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Implementation of various Deep Image Segmentation models in keras. .Deep learning and convolutional neural networks (CNN) have been extremely ubiquitous in the field of computer vision. CNNs are popular for several computer vision tasks such as Image Classification, Object Detection, Image Generation, etc. Like for all other computer vision tasks, deep learning has surpassed other approaches for image segmentation

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image-segmentation-keras's Introduction

Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras.

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Implementation of various Deep Image Segmentation models in keras.

Working Google Colab Examples:

Python Interface: https://colab.research.google.com/drive/1q_eCYEzKxixpCKH1YDsLnsvgxl92ORcv?usp=sharing
CLI Interface: https://colab.research.google.com/drive/1Kpy4QGFZ2ZHm69mPfkmLSUes8kj6Bjyi?usp=sharing

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Models

Following models are supported:

model_name	Base Model	Segmentation Model
fcn_8	Vanilla CNN	FCN8
fcn_32	Vanilla CNN	FCN8
fcn_8_vgg	VGG 16	FCN8
fcn_32_vgg	VGG 16	FCN32
fcn_8_resnet50	Resnet-50	FCN32
fcn_32_resnet50	Resnet-50	FCN32
fcn_8_mobilenet	MobileNet	FCN32
fcn_32_mobilenet	MobileNet	FCN32
pspnet	Vanilla CNN	PSPNet
vgg_pspnet	VGG 16	PSPNet
resnet50_pspnet	Resnet-50	PSPNet
unet_mini	Vanilla Mini CNN	U-Net
unet	Vanilla CNN	U-Net
vgg_unet	VGG 16	U-Net
resnet50_unet	Resnet-50	U-Net
mobilenet_unet	MobileNet	U-Net
segnet	Vanilla CNN	Segnet
vgg_segnet	VGG 16	Segnet
resnet50_segnet	Resnet-50	Segnet
mobilenet_segnet	MobileNet	Segnet