TachibanaYoshino/Remote-sensing-image-semantic-segmentation

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TachibanaYoshino/Remote-sensing-image-semantic-segmentation

TachibanaYoshino

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

Remote-sensing-image-semantic-segmentation

The project uses Unet-based improved networks to study Remote sensing image semantic segmentation, which is based on keras.
This project has been used in the Sparse Representation and Intelligent Analysis of 2019 Remote Sensing Image competition.

Requirements

python 3.6.8
tensorflow-gpu 1.8
Keras 2.2.4
opencv-python
tqdm
numpy
glob
argparse
matplotlib
tifffile
pyjson
Pillow 6.0
scikit-learn

Usage

1. Download dataset

Link,key:1d4x

2. Create new labels

python create_train_val_label.py

3. Train

eg. python train6_6.py --model checkpoint6_6

4. Download pre-trained weights

Link

5. Test

eg. python test.py --model 'checkpoint6_6'+ '/' + 'weights-039-0.7205-0.8099.h5'

Results

Since the original remote sensing image is too large, a partial screenshot of the test results is given here.

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-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.

Road-Crack-Segmentation--Keras

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

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.