Update README.md

README.md

@@ -15,18 +15,16 @@ configs:
 # BOP: Benchmark for 6D Object Pose Estimation
 The goal of BOP is to capture the state of the art in estimating the 6D pose, i.e. 3D translation and 3D rotation, of rigid objects from RGB/RGB-D images. An accurate, fast, robust, scalable and easy-to-train method that solves this task will have a big impact in application fields such as robotics or augmented reality.
 
-![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/637fb712084fca81acde6e40/8WSyi9CNNsfDHC-lwaRpG.jpeg)
-
 Homepage: https://bop.felk.cvut.cz/home/
 
-Toolkit: https://github.com/thodan/bop_toolkit
+BOP Toolkit: https://github.com/thodan/bop_toolkit
 
 ## Downloading datasets
 
-#### Option 1: Using `huggingface_hub`:
-
 <details><summary>Click to expand</summary>
 
+#### Option 1: Using `huggingface_hub`:
+
 a. Install the library:
 ```
 pip install --upgrade huggingface_hub
@@ -45,13 +43,9 @@ snapshot_download(repo_id="bop-benchmark/datasets",
 ```
 If you want to download the entire BOP datasets (~3TB), please remove the `allow_patterns` argument. More options are available in the [official documentation](https://huggingface.co/docs/huggingface_hub/main/en/guides/download).
 
-</details>
-
 
 #### Option 2: Using `huggingface_hub[cli]`:
 
-<details><summary>Click to expand</summary>
-
 a. Install the library:
 ```
 pip install -U "huggingface_hub[cli]"
@@ -64,12 +58,9 @@ export DATASET_NAME=hope
 huggingface-cli download bop-benchmark/datasets --include "$DATASET_NAME/*.zip" --local-dir $LOCAL_DIR --repo-type=dataset  
 ```
 Please remove this argument `--include "$DATASET_NAME/*.zip"` to download entire BOP datasets (~3TB). More options are available in the [official documentation](https://huggingface.co/docs/huggingface_hub/main/en/guides/download).
-</details>
 
 #### Option 3: Using `wget`:
 
-<details><summary>Click to expand</summary>
-
 Similar `wget` command as in [BOP website](https://bop.felk.cvut.cz/datasets/) can be used to download the dataset from huggingface hub:
 ```
 export SRC=https://huggingface.co/datasets/bop-benchmark/datasets/resolve/main
@@ -79,7 +70,6 @@ wget $SRC/lm/lm_models.zip       # 3D object models
 wget $SRC/lm/lm_test_all.zip     # All test images ("_bop19" for a subset)
 wget $SRC/lm/lm_train_pbr.zip    # PBR training images 
 ```
-</details>
 
 Datasets are stored in `.zip` format. You can extract them using the following command:
 ```
@@ -92,16 +82,18 @@ pip install huggingface_hub[hf_transfer]
 export HF_HUB_ENABLE_HF_TRANSFER=1
 ```
 
+</details>
+
 ## Uploading datasets
 
+<details><summary>Click to expand</summary>
+
 You create a new dataset and want to share it with BOP community. Here is a step-by-step guide to upload the dataset and create a pull request to [our huggingface hub](https://huggingface.co/datasets/bop-benchmark/datasets/). Feel free to reach out to vanngn.nguyen@gmail.com if you have any questions.
 
 Similar to the download process, you can upload the dataset using the `huggingface_hub` library or `huggingface_hub[cli]`. We recommend using `huggingface_hub[cli]` for its simplicity.
 
 #### Option 1: Using `huggingface_hub[cli]`:
 
-<details><summary>Click to expand</summary>
-
 a. Install the library:
 ```
 pip install -U "huggingface_hub[cli]"
@@ -135,12 +127,8 @@ export HF_FOLDER=/hope
 huggingface-cli upload bop-benchmark/datasets $LOCAL_FOLDER $HF_FOLDER --repo-type=dataset --create-pr
 ```
 
-</details>
-
 #### Option 2: Using `huggingface_hub`:
 
-<details><summary>Click to expand</summary>
-
 a. Install the library:
 ```
 pip install --upgrade huggingface_hub
@@ -175,10 +163,10 @@ api.create_commit(repo_id="bop-benchmark/datasets",
 ```
 If your dataset is large (> 500 GB), you can upload it in chunks by adding the `multi_commits=True, multi_commits_verbose=True,` argument. More options are available in the [official documentation](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/package_reference/hf_api#huggingface_hub.HfApi.create_pull_request).
 
-</details>
-
 ## FAQ
 
+<details><summary>Click to expand</summary>
+
 #### 1. How to upload a large file > 50 GB?
 Note that HuggingFace limits the size of each file to 50 GB. If your dataset is larger, you can split it into smaller files:
 ```
@@ -198,27 +186,4 @@ If you are running on a machine with high bandwidth, you can increase your downl
 pip install huggingface_hub[hf_transfer]
 export HF_HUB_ENABLE_HF_TRANSFER=1
 ```
-
-## Publications
-- [**BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objects**](https://arxiv.org/pdf/2403.09799.pdf)
-  - T. Hodaň, M. Sundermeyer, Y. Labbé, V. N. Nguyen, G. Wang, E. Brachmann, B. Drost, V. Lepetit, C. Rother, J. Matas
-  - IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW, [CV4MR workshop](https://cv4mr.github.io/)) 2024, Seattle
-  - [PDF](https://arxiv.org/pdf/2403.09799.pdf), [SLIDES](https://cmp.felk.cvut.cz/sixd/workshop_2023/slides/bop_challenge_2023_results.pdf), [VIDEO](https://www.youtube.com/watch?v=PcDszFANcDQ), [BIB](https://cmp.felk.cvut.cz/~hodanto2/data/hodan2023bop.bib)
-
-- [**BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects**](https://arxiv.org/pdf/2302.13075.pdf)
-  - M. Sundermeyer, T. Hodaň, Y. Labbé, G. Wang, E. Brachmann, B. Drost, C. Rother, J. Matas
-  - IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW, [CV4MR workshop](https://cv4mr.github.io/)) 2023, Vancouver
-  - [PDF](https://arxiv.org/pdf/2302.13075.pdf), [SLIDES](https://cmp.felk.cvut.cz/sixd/workshop_2022/slides/bop_challenge_2022_results.pdf), [VIDEO 1](https://vimeo.com/showcase/9946695/video/768457697), [VIDEO 2](https://vimeo.com/showcase/9946695/video/768458355), [BIB](https://cmp.felk.cvut.cz/~hodanto2/data/sundermeyer2022bop.bib)
-
-- [**BOP Challenge 2020 on 6D Object Localization**](https://arxiv.org/pdf/2009.07378.pdf)
-  - T. Hodaň, M. Sundermeyer, B. Drost, Y. Labbé, E. Brachmann, F. Michel, C. Rother, J. Matas
-  - European Conference on Computer Vision Workshops (ECCVW) 2020, Glasgow
-  - [PDF](https://arxiv.org/pdf/2009.07378.pdf), [SLIDES](https://bop.felk.cvut.cz/media/bop_challenge_2020_results.pdf), [BIB](http://cmp.felk.cvut.cz/~hodanto2/data/hodan2020bop.bib)
-
-- [**BOP: Benchmark for 6D Object Pose Estimation**](http://cmp.felk.cvut.cz/~hodanto2/data/hodan2018bop.pdf)
-  - T. Hodaň, F. Michel, E. Brachmann, W. Kehl, A. G. Buch, D. Kraft, B. Drost, J. Vidal, S. Ihrke, X. Zabulis, C. Sahin, F. Manhardt, F. Tombari, T.-K. Kim, J. Matas, C. Rother
-  - European Conference on Computer Vision (ECCV) 2018, Munich
-  - [PDF](http://cmp.felk.cvut.cz/~hodanto2/data/hodan2018bop.pdf), [SLIDES](http://cmp.felk.cvut.cz/~hodanto2/data/hodan2018bop_slides_eccv.pdf), [POSTER](http://cmp.felk.cvut.cz/~hodanto2/data/hodan2018bop_poster.pdf), [BIB](http://cmp.felk.cvut.cz/~hodanto2/data/hodan2018bop.bib)
-  
-
-The online evaluation system has been developed by [T. Hodaň](http://www.hodan.xyz) and [A. Melenovský](https://www.linkedin.com/in/anton%C3%ADn-melenovsk%C3%BD-09907b151/).
+</details>