Popular GitHub Repositories for Flops Counter

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

Flops counter for convolutional networks in pytorch framework

High-performance multiple object tracking based on YOLO, Deep SORT, and KLT ?

Multi-camera live traffic and object counting with YOLO v4, Deep SORT, and Flask.

The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)

People Counting in Real-Time with an IP camera.

Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.

AI and Memory Wall

The code of the Object Counting API, implemented with the YOLO algorithm and with the SORT algorithm

A Ruby natural language processor.

This project aims to count every vehicle (motorcycle, bus, car, cycle, truck, train) detected in the input video using YOLOv3 object-detection algorithm.

Golang URL shortener and bookmarker service with UI, API, Cache, Hits Counter and forwarder using postgres and redis in backend, bulma in frontend. Think of it as self hosting ready url shortener.

Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.

Crispy is a machine-learning platform to make video-games montages efficiently. It uses a neural network to detect highlights in the video-game frames

Vehicle Counting Using Yolov8 and DeepSORT

llm theoretical performance analysis tools and support params, flops, memory and latency analysis.

Count number of parameters / MACs / FLOPS for ONNX models.

Social distance monitoring in real-time with an IP camera. Optimized for better performance with threading.

AI Exercise Rep Counter based on Google's Human Pose Estimation Library (Posenet)

Your one stop CLI for ONNX model analysis.