Semantic-segmentation Libraries

11 Components & Libraries

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Semantic-segmentation Libraries

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

There are options: Below shows how to build the standalone executable on macOS, Linux and Windows.

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

There are options: A few object categories and images: Below shows how to build the standalone executable on macOS, Linux and Windows.

Simplest and fastest image and text annotation tool.

Install the Kili client with pip: Instantiate the Kili client: Here is a sample of the operations you can do with the Kili client:

WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab].

Our augmentation method can accurately emulate realistic color constancy degradation. Existing color augmentation methods often generate unrealistic colors which rarely happen in reality (e.g., green…

A simpler way of reading and augmenting image segmentation data into TensorFlow

This is an efficient semantic segmentaiton data input pipeline function for Tensorflow 2. The pipeline is made to be multithreaded, and uses the tf data API to prerocess the image and segmentation ma…

Code for the model to segment people at the image

To convert datasets to the format: You can enable / disable datasets that are used for training and validation. Example: Example:

A High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.

This is the Official Repository of Xtreme-Vision. Xtreme-Vision is a High Level Python Library which is built with simplicity in mind for Computer Vision Tasks, such as Object-Detection, Human-Pose-E…

Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.

This repository contains implementations of multiple deep learning models (U-Net, FCN32 and SegNet) for multiclass semantic segmentation of the CamVid dataset

A Python module that produces image patches and annotation masks from whole slide images for deep learning in digital pathology.

Welcome to SlideSeg, a python module that allows you to segment whole slide images into usable image chips for deep learning. Image masks for each chip are generated from associated markup and annota…

pytorch-naive-video-neural-style-transfer

Create naive (no temporal loss) NST for videos with person segmentation. Just place your videos in data/, run and you get your stylized and segmented videos.

The first video of the series was created exactly using this method (I also used ReCoNet for 1 part of the video). On the left you can see typical NST output and the 2 other images on the right were …