## ROBOPROX dataset — transparent_meagapose_finetune_HF

This document provides the Data/Code metadata for the dataset distributed in this repository following the ROBOPROX template.

---

1. Contributors
   - [Add contributor names and affiliations here]
   - Contact: [maintainer email or GitHub handle]

2. Description of data/code
   - This dataset contains rendered PBR data and supporting metadata for training and fine-tuning pose-estimation and related models focused on transparent objects. The repository contains:
     - `dataset/camera.json` — camera intrinsics/extrinsics used across renders (summary file)
     - `dataset/meshes/` — mesh assets and `models_info.json` describing models
     - `dataset/train_pbr/` — multiple numeric scene/sequence folders (e.g. `000000`, `000001`, ...)
     - `scripts/upload_dataset.py` — helper script (if present) used for uploading or processing the dataset

   - Each numeric folder under `train_pbr/` contains one rendered sequence (images and associated per-frame metadata). The structure is intentionally modular so sequences can be streamed for training.

3. Date of creation / date of analysis
   - Dataset generation date: [add original creation date(s) here]
   - README created: 2025-11-06 (this file)
   - Date of analysis: [add date(s) when dataset was analyzed, if applicable]

4. Raw vs analyzed
   - The data uploaded here are the raw rendered outputs and supporting metadata (meshes, camera file, per-sequence folders). No analysis/aggregation results are included unless noted.

5. License of the data/code
   - Recommended license: CC-BY 4.0 International
   - If CC-BY 4.0 is acceptable, please include a `LICENSE` file with the full CC-BY 4.0 text. Example short statement:
     "This dataset is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Users are free to share and adapt the material provided they give appropriate credit."

6. Connected publications
   - If this dataset is associated with a paper, add DOI(s) or persistent identifiers (PID) here.
   - Placeholder: [Add DOI/URL to connected publication]

7. Funding information
   - This work was supported by the European Union under the project Robotics and advanced industrial production (reg. no. CZ.02.01.01/00/22_008/0004590).

8. Naming convention of files and folders
   - Top-level layout (relative to repo root):
     - `dataset/`
         - `camera.json` — global camera metadata
         - `meshes/` — assets and `models_info.json`
         - `train_pbr/` — numeric scene/sequence directories
             - `000000/`, `000001/`, `000002/`, ... — each directory contains files for a single rendered sequence

   - Observed conventions and recommended rules:
     - Sequence folders are zero-padded numeric identifiers (6 digits in this repository: `000000`, `000001`, ...).
     - Within each sequence folder, we expect per-frame files (images, masks, depth, frame metadata). Please check the exact filename patterns in your exported sequences and add them here. Example (common patterns — confirm in your dataset):
         - `rgb/` or `img_000000.png` — rendered color image(s)
         - `depth/` or `depth_000000.exr` — depth images
         - `seg/` or `mask_000000.png` — segmentation/mask images
         - `meta_000000.json` — per-frame metadata (object poses, camera, lighting)

   - To inspect a particular sequence folder and verify exact filenames, run (example):
     ```bash
     ls -la dataset/train_pbr/000000 | head -n 100
     ```

9. Citation of datasets/code used
   - If this dataset was created using or adapted from other datasets or code, list them here with citations and version information. Example placeholders:
     - [Dataset or code name] — DOI/URL — short note about how it was used

---

How to add missing metadata
 - Contributors: add name, affiliation, email and ORCID if available.
 - Dates: add the generation and analysis dates where known.
 - Publications: add DOI/URLs and update the Citation section.
 - License: if CC-BY 4.0 is accepted, add a `LICENSE` file with the full license text.

Suggested citation (example template)
 - When you publish results using this dataset, please cite it as follows (replace placeholders):

  BibTeX example
  ```bibtex
  @dataset{roboprox_transparent_megapose_2025,
    author = {Add Dataset Authors Here},
    title  = {ROBOPROX: transparent_meagapose_finetune_HF dataset},
    year   = {2025},
    publisher = {[Institution or Repository name]},
    doi = {[Add DOI if available]}
  }
  ```

Acknowledgements
 - Funded by the European Union under the project Robotics and advanced industrial production (reg. no. CZ.02.01.01/00/22_008/0004590).

Contact and support
 - For questions, corrections or to request missing metadata, please contact: [maintainer email or GitHub issue link].

Next steps / recommended validation
 - Inspect a representative `train_pbr/<id>` folder and add exact per-file naming patterns to section 8.
 - Add contributor list and any connected publication DOIs.
 - Add `LICENSE` file if CC-BY 4.0 is to be used.
 - Optionally add a small example script that reads `camera.json` and one sequence to demonstrate usage.

--
Generated on 2025-11-06
