| --- |
| library_name: pytorch |
| tags: |
| - computer-vision |
| - object-detection |
| - image-classification |
| - yolov7 |
| - marine-biology |
| pipeline_tag: object-detection |
| model-index: |
| - name: YOLOv7 Baselines on N-MARINE |
| results: |
| - task: |
| type: object-detection |
| name: Object Detection |
| dataset: |
| type: other |
| name: N-MARINE |
| url: https://open.canada.ca/data/en/dataset/2ae46860-f82a-4127-bb1f-b02e36ef6a70 |
| split: test |
| citation: | |
| Morris, C. J., Ayyagari, K. D., Porter, D., Nguyen, Q. K., Hanlon, J., & Whidden, C. (2025). |
| *Newfoundland Marine Refuge Fish Classification Dataset (N-Marine)*. |
| Government of Canada Open Data Portal. |
| https://open.canada.ca/data/en/dataset/2ae46860-f82a-4127-bb1f-b02e36ef6a70 |
| metrics: |
| - name: "mAP@0.5" |
| type: mAP |
| value: 0.808 |
| - name: "mAP@0.5:0.95" |
| type: mAP |
| value: 0.494 |
| - name: precision |
| type: precision |
| value: 0.807 |
| - name: recall |
| type: recall |
| value: 0.764 |
| --- |
| |
| # YOLOv7 Baselines for N-MARINE |
| This repo hosts baseline **YOLOv7** models trained on the **N-MARINE** dataset (North Atlantic underwater images with 9 fish species + background). |
|
|
| - **Best baseline (no class weights)** |
| mAP@0.5 **0.808 ± 0.007** · mAP@[0.5:0.95] **0.494 ± 0.008** · P **0.807 ± 0.036** · R **0.764 ± 0.014** |
| - **Paper:** TODO – add link when available |
| |
| > Dataset: [N-MARINE](https://open.canada.ca/data/en/dataset/2ae46860-f82a-4127-bb1f-b02e36ef6a70) |
| > Supplementary + scripts: https://github.com/Pentaerythrittetranitrat/N-MARINE_dataset_supplementary |
|
|
| ## Model list |
| The released models follow this directory structure, where each `datasetX` (X = 1–5) corresponds to one of the five cross-validation splits: |
|
|
| Each `datasetX` directory contains two trained models: |
| - `classweights/best.pt` — trained with inverse-frequency class weights. |
| - `no_classweights/best.pt` — trained without class weights (baseline, recommended). |
|
|
| The **dataset splits** used for training can be found in the supplementary repository: |
| [https://github.com/Pentaerythrittetranitrat/N-MARINE_dataset_supplementary](https://github.com/Pentaerythrittetranitrat/N-MARINE_dataset_supplementary) |
| > **Note:** The models under `dataset5` correspond to the most balanced split across classes. |
|
|
| Each model outputs **9 classes**. The **class order (index → class)** for all models is: |
| | Index | Class name | |
| |-------|----------------------| |
| | 0 | Atlantic Cod | |
| | 1 | Roughhead Grenadier | |
| | 2 | Atlantic Halibut | |
| | 3 | Redfish Mentella | |
| | 4 | Thorny Skate | |
| | 5 | Striped Wolffish | |
| | 6 | Spinytail Skate | |
| | 7 | Whelk | |
| | 8 | Northern Wolffish | |
|
|
| ## Intended use |
|
|
| - Benchmarking object detection on North Atlantic underwater imagery |
| - Studying class imbalance, visibility limits (turbidity/occlusion), and domain shifts |
| - Generating crops for downstream **species classification** tasks |
|
|
| ## Training data and splits |
|
|
| - **Data:** N-MARINE (23,936 images, 9 species + background) |
| - **Split protocol:** fixed **15% video-level** test; 5-fold CV within train videos |
| - **Pretraining:** COCO weights (YOLOv7) |
| - **Image size:** 640×640 letterboxed |
| - **Epochs:** 50 |
| - **Batch size:** 32 |
| - **Other:** default YOLOv7 augmentations & hyperparams unless noted |
|
|
| ### Class weights variant |
| Inverse-frequency class weights slightly improved **Spinytail Skate** but reduced aggregate mAP. |
|
|
| ### Quick inference |
|
|
| > These weights are YOLOv7-format PyTorch checkpoints. Use the YOLOv7 repository or a compatible runner. |
|
|
| ## CLI (YOLOv7) |
|
|
| ```bash |
| # 1) Clone YOLOv7 (example URL; use the official repo you trained with) |
| git clone https://github.com/WongKinYiu/yolov7.git |
| cd yolov7 |
| pip install -r requirements.txt |
| |
| # 2) Run inference |
| python detect.py \ |
| --weights /path/to/N-MARINE_baseline_classifiers/n-marine_weights/dataset5/no_classweights/best.pt \ |
| --source /path/to/images_or_video \ |
| --img-size 640 \ |
| --conf-thres 0.25 \ |
| --iou-thres 0.65 \ |
| --save-txt --save-conf |
| ``` |
| ### Citation |
|
|
| If you use the dataset, please cite: |
|
|
| Dataset citation (plain text): |
| Morris, C. J., Ayyagari, K. D., Porter, D., Nguyen, Q. K., Hanlon, J., & Whidden, C. (2025). |
| Newfoundland Marine Refuge Fish Classification Dataset (N-Marine). |
| Government of Canada Open Data Portal. |
| https://open.canada.ca/data/en/dataset/2ae46860-f82a-4127-bb1f-b02e36ef6a70 |
|
|
| If you use the models, please cite: |
|
|
| Model citation (plain text): |
| TODO: Add |
