Keras

Faster R-CNN (object detection) implemented by Keras for custom data from Google’s Open Images…

The whole dataset of Open Images Dataset V4 which contains 600 classes is too large. So we extract 1,000 images for three classes, ‘Person’, ‘Mobile phone’ and ‘Car’ respectively.

Source: towardsdatascience.com/faster-r-cnn-object-detection-implemented-by-keras-for-custom-data-from-googles-open-images-125f62b9141a

Faster R-CNN (object detection) implemented by Keras for custom data from Google’s Open Images

Building Your First ConvNet

This post is to help you get up to speed on training ConvNet models in the cloud without the hassles of setting up a VM, AWS instance, or anything of that sort. You’ll be able to design your own classification task with lots of images and train your own ConvNet models.

Source: blog.floydhub.com/building-your-first-convnet/

Building Your First ConvNet

Haggis, Not Haggis: Build a haggis-detection app with TensorFlow and FloydHub

Use TensorFlow to build your own haggis-hunting app for Burns Night! The Scottish quest for the mythical wild haggis just got easier with deep learning.

Source: blog.floydhub.com/haggis-not-haggis/

Haggis, Not Haggis: Build a haggis-detection app with TensorFlow and FloydHub

On Building an Instagram Street Art Dataset and Detection Model

In this article, we will go over how to build a deep learning model using TensorFlow and Keras that accomplishes the task of generally detecting street art by using publicly available social media data on Instagram.

Source: blog.floydhub.com/instagram-street-art/

On Building an Instagram Street Art Dataset and Detection Model

Jrobot Self Drive Powered by Tensorflow Lite

Jrobot Self Drive is another self-driving experiment based on machine learning. It is not a simulator, it is not a road vehicle, it is a footpath traveler. We built Nvidia CNN self drive model using Keras, collected training data, trained the model, and converted the trained model to TensorFlow Lite. TensorFlow Lite allows us to do inference on-board a mobile device and is the key part of this project. We added TensorFlow Lite to Jrobot Android app. When running, TensorFlow Lite is able to load the trained model, take a camera image as input and give a steering angle as output. Jrobot app runs on an Android phone (Xiaomi Mi5) sitting in the phone box on Jrobot car, and control the movement of the Jrobot car through Bluetooth connection with Arduino on the car.

Source: www.youtube.com/watch?v=FKoxqZ7R7Ec

Jrobot Self Drive Powered by TensorFlow Lite

Building a Toy Self-Driving Car: Part One

Learn the history and technology of autonomous cars in this Part 1 of a series on building a self-driving toy car with Raspberry Pi, Keras, and FloydHub GPUs.

Source: blog.floydhub.com/toy-self-driving-car-part-one/

Building a Toy Self-Driving Car: Part One