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--- |
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license: cc-by-4.0 |
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task_categories: |
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- audio-classification |
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size_categories: |
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- n>1T |
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tags: |
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- pedestrian detection |
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--- |
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# ASPED: An Audio Dataset for Detecting Pedestrians |
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This repo contains the data for the ASPED dataset, presented at ICASSP 2024. |
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- [Paper Link](https://arxiv.org/abs/2309.06531), [Project Homepage](https://urbanaudiosensing.github.io/ASPED.html) |
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- Pavan Seshadri, Chaeyeon Han, Bon-Woo Koo, Noah Posner, Suhbrajit Guhathakurta, Alexander Lerch |
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## Usage |
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This dataset contains audio and video recordings of pedestrian activity collected at various locations in and around Georgia Tech. |
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Labels of pedestrian counts per each second of audio/video are provided as well, calculated via a computer vision model (Mask2Former trained on msft-coco) using the video recordings. |
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### Access |
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It is recommended to use the huggingface_hub library to download the dataset from this location. [Info on downloading with huggingface_hub](https://huggingface.co./docs/huggingface_hub/guides/download). |
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Downloading the entire dataset can be done with the following code: |
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``` |
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from huggingface_hub import snapshot_download |
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snapshot_download(repo_id="pseshadri9/ASPED", repo_type="dataset") |
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``` |
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Alternatively if you would like to download only the audio or video, pass the ignore_patterns flag to snapshot_download to avoid downloading the entire set. |
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**Audio Only** |
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``` |
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from huggingface_hub import snapshot_download |
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snapshot_download(repo_id="pseshadri9/ASPED", repo_type="dataset", ignore_patterns="*.mp4") |
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``` |
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**Video Only** |
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``` |
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from huggingface_hub import snapshot_download |
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snapshot_download(repo_id="pseshadri9/ASPED", repo_type="dataset", ignore_patterns="*.flac") |
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``` |
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## Citation |
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``` |
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@inproceedings{Seshadri24, |
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title={ASPED: An Audio Dataset for Detecting Pedestrians}, |
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author={Seshadri, Pavan and Han, Chaeyeon and Koo, Bon-Woo and Posner, Noah and Guhathakurta, Suhbrajit and Lerch, Alexander}, |
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booktitle={Proc. of ICASSP 2024}, |
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pages={1--5}, |
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year={2024}, |
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organization={IEEE} |
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} |
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``` |
