6 Commits

Author SHA1 Message Date
David Novotny
5add065f8a Readme updates
Summary:
Running:
- clearly points users to experiment.py/visualize_reconstruction.py
Reproducing:
- Adds NeRF training on Blender
- Adds CO3Dv2 configs

Reviewed By: bottler

Differential Revision: D41534315

fbshipit-source-id: e85f5f1eafed8c35c9e91d748a04f238509cf8ec
2022-11-30 07:02:01 -08:00
David Novotny
597bc7c7f6 Blender config fixes
Summary: Fixes the blender synthetic configs.

Reviewed By: kjchalup

Differential Revision: D38786095

fbshipit-source-id: 6d0784ced41a3f2904f074221108cdb56bd20e7f
2022-08-19 06:03:34 -07:00
Jeremy Reizenstein
a39cad40f4 LinearExponential LR
Summary: Linear followed by exponential LR progression. Needed for making Blender scenes converge.

Reviewed By: kjchalup

Differential Revision: D38557007

fbshipit-source-id: ad630dbc5b8fabcb33eeb5bdeed5e4f31360bac2
2022-08-09 18:18:46 -07:00
Krzysztof Chalupka
c83ec3555d Mods and bugfixes for LLFF and Blender repros
Summary:
LLFF (and most/all non-synth datasets) will have no background/foreground distinction. Add support for data with no fg mask.

Also, we had a bug in stats loading, like this:
  * Load stats
  * One of the stats has a history of length 0
  * That's fine, e.g. maybe it's fg_error but the dataset has no notion of fg/bg. So leave it as len 0
  * Check whether all the stats have the same history length as an arbitrarily chosen "reference-stat"
  * Ooops the reference-stat happened to be the stat with length 0
  * assert (legit_stat_len == reference_stat_len (=0)) ---> failed assert

Also some minor fixes (from Jeremy's other diff) to support LLFF

Reviewed By: davnov134

Differential Revision: D38475272

fbshipit-source-id: 5b35ac86d1d5239759f537621f41a3aa4eb3bd68
2022-08-09 15:04:44 -07:00
Krzysztof Chalupka
760305e044 Fix test evaluation for Blender data
Summary: Blender data doesn't have depths or crops.

Reviewed By: shapovalov

Differential Revision: D38345583

fbshipit-source-id: a19300daf666bbfd799d0038aeefa14641c559d7
2022-08-02 12:40:21 -07:00
Krzysztof Chalupka
1b0584f7bd Replace pluggable components to create a proper Configurable hierarchy.
Summary:
This large diff rewrites a significant portion of Implicitron's config hierarchy. The new hierarchy, and some of the default implementation classes, are as follows:
```
Experiment
    data_source: ImplicitronDataSource
        dataset_map_provider
        data_loader_map_provider
    model_factory: ImplicitronModelFactory
        model: GenericModel
    optimizer_factory: ImplicitronOptimizerFactory
    training_loop: ImplicitronTrainingLoop
        evaluator: ImplicitronEvaluator
```

1) Experiment (used to be ExperimentConfig) is now a top-level Configurable and contains as members mainly (mostly new) high-level factory Configurables.
2) Experiment's job is to run factories, do some accelerate setup and then pass the results to the main training loop.
3) ImplicitronOptimizerFactory and ImplicitronModelFactory are new high-level factories that create the optimizer, scheduler, model, and stats objects.
4) TrainingLoop is a new configurable that runs the main training loop and the inner train-validate step.
5) Evaluator is a new configurable that TrainingLoop uses to run validation/test steps.
6) GenericModel is not the only model choice anymore. Instead, ImplicitronModelBase (by default instantiated with GenericModel) is a member of Experiment and can be easily replaced by a custom implementation by the user.

All the new Configurables are children of ReplaceableBase, and can be easily replaced with custom implementations.

In addition, I added support for the exponential LR schedule, updated the config files and the test, as well as added a config file that reproduces NERF results and a test to run the repro experiment.

Reviewed By: bottler

Differential Revision: D37723227

fbshipit-source-id: b36bee880d6aa53efdd2abfaae4489d8ab1e8a27
2022-07-29 17:32:51 -07:00