use std::collections::HashMap;
use re_types::{
archetypes::SegmentationImage,
datatypes::{TensorBuffer, TensorData, TensorDimension},
Archetype as _, AsComponents as _,
};
mod util;
#[test]
fn segmentation_image_roundtrip() {
let all_expected = [SegmentationImage {
data: TensorData {
shape: vec![
TensorDimension {
size: 2,
name: Some("height".into()),
},
TensorDimension {
size: 3,
name: Some("width".into()),
},
],
buffer: TensorBuffer::U8(vec![1, 2, 3, 4, 5, 6].into()),
}
.into(),
draw_order: None,
}];
let all_arch_serialized = [SegmentationImage::try_from(ndarray::array![
[1u8, 2, 3],
[4, 5, 6]
])
.unwrap()
.to_arrow()
.unwrap()];
let expected_extensions: HashMap<_, _> = [("data", vec!["rerun.components.TensorData"])].into();
for (expected, serialized) in all_expected.into_iter().zip(all_arch_serialized) {
for (field, array) in &serialized {
eprintln!("{} = {array:#?}", field.name);
if false {
util::assert_extensions(
&**array,
expected_extensions[field.name.as_str()].as_slice(),
);
}
}
let deserialized = SegmentationImage::from_arrow(serialized).unwrap();
similar_asserts::assert_eq!(expected, deserialized);
}
}