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--- |
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task_categories: |
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- image-to-image |
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- image-feature-extraction |
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- object-detection |
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language: |
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- en |
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tags: |
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- plant |
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- precision agriculture |
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- plant phenotyping |
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- tracking |
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size_categories: |
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- 10B<n<100B |
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pretty_name: CanolaTrack |
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--- |
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# CanolaTrack |
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**CanolaTrack** is a curated dataset for **leaf-level multi-object tracking (MOT)** and **detection** from top-down RGB imagery of *Brassica napus* (canola) plants. Each sequence records a single plant over time; frames contain annotated **bounding boxes** with **persistent leaf IDs** for tracking. |
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- For baseline methods and a reference pipeline built on CanolaTrack, see **LeafTrackNet** (training, inference, and TrackEval integration) in our [Github repo](https://github.com/shl-shawn/LeafTrackNet). |
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--- |
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## Dataset Summary |
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- **Domain:** Plant phenotyping (leaf-level analysis, time series) |
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- **Modalities:** RGB images (top-down) |
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- **Use cases:** Multi-object tracking (leaf IDs), detection, re-identification |
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- **Content:** Sequences of a single plant over days; each frame has MOT-style annotations |
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- **Annotations:** `gt/gt.txt` per sequence with **frame**, **leaf_id**, **x**, **y**, **w**, **h** (pixels) |
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- **Extras:** YOLOv10 **proposals JSONs** and **LeafTrackNet model weights**for reproducible tracking baselines |
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--- |
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## Repository Structure |
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``` |
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CanolaTrack/ |
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│ ├── train/ |
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│ │ └── <plant_id>/ |
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│ │ ├── gt/gt.txt # CSV: frame,id,x,y,w,h,,,* |
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│ │ └── img/{frame:08d}.jpg |
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│ └──val/ |
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│ └── <plant_id>/ |
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│ ├── gt/gt.txt |
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│ └── img/{frame:08d}.jpg |
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proposals/ # detection proposals for standardized benchmarking |
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│ ├── det_db_train.json |
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│ └── det_db_val.json |
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weights/ # detctors and tracker weights |
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└── <files> |
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``` |
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## Supported Tasks and Benchmarks |
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- **Multi-Object Tracking (MOT)** at the **leaf** level |
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- **Object Detection** (per-frame leaf boxes) |
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- **Leaf Segmentation** (per-frame leaf masks) |
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--- |
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## How to Cite |
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Please cite the dataset and the accompanying papers: |
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```bib |
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@article{leaftracknet2025, |
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title={LeafTrackNet: A Deep Learning Framework for Robust Leaf Tracking in Top-Down Plant Phenotyping}, |
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year={2025}, |
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author = {}, |
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url = {} |
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} |
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``` |
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> CanolaTrack dataset© BASF SE 2025. This dataset may be freely used for non-commercial research and educational purposes. |
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