Adds a README to the COTS detector.

PiperOrigin-RevId: 447913647

official/projects/cots_detector/README.md

+# Crown-of-Thorns Starfish Detection Pipeline
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/tensorflow/models/blob/master/official/projects/cots_detector/crown_of_thorns_starfish_detection_pipeline.ipynb)
+
+This repository shows how to detect crown-of-thorns starfish (COTS) using a
+pre-trained COTS detector implemented in TensorFlow.
+
+![Underwater photo of coral reef with annotated boxes identifying detected
+starfish](https://storage.googleapis.com/download.tensorflow.org/data/cots_detection/COTS_detected_sample.png)
+
+## Description
+
+Coral reefs are some of the most diverse and important ecosystems in the world,
+however they face a number of rising threats that have resulted in massive
+global declines. In Australia, outbreaks of the coral-eating crown-of-thorns
+starfish (COTS) have been shown to cause major coral loss, with just 15 starfish
+in a hectare being able to strip a reef of 90% of its coral tissue. While COTS
+naturally exist in the Indo-Pacific, overfishing and excess run-off nutrients
+have led to massive outbreaks that are devastating already vulnerable coral
+communities.
+
+Controlling COTS populations is critical to promoting coral growth and
+resilience, so Google teamed up with Australia’s national science agency,
+[CSIRO](https://www.csiro.au/en/), to tackle this problem. We trained ML object
+detection models to help scale underwater surveys, enabling the monitoring and
+mapping out these harmful invertebrates with the ultimate goal of helping
+control teams to address and prioritize outbreaks.
+
+## Get started
+
+[Open the notebook in Colab](https://colab.research.google.com/github/tensorflow/models/blob/master/official/projects/cots_detector/crown_of_thorns_starfish_detection_pipeline.ipynb)
+to run the COTS detection pipeline.