Stars
A collection of loss functions for medical image segmentation
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
This data set includes Landsat 8 images and their manually extracted pixel-level ground truths for cloud detection.
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
Kaggle DSTL Satellite Imagery Feature Detection
🤘 awesome-semantic-segmentation
Code for a winning model (3 out of 419) in a Dstl Satellite Imagery Feature Detection challenge
Techniques for deep learning with satellite & aerial imagery
Sample code to call C API for Tensorflow 2.1
ResUNet, a semantic segmentation model inspired by the deep residual learning and UNet. An architecture that take advantages from both(Residual and UNet) models.
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
tensorflow object detection api helper tool ( custom object detection )
Faster R-CNN for Open Images Dataset by Keras
Helper functions to create COCO datasets
faster RCNN keras step by step implementation
Cloned from https://github.com/yhenon/keras-frcnn. Added resnet101 support
Road and Building Segmentation in Satellite Imagery
We propose a simple yet efficient technique to leverage semantic segmentation model to extract and separate individual buildings in densely compacted areas using medium resolution satellite/UAV ort…
Keras package for region-based convolutional neural networks (RCNNs)
A paper list of object detection using deep learning.
A faster pytorch implementation of faster r-cnn
DeepLab v3+ model in PyTorch. Support different backbones.
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source …
💥Faster R-CNN from scratch written with Keras
Keras implementation of RetinaNet object detection.