lufficc/SSD
High quality, fast, modular reference implementation of SSD in PyTorch
This project offers a robust and flexible implementation of the SSD (Single Shot MultiBox Detector) model for object detection. It takes images as input and accurately identifies and localizes multiple objects within them, outputting images with bounding boxes, labels, and confidence scores. Researchers and machine learning engineers working on computer vision tasks will find this useful for developing and evaluating object detection models.
1,590 stars. No commits in the last 6 months.
Use this if you are a researcher or ML engineer needing a high-quality, fast, and modular codebase for experimenting with and building upon the SSD object detection architecture.
Not ideal if you are an end-user looking for a ready-to-use application or API for object detection without needing to delve into model training or development.
Stars
1,590
Forks
390
Language
Python
License
MIT
Category
Last pushed
Jan 26, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lufficc/SSD"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
broadinstitute/keras-rcnn
Keras package for region-based convolutional neural networks (RCNNs)
alankbi/detecto
Build fully-functioning computer vision models with PyTorch
sovit-123/fasterrcnn-pytorch-training-pipeline
PyTorch Faster R-CNN Object Detection on Custom Dataset
kenshohara/video-classification-3d-cnn-pytorch
Video classification tools using 3D ResNet
Tony607/object_detection_demo
How to train an object detection model easy for free