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computer vision projects | 计算机视觉相关好玩的AI项目（Python、C++、embedded system）

We write your reusable computer vision tools. 💜

Efficient vision foundation models for high-resolution generation and perception.

Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

YOLO-Mark is not a good tool to use,So we use the tool labelme to get the things for YOLO to train,

[CVPR 2023] Effcient Frequence Domain-based Transformer for High-Quality Image Deblurring

Code examples in pyTorch and Tensorflow for CS230

Segment Anything in High Quality [NeurIPS 2023]

STM32 library for read result ADC from ADS1115 with i2c protocol

The code for "Improving Nighttime Driving-Scene Segmentation via Dual Image-adaptive Learnable Filters".

CoRP : Co-Salient Object Detection with Co-Representation Purification

EGNet:Edge Guidance Network for Salient Object Detection (ICCV 2019)

C++ code (with python wrapper) for measuring the F-measure and MAE scores for salient object detection

Amulet and UCF methods for Saliency Detection

Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

Painlessly create beautiful matplotlib plots.

Boundary Aware PoolNet = PoolNet + BASNet : Deeply supervised PoolNet using the hybrid loss in BASNet for Salient Object Detection

Video Salient Object Detection via Fully Convolutional Networks (TIP18)

[CVPR 2022] This repository includes the official project for the paper: TransMix: Attend to Mix for Vision Transformers.

Springer journal article template in LaTeX for Overleaf

This is the official repository for our recent work: PIDNet

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

SuperYOLO is accepted by TGRS

RAFConv: Innovating Spatital Attention and Standard Convolutional Operation