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Train, evaluate, and run machine learning models.

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7,589 projects

a7m4-lut

Itinerary200

8stars
a7m4-lut preview

把 .cube LUT 转成索尼 A7M4 机内创意外观(camera-look v2 JSON);9 家品牌 log 曲线自动适配,ΔE00 中位 1.51

28stars
ClashRoyaleAi preview

A fast, deterministic Clash Royale battle simulator in C++ with Python bindings, a recurrent PPO agent, lookahead search, and a computer-vision bridge to the real game.

  • 132 cards and 41 Evolutions: troops, buildings, spells, spawners, Champions and their abilities, death effects, knockback, slows, stuns and rolling spells. Every card's stats are in docs/CARDS.md, generated from the engine.
  • Real-game timing: 10 ticks per second, deploy time, King Tower activation, and 1×/2×/3× elixir phases on the real schedule.

torch-conv-kan

IvanDrokin

533stars
torch-conv-kan preview

This project is dedicated to the implementation and research of Kolmogorov-Arnold convolutional networks. The repository includes implementations of 1D, 2D, and 3D convolutions with different kernels, ResNet-like and DenseNet-like models, training code based on accelerate/PyTorch, as well as scripts for experiments with CIFAR-10 and Tiny ImageNet.

350stars
pytorch-dnc preview

Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch

MIRAGE

j-morano

58stars
MIRAGE preview

Official repository of the paper "MIRAGE: A multimodal foundation model and benchmark for comprehensive retinal OCT image analysis", published in npj Digital Medicine (2025).

VL-BERT

jackroos

741stars
VL-BERT preview

Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".

Machine LearningJupyter NotebookMITGitHub

Yolov7-tracker

JackWoo0831

787stars
Yolov7-tracker preview

Yolo X, v3 ~ v12 and several Multi-Object Tracker(SORT, DeepSORT, ByteTrack, BoT-SORT, etc.) in MOT17 and VisDrone2019 Dataset. It uses a unified style and integrated tracker for easy embedding in your own projects.

610stars

This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance segmentation tasks. These datasets are ideal for applications in computer vision, machine learning, remote sensing, and maritime analysis.