Update README.md

README.md

@@ -1,3 +1,38 @@
 ---
 license: cc-by-4.0
+tags:
+- ocean
+- midwater
+- object-detection
 ---
+
+# MBARI Midwater Supercategory Detector
+
+## Model Details
+- Trained by researchers at [CVisionAI](https://www.cvisionai.com/) and the [Monterey Bay Aquarium Research Institute](https://www.mbari.org/) (MBARI).
+- [YOLOv5v6.2](https://github.com/ultralytics/yolov5/tree/v6.2)
+- Object detection
+- Fine tuned yolov5l to detect 22 morhpotaxonmic categories of midwater animals in the Greater Monterey Bay Area off the coast of Central California.
+
+## Intended Use
+- Make real time detections on video feed from MBARI Remotely Operated Vehicles.
+- Post-process video collected in the region by MBARI vehicles.
+
+## Factors
+- Distribution shifts related to sampling platform, camera parameters, illumination, and deployment environment are expected to impact model performance.
+- Evaluation was performed on an IID subset of available training data. Data to test out of distribution performance not currently available.
+
+## Metrics
+- Precision, Recall, and per class accuracy were evaluated at test time. 
+- [email protected] = 0.866
+- Indicates reasonably good performance for target task.
+
+## Training Data
+- A combination of publicly available [FathomNet](https://fathomnet.org/fathomnet/#/) and internal MBARI data
+
+## Deployment
+In an environment running [YOLOv5v6.2](https://github.com/ultralytics/yolov5/tree/v6.2):
+
+```
+python classify/predict.py --weights best.pt --data data/images/
+```