kelamini

kelamini

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Location:hena, China

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kelamini's repositories

cleanlab

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

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cocoapi

COCO API - Dataset @ http://cocodataset.org/

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darknet-office

YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )

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eval_data

data clean

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HeadDetection

Head Person Helmet Detection on Construction Sites,基于目标检测工地安全帽和禁入危险区域识别系统,🚀😆附 YOLOv5 训练自己的数据集超详细教程🚀😆2021.3新增可视化界面❗❗

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LabelKeypoints

A tools to label the person of keypoints with 17 points.

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labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

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lihang-code

《统计学习方法》的代码实现

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mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

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mmclassification

OpenMMLab Image Classification Toolbox and Benchmark

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mmdetection

OpenMMLab Detection Toolbox and Benchmark

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mmpose

OpenMMLab Pose Estimation Toolbox and Benchmark.

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MOTRv2

MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors

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NuoMi

Inteligent security display interface, based on pyside6.

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onnxruntime-inference-examples

Examples for using ONNX Runtime for machine learning inferencing.

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Open-Sora

Open-Sora: Democratizing Efficient Video Production for All

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ORB_SLAM2-self

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

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PaperRead

记录日常论文阅读情况

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PFLD-pytorch

PFLD pytorch Implementation

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PIPNet

Efficient facial landmark detector

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Python-100-Days

Python - 100天从新手到大师

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SoftTeacher

Semi-Supervised Learning, Object Detection, ICCV2021

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yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

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yolov8-object-tracking

YOLOv8 Object Tracking Using PyTorch, OpenCV and Ultralytics

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YOLOX

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

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