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Deep Learning Experiment 1

A project log for Visioneer

AI glasses that provide traffic information and obstacle avoidance for the visually impaired.

andrew.cratonandrew.craton 09/16/2017 at 16:100 Comments

The first video shows my first experiment of live recognition using a Pi3, USB webcam, Movidius\Caffe and OpenCV on a pre-trained neural net called SqueezeNet.

The second video shows the same Pi3  setup classifying a single cat pic at 307ms.  Hopefully you can see in the video the number 307523 which is = 307ms.

Now that we have a successful benchmark for Movidius, we will turn our efforts to benchmarking without it, and using YOLO\Darknet instead of Caffe\Squeezenet.

After that, we will train\compile a custom neural net on traffic-related images which should achieve a faster recognition speed on either platforms.  The goal is < 40 ms on a small custom set of objects.

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