From bb42f13f2fcbfad0ce17405275a82f38c2f51a4d Mon Sep 17 00:00:00 2001 From: Hanzhe Teng Date: Thu, 7 Dec 2023 17:01:34 -0800 Subject: [PATCH] update aws download option --- README.md | 2 +- docs/download.md | 9 +++++---- docs/index.md | 2 +- 3 files changed, 7 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index e92d471..53be431 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,7 @@ CitrusFarm is a multimodal agricultural robotics dataset that provides both **mu **Related Workshop Spotlight:** [Present and Future of Agricultural Robotics and Technologies: Academic and Industry Perspectives](https://sites.google.com/view/agrobotics) (IROS 2023) **Related Publications:** -H. Teng, Y. Wang, X. Song and K. Karydis, "Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms", in the 18th International Symposium on Visual Computing (ISVC 2023). [[paper](https://link.springer.com/chapter/10.1007/978-3-031-47969-4_44)] [[preprint](https://arxiv.org/abs/2309.15332)] +H. Teng, Y. Wang, X. Song and K. Karydis, "Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms", In International Symposium on Visual Computing (ISVC 2023). [[paper](https://link.springer.com/chapter/10.1007/978-3-031-47969-4_44)] [[preprint](https://arxiv.org/abs/2309.15332)] ``` @inproceedings{teng2023multimodal, title={Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms}, diff --git a/docs/download.md b/docs/download.md index 52ac6ac..578036e 100644 --- a/docs/download.md +++ b/docs/download.md @@ -42,17 +42,18 @@ For a complete file list, please see [dataset_file_list.yaml](https://raw.github ## Download We host [our dataset](https://registry.opendata.aws/citrus-farm/) on Amazon Web Services (AWS), sponsored by AWS [Open Data program](https://aws.amazon.com/opendata/open-data-sponsorship-program/). -You may use this Python script ([download_citrusfarm.py](https://raw.githubusercontent.com/UCR-Robotics/Citrus-Farm-Dataset/main/scripts/download_citrusfarm.py)) to download the dataset from AWS. +Option 1: You may use this Python script ([download_citrusfarm.py](https://raw.githubusercontent.com/UCR-Robotics/Citrus-Farm-Dataset/main/scripts/download_citrusfarm.py)) to download the dataset from AWS. - By default, the script will download all sequences and all modalities. - Change `folder_list` in the script to download only sequences of your interest. - Change `modality_list` in the script to download only modalities of your interest. -If you are a user of AWS, you can also download all data directly from the S3 bucket using AWS CLI tool: +Option 2: If you are using a Ubuntu computer, you can also download all data directly from the S3 bucket using AWS CLI tool (No AWS account required): ``` -aws s3 sync s3://ucr-robotics/citrus-farm-dataset/ /path/to/local/directory +sudo apt install awscli +aws s3 sync --no-sign-request s3://ucr-robotics/citrus-farm-dataset/ /path/to/local/directory ``` -Alternatively, you may download the dataset from two other backup sources: +Option 3: Alternatively, you may download the dataset from two other cloud services: - [Google Drive](https://drive.google.com/drive/folders/12h5CAagVVtz1Od9bK_O6hDMyG8Xh_DLG?usp=sharing) - [Baidu Pan](https://pan.baidu.com/s/1NVRTHKvFUue2qaQsb7wlVQ?pwd=ilas) (Credits to Yicheng Jin & Qi Wu@SJTU; please contact robotics_qi@sjtu.edu.cn for any download issue.) diff --git a/docs/index.md b/docs/index.md index c239787..f73cb47 100644 --- a/docs/index.md +++ b/docs/index.md @@ -17,7 +17,7 @@ CitrusFarm is a multimodal agricultural robotics dataset that provides both **mu **Related Workshop Spotlight:** [Present and Future of Agricultural Robotics and Technologies: Academic and Industry Perspectives](https://sites.google.com/view/agrobotics) (IROS 2023) **Related Publications:** -H. Teng, Y. Wang, X. Song and K. Karydis, "Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms", in the 18th International Symposium on Visual Computing (ISVC 2023). [[paper](https://link.springer.com/chapter/10.1007/978-3-031-47969-4_44)] [[preprint](https://arxiv.org/abs/2309.15332)] +H. Teng, Y. Wang, X. Song and K. Karydis, "Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms", In International Symposium on Visual Computing (ISVC 2023). [[paper](https://link.springer.com/chapter/10.1007/978-3-031-47969-4_44)] [[preprint](https://arxiv.org/abs/2309.15332)] ``` @inproceedings{teng2023multimodal, title={Multimodal Dataset for Localization, Mapping and Crop Monitoring in Citrus Tree Farms},