opencv/cvat, voxel51/fiftyone

Possibly worth reviewing these open source tools for feature ideas, annotation UI workflows:
- opencv/cvat
- Src: https://github.com/opencv/cvat
- voxel51/fiftyone
- Src: https://github.com/voxel51/fiftyone
- Docs: https://voxel51.com/docs/fiftyone/
- Docs: https://voxel51.com/docs/fiftyone/tutorials/pandas_comparison.html
> While they apply to different types of data, the pandas DataFrame and FiftyOne Dataset classes share many similar functionalities. In this overview, we’ll present a side-by-side comparison of common operations in the two libraries.
- Docs: https://voxel51.com/docs/fiftyone/tutorials/evaluate_classifications.html

As well, NIRS Near Infrared Spectroscopy:
- https://en.wikipedia.org/wiki/Near-infrared_spectroscopy
- https://twitter.com/westurner/status/1617498999535149057
- From https://twitter.com/westurner/status/1609498590367420416 :
> Are there implied molecular structures that can be inferred from low-cost {NIRS, Light field, [...]} sensor data?
Task: Learn a function `f()` such that `f(lowcost_sensor_data) -> expensive_sensor_data`