eweill/keras-deepcv

This repository will contain model definitions, training scripts, and other for Keras implementations for classification, detection, and segmentation (computer vision)

Keras Deep Computer Vision

This repository contains model definitions, training scripts, and other examples for Keras (Tensorflow backend) implementations for classification, detection, and segmentation (computer vision).

Models

Classification

• LeNet Paper Model
• AlexNet Paper Model
• VGG16 and VGG19 Paper Model
• ResNet Paper
• YOLO9000 Paper
• DenseNet Paper

Detection

• Faster RCNN Paper
• SSD Paper
• YOLOv2 Paper
• R-FCN Paper

Segmentation

• FCN8 Paper
• SegNet Paper
• U-Net Paper
• E-Net Paper
• ResNetFCN Paper
• PSPNet Paper
• Mask RCNN Paper

Datasets

Classification

• MNIST
• CIFAR-10
• MNIST-Fashion
• ImageNet
• Pascal VOC

Detection

• Pascal VOC
• LISA Traffic Sign
• KITTI
• MSCOCO

Segmentation

• CamVid
• Cityscapes
• Pascal VOC
• KITTI
• SYNTHIA
• GTA-V Segmentation
• MSCOCO

Prerequisites

For the models in thie repo, Keras and Tensorflow are required. Make sure the latest versions are installed.

After these packages have been installed, a few other packages are required (which can be found in requirements.txt)

pip install -r requirements.txt

Acknowledgments

This repo would like to acknowledge the following pieces of code which played a part in the development of this repository:

• keras_zoo