Underwater Trash Detection using Opensource Monk Toolkit: Train a machine vision engine that detects marine waste debris in videos captured by underwater autonomous robots.
Underwater Waste is a huge environmental problem affecting aquatic habitat drastically. Marine debris includes plastic, non-bio-degradable industrial waste, sewage sludge, radioactive material dumps, etc.
As per the statistics published at Condor Ferries
★ More than 100K marine animals die due to plastic waste
★ It is estimated that around 5.25 trillion plastic pieces exist in our oceans
★ 70 % of waste debris sinks in the ocean, around 15% floats, and the rest is washed ashore.
The great pacific garbage patch, also known as pacific trash vortex spans around 617K miles between Hawaii and California. And this is still a small part of the entire marine pollution.
To tackle this issue a lot of initiatives are being taken up like
… And many more!
A crucial part of these projects is the use of robots
★ to clean up the larger areas in a shorter period as compared to manual cleanup drives.
★ to access areas where human divers cannot reach
Robotic crab bot for plastic removal from ocean beds. Credits
A critical component for these robots is to identify different objects and take actions accordingly and this is where Deep Learning and Machine Vision enters the space!!!
Let’s dive in and add a minimalistic contribution as deep learning engineers to make this world a better place
To create a detector we used Trash-ICRA19** Dataset**
Contains 5K+ Training images and 1K+ Test Images
Data was sourced from the_ J-EDI dataset of marine debris_
The dataset is labeled with bounding box annotations over trash as well as marine life. (For simplicity we train only over trash data)
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