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--- |
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language: |
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- en |
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tags: |
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- robotics |
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--- |
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## EgoPAT3Dv2 |
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### Dataset introduction |
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There are **11 scenes** contained in the EgoPAT3Dv2 dataset, corresponding to folders 1 through 11. Each scene folder contains 2 to 6 video folders, and each video folder contains an **RGB** folder, a **depth** folder, a **point cloud** folder and a **transformation matrices** folder. (Please ignore other folders or files inside the zip file.) The annotations (ground truth) and transformation matrices (the same as the transformation matrices above) are included in the annotation_transformation.hdf5 file. We use HDF5 to organize the dataset in the experiment, and the dataloader in the GitHub repo is also written correspondingly. |
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### Dataset folder hierarchy |
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```bash |
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Dataset/ |
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├── 1 # scene 1 |
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├── 1.1.zip -> 1.1 # video 1 in scene 1 |
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├── d2rgb # depth files |
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├── color # rgb files |
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├── pointcloud # point cloud files |
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└── transformation # transformation matrices |
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├── 1.2.zip -> 1.2 # share the same structure as 1.1 |
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├── ... |
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└── 1.4.zip -> 1.4 |
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├── 2/ # all scene/video directories share the same structure as above |
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└── ... |
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. |
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. |
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. |
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└── 11 |
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``` |
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## Construct HDF5 dataset file |
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Since 50GB is the hard limit for single file size in huggingface, please use [make_RGB_dataset.py](https://huggingface.co/datasets/ai4ce/EgoPAT3Dv2/blob/main/make_RGB_dataset.py) to construct the HDF5 file on your own. |
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1. Download all zipped files. Unzip them and keep RGB("color" in the folder) folder in each video folder only. |
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2. Run `make_RGB_dataset.py` after step 1. |
