In this project, we are going to train a deep convolutional neural network to transcribe digits. Then we are going to use the data from the learning stage to allow the Pi Camera to read and recognize digits. The AI pipeline will be implemented using Scikit and OpenCV 3.3 for image manipulation and Keras which uses Tensorflow as a back-end for the deep learning part.
To keep this easy no feature localization stage is done so you’ll have to shove the image in front of the camera lens so that it’s the only feature that it sees.
The MNIST dataset will be used. It is comprised of 60,000training examples and 10,000 test examples of the handwritten digits 0–9,formatted as 28×28-pixel monochrome images.
Stop breadboarding and soldering – start making immediately! Adafruit’s Circuit Playground is jam-packed with LEDs, sensors, buttons, alligator clip pads and more. Build projects with Circuit Playground in a few minutes with the drag-and-drop MakeCode programming site, learn computer science using the CS Discoveries class on code.org, jump into CircuitPython to learn Python and hardware together, or even use Arduino IDE. Circuit Playground Express is the newest and best Circuit Playground board, with support for MakeCode, CircuitPython, and Arduino. It has a powerful processor, 10 NeoPixels, mini speaker, InfraRed receive and transmit, two buttons, a switch, 14 alligator clip pads, and lots of sensors: capacitive touch, IR proximity, temperature, light, motion and sound. A whole wide world of electronics and coding is waiting for you, and it fits in the palm of your hand.