Pixellib is a library for the task of segmenting objects in images and videos. The library supports two main types of object segmentation: semantic and instance segmentation.
The complexity of ML-models implementation
Object segmentation has many applications in computer vision such as medical image analysis, road scene segmentation for self-driving cars, satellite image analysis, and photo editing. Developers usually find it difficult to integrate machine learning models into their products. One of the challenges is combining programming skills with model training skills. PixelLib’s goal is to lower the entry threshold for developers who want to use Object Segmentation Models in their systems.
Image background editing
The library allows you to implement segmentation models without theoretical knowledge of the operation of neural networks. One of the tasks that PixelLib can solve is to edit the background of an image or video. This is solved in 5 lines of code. The library’s functionality allows:
- Create a virtual background for images and videos;
- Erase the background on images and videos;
- Paint the background in some color;
- Make the background black and white.
The functionality of the library is described in more detail in the original article.
