TachibanaYoshino/Road-Crack-Segmentation--Keras

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Created over 5 years ago
Updated about 5 years ago

TachibanaYoshino/Road-Crack-Segmentation--Keras

TachibanaYoshino

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The project uses Unet-based improved networks to study road crack segmentation, which is based on keras.

AnimeGANv2

[Open Source]. The improved version of AnimeGAN. Landscape photos/videos to anime

AnimeGAN

A Tensorflow implementation of AnimeGAN for fast photo animation ! This is the Open source of the paper 「AnimeGAN: a novel lightweight GAN for photo animation」, which uses the GAN framwork to transform real-world photos into anime images.

AnimeGANv3

Use AnimeGANv3 to make your own animation works, including turning photos or videos into anime.

Remote-sensing-image-semantic-segmentation

The project uses Unet-based improved networks to study Remote sensing image semantic segmentation, which is based on keras.

Remote-sensing-image-semantic-segmentation-tf2

The remote sensing image semantic segmentation repository based on tf.keras includes backbone networks such as resnet, densenet, mobilenet, and segmentation networks such as deeplabv3+, pspnet, panet, and refinenet.

AnimeGANv3_gui.exe

The UI tool based on pyqt5 to call the AnimeGANv3 model.

AnimeGANv3_Portrait_Inference

The whole image inference based on the onnx model of AnimeGANv3

State-Farm-Distracted-Driver-Detect-Pytorch

This project is from a kaggle competition in 2016, we use mobileNet V2 to achieve classification recognition based on pytorch.