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tf-faster-rcnn

TensorFlow implementation of Faster R-CNN

tf-faster-rcnn-1

Tensorflow Faster RCNN for Object Detection

tf_unet

Generic U-Net Tensorflow implementation for image segmentation

threadpool

A simple C++11 Thread Pool implementation

threadpool-1

based on C++11 , a mini threadpool , accept variable number of parameters 基于C++11的线程池,简洁且可以带任意多的参数

thrust

The C++ parallel algorithms library.

tlnet

Triangulation Learning Network: from Monocular to Stereo 3D Object Detection | KITTI

torch2trt

An easy to use PyTorch to TensorRT converter

trt-samples-for-hackathon-cn

Simple samples for TensorRT programming

tt100k_yolo_label

Tsinghua-Tencent 100K dataset XML and TXT Label

tusimple-benchmark

Download Datasets and Ground Truths: https://github.com/TuSimple/tusimple-benchmark/issues/3

tutorials

Some basic programming tutorials

ultra-fast-lane-detection

Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

ultra-fast-lane-detection-v2

Ultra Fast Deep Lane Detection With Hybrid Anchor Driven Ordinal Classification (TPAMI 2022)

ultra-light-fast-generic-face-detector-1mb

💎 轻量级通用人脸检测模型

ultralytics

YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite

unet

unet for image segmentation

unetplusplus

Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018

unrealenginepython

Embed Python in Unreal Engine 4

usb_cam

A ROS Driver for V4L USB Cameras

velodyne

ROS support for Velodyne 3D LIDARs

vision

Datasets, Transforms and Models specific to Computer Vision

vision_opencv

vision_transformer

vitlld

The data and Code of "ViT with diamond patches for lane line detection under occlusion"

xtreme1

Xtreme1 - The Next GEN Platform for Multimodal Training Data. #3D annotation, lidar-camera fusion annotation, image annotation and visualation tools are supported!

yolo-fastest

:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+

yolo-fastestv2-opencv

使用OpenCV部署Yolo-FastestV2，包含C++和Python两种版本的程序

yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite

yolov3-tensorrt