Gain Object Detection on Mobile Devices Using TensorFlow in a Browser

Gain object detection on mobile devices using TensorFlow in a browser.

CabeAtwell
over 4 years ago Sensors

The fine folks over at Adafruit have put together a handy tutorial on how to run the TensorFlow machine learning application within a browser, which is then able to take advantage of a smartphone, PC, or laptop camera to identify objects it sees. The secret to running the AI application is the use of Google’s Colab cloud-based service, which offloads all the processing necessary using their GPU servers rather than relying on internal hardware.

Running TensorFlow on a camera-equipped mobile device within a browser is done using Google Colab, along with with Mobilenet v2 + SSDLite model to box the object it sees. (📷: Adafruit)
"We've hacked together a Colab notebook that can see things using your computer, laptop, or phone camera! It takes live pictures from your camera and feeds them through the Mobilenet v2 + SSDLite model to find and box the objects it sees. This way, you can see what Mobilenet v2 + SSDLite can do, instantly!”

The platform works by using Mobilenet v2 + SSDLite — a neural network-based object detection system, which offers three outputs utilizing the camera’s video feed, including object identification, confidence level in determining what they are, and a bounding box drawn around the objects in question. TensorFlow takes that data from object detection system and learns to identify the items within its view with increased accuracy.

Mobilenet v2 + SSDLite is an object detection system that is capable of targeting objects on real-time video, which are denoted by bounding boxes. (📷: Adafruit)

This is an excellent project for those who would like to learn about AI without needing a Ph.D. in computer science, or for those with limited hardware that would like to see what all the fuss is about machine-learning.

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