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Support any
dtype
for depth images (#2602)
Closes #2550 * #2550 ### What Support any `dtype` for depth images. Previously only `uint16` and `float32` were supported. This also unifies the textures used for depth cloud projection and for displaying images ("rectangle" shader). This means less time spent uploading data to the GPU, half the GPU memory used, and less room for bugs and inconsistencies. I also took an unrelated pass at reducing log spam when running with `RUST_LOG=debug`. Example of using `float16`: ![image](https://github.com/rerun-io/rerun/assets/1148717/579b61af-6554-4c8c-b894-81b134a34d5c) ### Checklist * [x] I have read and agree to [Contributor Guide](https://github.com/rerun-io/rerun/blob/main/CONTRIBUTING.md) and the [Code of Conduct](https://github.com/rerun-io/rerun/blob/main/CODE_OF_CONDUCT.md) * [x] I've included a screenshot or gif (if applicable) * [x] I have tested [demo.rerun.io](https://demo.rerun.io/pr/2602) (if applicable) - [PR Build Summary](https://build.rerun.io/pr/2602) - [Docs preview](https://rerun.io/preview/pr%3Aemilk%2Fgeneralize-depth-texture/docs) - [Examples preview](https://rerun.io/preview/pr%3Aemilk%2Fgeneralize-depth-texture/examples)
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Possible performance regression was detected for benchmark 'Rust Benchmark'.
Benchmark result of this commit is worse than the previous benchmark result exceeding threshold
1.25
.datastore/num_rows=1000/num_instances=1000/packed=false/insert/default
3866239
ns/iter (± 56375
)2815199
ns/iter (± 70928
)1.37
datastore/num_rows=1000/num_instances=1000/packed=false/range/default
3997107
ns/iter (± 75227
)2738743
ns/iter (± 71477
)1.46
mono_points_arrow/generate_message_bundles
38086572
ns/iter (± 211883
)28209476
ns/iter (± 952493
)1.35
mono_points_arrow/decode_message_bundles
77011809
ns/iter (± 248511
)57597950
ns/iter (± 729698
)1.34
mono_points_arrow_batched/generate_messages
7609796
ns/iter (± 237895
)3557183
ns/iter (± 78251
)2.14
mono_points_arrow_batched/encode_log_msg
514104
ns/iter (± 2566
)408471
ns/iter (± 10222
)1.26
mono_points_arrow_batched/encode_total
42463451
ns/iter (± 792461
)22528081
ns/iter (± 539577
)1.88
mono_points_arrow_batched/decode_total
10672335
ns/iter (± 373336
)7563681
ns/iter (± 183688
)1.41
batch_points_arrow/encode_log_msg
90913
ns/iter (± 686
)47274
ns/iter (± 1152
)1.92
This comment was automatically generated by workflow using github-action-benchmark.