Datasets:
Size:
10K<n<100K
License:
File size: 3,266 Bytes
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import io
from PIL import Image
from datasets import GeneratorBasedBuilder, DatasetInfo, Features, SplitGenerator, Value, Array2D, Split
import datasets
import numpy as np
import h5py
class CustomConfig(datasets.BuilderConfig):
def __init__(self, **kwargs):
super(CustomConfig, self).__init__(**kwargs)
self.dataset_type = kwargs.pop("name", "all")
class RGBSemanticDepthDataset(GeneratorBasedBuilder):
BUILDER_CONFIGS = [
CustomConfig(name="all", version="1.0.0", description="all"),
CustomConfig(name="depth", version="1.0.0", description="depth"),
CustomConfig(name="seg", version="1.0.0", description="segmentation"),
] # Configs initialization
BUILDER_CONFIG_CLASS = CustomConfig
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, type_dataset):
# Reference: https://github.com/dwofk/fast-depth/blob/master/dataloaders/dataloader.py#L8-L13
f = io.BytesIO(bytes_stream)
h5f = h5py.File(f, "r")
print(type_dataset)
left_rgb = self._read_jpg(h5f['rgb_left'][:])
if type_dataset == 'depth':
right_rgb = self._read_jpg(h5f['rgb_right'][:])
left_depth = h5f['depth_left'][:].astype(np.float32)
right_depth = h5f['depth_right'][:].astype(np.float32)
return left_rgb, right_rgb, np.zeros((1,1)), left_depth, right_depth
elif type_dataset == 'seg':
left_seg = h5f['seg_left'][:]
return left_rgb, np.zeros((1,1)), left_seg, np.zeros((1,1)), np.zeros((1,1))
else:
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)
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_1730238419.175364.tar"]})
return [
SplitGenerator(
name=Split.TRAIN,
gen_kwargs={
"archives": [dl_manager.iter_archive(archive) for archive in archives["train"]],
},
),
]
def _generate_examples(self, archives):
print(self.config.dataset_type)
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(), self.config.dataset_type)
yield path, {
"left_rgb": left_rgb,
"right_rgb": right_rgb,
"left_seg": left_seg,
"left_depth": left_depth,
"right_depth": right_depth,
} |