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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: left |
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dtype: int64 |
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- name: forward |
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dtype: int64 |
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- name: right |
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dtype: int64 |
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splits: |
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- name: train |
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num_bytes: 1245310731.916 |
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num_examples: 27754 |
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download_size: 1242463614 |
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dataset_size: 1245310731.916 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Dataset Card for Dataset Name |
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This dataset includes images taken in the Cyberzoo in the aircraft hall of the Delft University of Technology. |
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## Dataset Details |
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### Dataset Description |
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This dataset was collected throughout multiple testing sessions at the Cyberzoo, both while actually flying and handheld. The labeling of the data has been performed using monocular depth maps, generated using [Depth-Anything](https://github.com/LiheYoung/Depth-Anything). The exact labeling process has been explained in [this](https://github.com/Timdnb/CNN-for-Micro-Air-Vehicles/blob/main/Dataset_generation.ipynb) notebook. |
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- **Curated by:** [Tim den Blanken] |
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## Uses |
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This dataset can be used to train Convolutional Neural Networks for obstacle avoidance of Micro Air Vehicles in the Cyberzoo of Delft University of Technology. For the entire training pipeline, please go this [this](https://github.com/Timdnb/CNN-for-Micro-Air-Vehicles) repository. |
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## Dataset Structure |
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The dataset consists of a single folder containing all images. Each image has features listed in the metadata, which are "Left", "Forward" and "Right". |
