#SSD

This PyTorch-based implementation of the Single Shot MultiBox Detector offers a streamlined approach for efficient object detection. Compatible with popular datasets and offering straightforward processes for setup, training, and evaluation, this project supports NVIDIA GPU acceleration and real-time training performance enhancements via Visdom integration. Users can explore transfer learning with pre-trained model weights, supported by comprehensive instructions for both command-line and Jupyter notebook demos. Regular updates aim to expand capabilities, including support for SSD512 and custom dataset training.

This open-source project re-implements Single Shot MultiBox Detector in TensorFlow with a focus on modular VGG-based SSD networks. It supports popular datasets like Pascal VOC, offers tools for easy training and evaluation, and provides options for extending to networks like ResNet. Ideal for computer vision research.