| --- |
| language: en |
| license: cc-by-4.0 |
| pretty_name: DCSkyCam Helicopter Classification Dataset |
| tags: |
| - image-classification |
| - helicopter |
| - aviation |
| - computer-vision |
| task_categories: |
| - image-classification |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # DCSkyCam Helicopter Classification Dataset |
|
|
| This dataset contains cropped images of helicopters and non-helicopter objects captured by the DCSkyCam - a Raspberry Pi-based webcam in Washington, DC. The images were used to train binary and multi-class helicopter classification models using transfer learning from EfficientNet. |
|
|
| ## Dataset Description |
|
|
| The DCSkyCam system used a three-stage detection pipeline: |
| 1. **Object Detection** (SSD MobileNet V3) identifies candidate objects in the sky |
| 2. **Binary Classifier** determines if a candidate is a helicopter or not |
| 3. **Multi-class Classifier** identifies the specific helicopter type |
|
|
| This dataset contains the cropped images used for stages 2 and 3. |
|
|
| ### Image Format |
| - **Format:** JPEG (cropped from full-frame) |
| - **Typical size:** Pixel sizes vary depending on MobileNet bounding box output. Most have at least 1 axis >= 100px. |
| - **Total images:** 8,100 |
|
|
| ### Metadata Columns |
|
|
| | Column | Description | |
| |--------|-------------| |
| | `file_name` | Image filename (relative path within `train/`) | |
| | `helicopter_type` | `"helicopter"` or `"not_helicopter"` | |
| | `heli_subtype` | Helicopter type code (e.g., `"UH1N"`, `"AS350"`) or `"none"` for non-helicopters | |
|
|
| ### Class Distribution |
|
|
| **Helicopter Types:** |
| 5,153 images |
|
|
| | Type | Count | Type | Count | |
| |------|-------|------|-------| |
| | UH1N | 1,920 | MH65 | 717 | |
| | AS350 | 895 | B412 | 451 | |
| | H60 | 451 | EC35 | 126 | |
| | VH3D | 194 | VH92 | 125 | |
| | S76 | 124 | AW139 | 59 | |
| | UH72 | 39 | EC45 | 26 | |
| | MD52 | 14 | B206 | 5 | |
| | AH6 | 2 | V22 | 2 | |
|
|
| **Non-helicopter:** 2,947 images |
|
|
| ## Usage Notes |
|
|
| - The test/train/validation split is left to the user — no pre-defined splits are included. |
| - Data augmentation was applied during model training but is not reflected in this dataset. Users are free to apply their own augmentation. |
| - A small number of additional copyrighted images (<100) were used for training but are also excluded from this dataset for licensing reasons. |
|
|
| ## License |
|
|
| This dataset is licensed under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{dcskycam_classification_dataset, |
| title = {DCSkyCam Helicopter Classification Dataset}, |
| author = {DCSkyCam contributors}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/dcskycam/helicopter-classification}, |
| license = {CC-BY-4.0} |
| } |
| ``` |
|
|
| ## Project Information |
|
|
| The DCSkyCam project was an AI-enabled sky monitoring system built on Raspberry Pi that automatically detected and identified helicopters using TensorFlow Lite models. |
|
|
