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annie

👾 Fast and simple video download library and CLI tool written in Go

dcscn-super-resolution

A tensorflow implementation of "Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network", a deep learning based Single-Image Super-Resolution (SISR) model.

deeply-recursive-cnn-tf

Test implementation of Deeply-Recursive Convolutional Network for Image Super-Resolution

drn

Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution

edsr-pytorch

PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)

electron-ssr-backup

electron-ssr原作者删除了这个伟大的项目，故备份了下来，不继续开发,且用且珍惜

github-test

test of github features

hand-eye-calibration-matlab

hand eye calibration include eye on hand and eye in hand

kcf_kalman_tracker

A KCF Tracker with Kalman Filtter Position Prediction

ml-study-notes

Notes Of selfstudy in ML

ml_study_programs

Several Python codes for ML in book ML practice

mnist

mobilesam

This is the offiicial code for MobileSAM project that makes Segment Anything Model lightweight and faster

paddledetection

Object detection and instance segmentation toolkit based on PaddlePaddle.

plant-seedlings-classification

python-study

study python & some notes

srgan

A PyTorch implementation of SRGAN based on CVPR 2017 paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

srgan-colab

study-note-of-ml-by-andrew-ng

style-change

swc_test

Study of GitHub

templematch-based-on-opencv3-4-python3.6

尝试以opencv3+python3.6为基础进行图片模板匹配实验

tensorflow-zh

谷歌全新开源人工智能系统TensorFlow官方文档中文版

tensorflow_study

study of tensorflow

tensorrtx

Implementation of popular deep learning networks with TensorRT network definition API

vgg16

Recurrence the VGG-16 model with reveal of conv kernel

visualtracking

Some code in visual tracking

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/