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This repository was archived by the owner on Oct 31, 2023. It is now read-only.
This repository was archived by the owner on Oct 31, 2023. It is now read-only.

Cannot be reimplemented #14

Description

@Dandelionym
[19:56:29.655498] Loading dataset map (ball)
[19:56:29.940445] Loaded 0 categores for train
[19:56:29.940480] Loaded 1 categores for val
[19:56:29.945834] 1 categories loaded
[19:56:29.945937] containing 495 examples
[19:56:29.946329] 0 categories loaded
[19:56:29.946344] containing 0 examples
[19:56:29.946444] 1 categories loaded
[19:56:29.946513] containing 495 examples
[19:56:29.946606] Start training for 100 epochs
Backend QtAgg is interactive backend. Turning interactive mode on.
[19:56:39.632502] Epoch 0:

Process finished with exit code 139 (interrupted by signal 11: SIGSEGV)

No training data was found.
[19:56:29.940445] Loaded 0 categories for train

1. What I did

dict_keys(['train_known', 'train_unseen', 'test_known', 'test_unseen'])

/home/.../lib/python3.8/site-packages/pytorch3d/implicitron/dataset/json_index_dataset_map_provider_v2.py:327: UserWarning: 
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
Some eval batches are missing from the test dataset.
The evaluation results will be incomparable to the
evaluation results calculated on the original dataset.
@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
  warnings.warn(

Process finished with exit code 0

**Could you please reclaim the data installation? I tried several times but failed. Lots of problems exist. **

Before this, I downloaded the sub-dataset 'ball', then I modified the data dir as shown following json_index_dataset_map_provider_v2:

        self.dataset_root
            ├── <category_0>
            │   ├── <sequence_name_0>
            │   │   ├── depth_masks
            │   │   ├── depths
            │   │   ├── images
            │   │   ├── masks
            │   │   └── pointcloud.ply
            │   ├── <sequence_name_1>
            │   │   ├── depth_masks
            │   │   ├── depths
            │   │   ├── images
            │   │   ├── masks
            │   │   └── pointcloud.ply
            │   ├── ...
            │   ├── <sequence_name_N>
            │   ├── set_lists
            │       ├── set_lists_<subset_name_0>.json
            │       ├── set_lists_<subset_name_1>.json
            │       ├── ...
            │       ├── set_lists_<subset_name_M>.json
            │   ├── eval_batches
            │   │   ├── eval_batches_<subset_name_0>.json
            │   │   ├── eval_batches_<subset_name_1>.json
            │   │   ├── ...
            │   │   ├── eval_batches_<subset_name_M>.json
            │   ├── frame_annotations.jgz
            │   ├── sequence_annotations.jgz
            ├── <category_1>
            ├── ...
            ├── <category_K>

Then the key of the json file is not correct in terms of train, val and test.

2. Suggestion

Could you please give clearer instructions for data preparation?

Thanks a lot!

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