YOLACT provides real-time instance segmentation by predicting segmentation masks for detected objects in a single forward pass. The model uses a fully convolutional architecture with protonets and mask coefficients to generate mask prototypes, enabling fast inference at 33+ fps on standard GPUs. The project includes training scripts, pretrained models on COCO, and supports YOLACT++ improvements with deformable convolutions.