Displaying 1 to 9 from 9 results

Screenshot-to-code-in-Keras - A neural network that transforms a screenshot into a static website

  •    Jupyter

This is the code for the article 'Turning design mockups into code with deep learning' on FloydHub's blog. Within three years deep learning will change front-end development. It will increase prototyping speed and lower the barrier for building software.

self-driving-toy-car - A self driving toy car using end-to-end learning

  •    Jupyter

To make a lane follower based on a standard RC car using Raspberry Pi and a camera. The software is a simple Convolutional Network, which takes in the image fetched from the camera and outputs the steering angle. During data collection, we will simply hook the steering PWM of the car to pin GPIO17. The script raspberry_pi/collect_data.py will record the values of steering PWM and the associated images. The data of each trial are collectively stored in driving_trial_*. The trial folders are automatically numbered.

image-to-3d-bbox - Build a CNN network to predict 3D bounding box of car from 2D image.

  •    Jupyter

This is an implementation in Keras of the paper "3D Bounding Box Estimation Using Deep Learning and Geometry" (https://arxiv.org/abs/1612.00496).

CNN_keras - CNN | Keras | CAPTCHA recognition(卷积神经网络、Keras框架、验证码识别)

  •    Python

This CAPTCHAs generated from repo CAPTCHA_generator. Using about 5000 samples, Obtain 95% single letter accuracy.

Hyperopt-Keras-CNN-CIFAR-100 - Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset

  •    Python

This project acts as both a tutorial and a demo to using Hyperopt with Keras, TensorFlow and TensorBoard. Not only we try to find the best hyperparameters for the given hyperspace, but also we represent the neural network architecture as hyperparameters that can be tuned. This automates the process of searching for the best neural architecture configuration and hyperparameters. Here, we are meta-optimizing a neural net and its architecture on the CIFAR-100 dataset (100 fine labels), a computer vision task. This code could be easily transferred to another vision dataset or even to another machine learning task.

ResNetCAM-keras - Keras implementation of a ResNet-CAM model

  •    Python

The original Matlab implementation and paper (for AlexNet, GoogLeNet, and VGG16) can be found here. A Keras implementation of VGG-CAM can be found here. This implementation is written in Keras and uses ResNet-50, which was not explored in the original paper.

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