import Imath | |
import numpy as np | |
import h5py | |
class RGBSemanticDepthDataset(GeneratorBasedBuilder): | |
def _info(self): | |
return DatasetInfo( | |
features=Features({ | |
"left_rgb": datasets.Image(), | |
"right_rgb": datasets.Image(), | |
"left_seg": datasets.Image(), | |
"left_depth": datasets.Image(), | |
"right_depth": datasets.Image(), | |
}) | |
) | |
def _h5_loader(self, bytes_stream): | |
# Reference: https://github.com/dwofk/fast-depth/blob/master/dataloaders/dataloader.py#L8-L13 | |
f = io.BytesIO(bytes_stream) | |
h5f = h5py.File(f, "r") | |
left_rgb = self._read_jpg(h5f['rgb_left']) | |
right_rgb = self._read_jpg(h5f['rgb_right']) | |
left_seg = h5f['seg_left'] | |
left_depth = h5f['depth_left'].astype(np.float32) | |
right_depth = h5f['depth_right'].astype(np.float32) | |
print(left_rgb.shape, left_depth.shape, left_seg.shape) | |
return left_rgb, right_rgb, left_seg, left_depth, right_depth | |
def _read_jpg(self, bytes_stream): | |
return Image.open(io.BytesIO(bytes_stream)) | |
def _split_generators(self, dl_manager): | |
archives = dl_manager.download({"train":["data/images_1729368304.063240.tar"]}) | |
return [ | |
SplitGenerator( | |
name=Split.TRAIN, | |
gen_kwargs={ | |
"archives": [dl_manager.iter_archive(archive) for archive in archives["train"]], | |
}, | |
), | |
] | |
def _generate_examples(self, archives): | |
for archive in archives: | |
for path, file in archive: | |
print(path) | |
left_rgb, right_rgb, left_seg, left_depth, right_depth = self._h5_loader(file.read()) | |
yield path, { | |
"left_rgb": left_rgb, | |
"right_rgb": right_rgb, | |
"left_seg": left_seg, | |
"left_depth": left_depth, | |
"right_depth": right_depth, | |
} |