elicse

elicse's Stars

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook47.7k3086715.6k

• spmallick/learnopencv

  Learn OpenCV : C++ and Python Examples

  Language:Jupyter Notebook21.3k88631911.6k

• PaddlePaddle/PaddleDetection

  Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

  Language:Python12.8k1985.4k2.9k

• wang-xinyu/tensorrtx

  Implementation of popular deep learning networks with TensorRT network definition API

  Language:C++7k1041.3k1.8k

• RangiLyu/nanodet

  NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

  Language:Python5.8k684621k

• kartik-v/bootstrap-fileinput

  An enhanced HTML 5 file input for Bootstrap 5.x/4.x./3.x with file preview, multiple selection, and more features.

  Language:JavaScript5.4k3761.6k2.4k

• nwojke/deep_sort

  Simple Online Realtime Tracking with a Deep Association Metric

  Language:Python5.4k943081.5k

• amdegroot/ssd.pytorch

  A PyTorch Implementation of Single Shot MultiBox Detector

  Language:Python5.1k865451.7k

• ZheC/Realtime_Multi-Person_Pose_Estimation

  Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)

  Language:Jupyter Notebook5.1k2582361.4k

• Tianxiaomo/pytorch-YOLOv4

  PyTorch ,ONNX and TensorRT implementation of YOLOv4

  Language:Python4.5k525051.5k

• weiaicunzai/pytorch-cifar100

  Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

  Language:Python4.3k35831.2k

• open-mmlab/mmtracking

  OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.

  Language:Python3.6k48464598

• onnx/onnx-tensorrt

  ONNX-TensorRT: TensorRT backend for ONNX

  Language:C++3k68665545

• aaron-xichen/pytorch-playground

  Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

  Language:Python2.6k5350612

• Daniil-Osokin/lightweight-human-pose-estimation.pytorch

  Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.

  Language:Python2.1k34311479

• tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation

  Language:Python1.4k36148412

• tensorlayer/HyperPose

  Library for Fast and Flexible Human Pose Estimation

  Language:Python1.3k58184275

• helloflask/flask-tutorial

  Flask 入门教程 / Flask for Beginners

  Language:HTML8321725147

• tpm2-software/tpm2-tss

  OSS implementation of the TCG TPM2 Software Stack (TSS2)

  Language:C753681.1k365

• nihui/ncnn-android-nanodet

  Language:C++37492578

• bmartacho/UniPose

  We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.

  Language:Python215104445

• tjuskyzhang/Scaled-YOLOv4-TensorRT

  Got 100fps on TX2. Got 500fps on GeForce GTX 1660 Ti. If the project is useful to you, please Star it.

  Language:C++17862841

• vaesl/LRF-Net

  Learning Rich Features at High-Speed for Single-Shot Object Detection, ICCV, 2019

  Language:Python164121127

• l-sf/Linfer

  基于TensorRT的C++高性能推理库，Yolov10, YoloPv2，Yolov5/7/X/8，RT-DETR，单目标跟踪OSTrack、LightTrack。

  Language:C++1603621

• miyamotok0105/pytorch_handbook

  pytorch_handbook

  Language:Jupyter Notebook114101044

• fengjiqiang/Pretrained_Model_Pytorch

  pytorch pretrained model — resnet, densenet, inception, vgg, squeezenet, alexnet

  Language:Python713018

• foota/ccl

  Connected Component Labeling.

  Language:Cuda422117

• Wulingtian/nanodet_tensorrt_int8_tools

  Language:Python24217

• microsoft/TPM-2.0-Parser

  Parse TPM 2.0 Command and Response streams

  Language:C#2311115

• AlbinZhu/easy-trt

  TensorRT for YOLOv10 with CUDA

  Language:C++13112