fasterrcnn-pytorch-training-pipeline
sports
fasterrcnn-pytorch-training-pipeline | sports | |
---|---|---|
11 | 2 | |
173 | 438 | |
- | - | |
6.0 | 5.9 | |
7 days ago | 5 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
fasterrcnn-pytorch-training-pipeline
- A simple library to train more than 20 Faster RCNN models using PyTorch (including ViTDet)
- A Library of Faster RCNN Models with Simple Training Pipeline for Custom Dataset
- PyTorch Faster RCNN Library - Support for transformer detection models.
- PyTorch Faster RCNN Custom Dataset Training Made Easy
- An efficient, powerful, and easy training pipeline for Faster RCNN models in PyTorch
- A Faster RCNN Object Detection Pipeline for Custom Training in PyTorch
- A PyTorch library for easily training Faster RCNN models (even with custom backbones) on custom datasets for object detection.
- A very simple pipeline to train FasterRCNN Object Detection Models (WRITTEN IN PYTORCH)
- A Faster RCNN Object Detection Pipeline for custom datasets using PyTorch - Get started with training in 5 minutes
sports
-
[OC] Counting People in the Zones with YOLOv8, OpenCV, and Supervision
I actually have a project where I did exactly that: https://github.com/SkalskiP/sport. Maybe I'll upload it here next week ;)
-
Football Player 3D Pose Estimation using YOLOv7
I think it's this one: https://github.com/SkalskiP/sport
What are some alternatives?
simple-faster-rcnn-pytorch - A simplified implemention of Faster R-CNN that replicate performance from origin paper
uav-detection - Drone / Unmanned Aerial Vehicle (UAV) Detection is a very safety critical project. It takes in Infrared (IR) video streams and detects drones in it with high accuracy.
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
MMM-MyScoreboard - Module for MagicMirror to display today's scores for your favourite teams across multiple sports.
notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
synthetic-dataset-object-detection - How to Create Synthetic Dataset for Computer Vision (Object Detection) (Article on Medium)
roboflow-100-benchmark - Code for replicating Roboflow 100 benchmark results and programmatically downloading benchmark datasets
supervision - We write your reusable computer vision tools. 💜
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.