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- A Practical Implementation of the Faster R-CNN Algorithm for Object Detection (Part 2 — with Python codes)
- Snagging Parking Spaces with Mask R-CNN and Python
- SlowFast – Dual-mode CNN for Video Understanding
- Zero to Hero: Guide to Object Detection using Deep Learning: Faster R-CNN,YOLO,SSD
- Mask R-CNN for Object Detection - YouTube
- A Deep Learning based magnifying glass
- Zoom in... enhance: a Deep Learning based magnifying glass - part 2
- Object Detection — A Game Changer for Market Research
- NSFW Tensorflow: Identifying objectionable content using Deep Learning
- Realtime Multi-Person Pose Estimation 논문 리뷰 및 구현
- Deep Learning at Scale: Distributed Training and Hyperparameter Search for Image Recognition Problems
- 서비스에서 야경 좋은 식당 찾기 — Vision, Semi-supervised learning, Hierarchical classification | by Doyoung Gwak | 네이버 플레이스 개발 블로그 | Aug, 2021 | Medium
- Face Recognition
- 데이터야놀자2021 Transfer Learning으로 효율적인 이미지 분류모델 만들기 - 박경호/정현희님 - YouTube
- A new, unique AI dataset for animating amateur drawings
- donut: Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022
- fight_detection: Real time Fight Detection Based on 2D Pose Estimation and RNN Action Recognition
- ImageBind: Holistic AI learning across six modalities
- Painter & SegGPT Series: Vision Foundation Models from BAAI SegGPT: Segmenting Everything In Context
- 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
- Introducing Segment Anything: Working toward the first foundation model for image segmentation
- 모델의 가장 큰 특징은 foundation model이라는 점
- 기존에는 language model에서는 foundation model이라는 개념이 많이 도입되었던 것에 비해 image에 대한 특정 task에 대한 foundation model이 도입되지 않았음
- 이번 모델의 데모나 성능을 보면 image segmentation을 하고 도메인에 상관없이 제로샷으로 바로 작동
- How to Use the Segment Anything Model (SAM)
- Label Data with Segment Anything Model (SAM) in Roboflow - YouTube
- MobileSAM: This is the offiicial code for Faster Segment Anything (MobileSAM) project that makes SAM lightweight
- segment-anything-video: MetaSeg: Packaged version of the Segment Anything repository
- Introducing Segment Anything: Working toward the first foundation model for image segmentation
- SGToolkit: An Interactive Gesture Authoring Toolkit for Embodied Conversational Agents (UIST 2021)
- vid2player 페더러 vs. 페더러, AI 테니스 플레이어의 탄생 - YouTube
- Build A Hand Detection App Tutorial
- Naver CLOVA Face Recognition(CFR)을 활용한 웹앱 만들어보기 | by Ryan Kim | Oct, 2020 | Medium
- 사물인식하기 2 , ObjectDetection– ML5.js « Makezone – 인터랙티브 미디어, fablication 그리고 사물인터넷(IoT)
- 얼굴 인식하기 2, FaceAPI – ML5.js « Makezone – 인터랙티브 미디어, fablication 그리고 사물인터넷(IoT)
- handtrack.js: A library for prototyping realtime hand detection (bounding box), directly in the browser
- mind-ar-js: Web Augmented Reality. Image Tracking, Face Tracking. Tensorflow.js
- Albumentations: fast and flexible image augmentations
- CLOUD VISION API
- COCO API - Dataset @ http://cocodataset.org
- Cut-And-Save-Faces
- OpenCV와 dlib를 활용하여 만든 Face-Only Picture Collector. 얼굴이 많이 찍혀있는 사진을 Input으로 넣으면 자동으로 얼굴들을 잘라서 Save & Align
- face detect는 cv2, face align은 dlib
- Dataset Annotator - Tool for annotating image datasets
- DeepClassificationBot - A deep learning powered bot capable of classifying images into user-specified categories
- DensePose: Dense Human Pose Estimation In The Wild
- delira - Deep Learning In RAdiology
- PyTorch 기반 CT/MRI 등의 이미지 딥러닝 프레임워크
- 데이터셋 로딩, 샘플링, augmentation, 일반적인 트레이닝 클래스, 웹 기반 모니터링 등을 지원
- delira - Lightweight framework for fast prototyping and training deep neural networks in medical imaging
- dl-docker - All-in-one Docker image for Deep Learning
- fastocloud: IPTV/NVR/CCTV/Video cloud
- fb-vision-bot
- FIGR-8 - Few-shot Image Generation with Reptile: the dataset
- GluonCV: a Deep Learning Toolkit for Computer Vision
- Hand Keypoint Detection in Single Images using Multiview Bootstrapping
- imgaug - Image augmentation for machine learning experiments. http://imgaug.readthedocs.io
- Image Recognition using Machine Learning Techniques
- Image Text Recognition in Python
- Inpainting - Implementation of "Context Encoders: Feature Learning by Inpainting"
- Image Completion with Deep Learning in TensorFlow 기초부터 아주 자세하게 나와서 reddit에서 화제가 된 post
- JPEG-AUTOROTATE - A node module to rotate JPEG images based on EXIF orientation exif 파일에 맞게 픽셀값들을 맞춰주는 라이브러리
- python의 imread로 자신이 찍은 사진을 업로드 하면, 어떤 사진은 사진이 분명 뒤집어진 사진이 아님에도, 뒤집어져서 read되는 경우 발생
- 이유; Why Your Photos Don’t Always Appear Correctly Rotated
- exif meta정보를 이용해서 이미지 정보를 가지고 있는데, 문제는 이 exif가 구형 이미지 뷰어나, python의 imread를 활용할 때
- exif를 인식하지 못하여, exif에 있는 orientaion 항목이 아니라, exif를 무시한체 raw한 픽셀정보로 띄우다 보니
- 만약 orientaion과 실제 픽셀이 구성된 방향이 다르면 자연스럽게 뒤집어져서 로드
- Kinetics is a large-scale, high-quality dataset of YouTube video URLs which include a diverse range of human focused actions
- LAION-400M - 4억개짜리 이미지-텍스트 쌍 데이터셋 | GeekNews
- Leptonica is a pedagogically-oriented open source site containing software that is broadly useful for image processing and image analysis applications
- libfacedetection
- LUMINOTH - Open source Computer Vision toolkit
- MegaFace: Test face recognition at the million scale
- OpenPose: A Real-Time Multi-Person Keypoint Detection And Multi-Threading C++ Library
- paz: Hierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc
- pico.js, a face-detection library in 200 lines of JavaScript
- Pl@ntNet
- Realtime Multi-Person Pose Estimation
- Slic: Single line image classifier 한 줄의 명령어로 필요한 이미지 데이터셋을 생성, 자동으로 다중 분류 모델 학습, 학습이 종료되면 즉시 api를 빌드 및 테스트 환경(localhost) 구축
- smile-more - Check your face and make sure you smile using Google Vision API
- srez - Image super-resolution through deep learning
- StylEx Google AI Blog: Introducing StylEx: A New Approach for Visual Explanation of Classifiers
- Tencent ML Images released: 18 million training images with 11,000 categories
- TiefVision - End-to-end deep learning image-similarity search engine
- vatic is a free, online, interactive video annotation tool for computer vision research that crowdsources work to Amazon's Mechanical Turk
- VICAR Open Source - We are pleased to announce that the VICAR Core is now available in Open Source form!
- VTK - The Visualization Toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, image processing, and visualization
- WebRTC
- WebRTC samples
- Getting Started with WebRTC
- Build a Webcam Communication App using WebRTC
- Introduction | WebRTC for the Curious
- WebRTC Library 다루기 | Hyperconnect Tech Blog
- WebRTC는 어떻게 실시간으로 데이터를 교환할 수 있을까? - 재그지그의 개발 블로그
- Comparing WebRTC with HTTP-based streaming
- Building video chat into my personal website using WebRTC, Websockets, and Golang on GCP
- 사례별로 살펴보는 WebRTC + Streaming 설계 · Present
- Top 5: Best Open Source WebRTC Media Server Projects | Our Code World
- WebRTC 시동걸기 | Doublem.org
- WebRTC 시그널링 서버 구현하기 | Doublem.org
- The evolution of WebRTC 1.0. - Advancing WebRTC
- 샤피라이브 1편: WebRTC 기술 적용 스토리 (feat. low-latency) :: GS Retail Engineering
- 샤피라이브 2편: WebRTC 정복하기 (Flutter 개발자의WebRTC 개발담) :: GS Retail Engineering
- WebRTC? WebSockets? 5분 개념정리! - YouTube
- How does Discord scale to 5 million concurrent users ?? | by Sukhad Anand | Medium
- WebRTC 서비스 부하 테스트 | NHN FORWARD
- 글로벌 라이브 스트리밍을 지탱하는 하이퍼커넥트 미디어 서버 인프라를 소개합니다 | Hyperconnect Tech Blog
- 카카오워크 음성채팅 웹 개발기
- GStreamer 1.20: Embedded & WebRTC lead the way
- IPFS A guide to IPFS connectivity in web browsers | IPFS Blog & News
- Janus WebRTC Server (multistream): About Janus
- pear: WebRTC Library for IoT/Embedded Device using C
- webrtcH4cKS: ~ Open Source Cloud Gaming with WebRTC
- webrtc-nuts-and-bolts: A holistic way of understanding how WebRTC and its protocols run in practice, with code and detailed documentation
- Webtoon AI Painter
- YoHa - A practical hand tracking engine | handtracking.io
- YOLO: Real-Time Object Detection
- YOLO
- How to Deploy Yolo on Tensorflow Serving - Part 1
- '머신러닝&딥러닝/YOLO'
- 분석 YOLO
- 커스텀 데이터 셋으로 Yolo 써 보기 1
- 커스텀 데이터 셋으로 Yolo 써 보기 2
- Object detection in just 3 lines of R code using Tiny YOLO
- Common Understanding about YOLO
- One-shot object detection
- windows환경/darknet/ 점수내기 - DACON
- YOLO Real time object detection on CPU
- GaussianYoloV3_Detector
- OpenDataCam - An open source tool to quantify the world YOLO기반 카메라 활용
- labelImg: 🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images
- MS-DAYOLO: Multiscale Domain Adaptive YOLO for Cross-Domain Object Detection
- tfjs-yolo: YOLO v3 and Tiny YOLO v1, v2, v3 with Tensorflow.js
- TincyYOLO: a real-time, low-latency, low-power object detection system running on a Zynq UltraScale+ MPSoC
- v2
- v3
- PyTorch-YOLOv3
- PyTorch 로 YOLOv3 구현한 것을 Colaboratory 에서 돌려보자
- How to implement a YOLO (v3) object detector from scratch in PyTorch: Part 1
- How to implement a YOLO (v3) object detector from scratch in PyTorch
- 윈도우즈에서 yolo v3 돌려보기 1/2
- 윈도우즈에서 yolo v3 돌려보기 2/2
- Yolo v3 커스텀 모델 학습
- What’s new in YOLO v3?
- YOLOv3
- How to Build an Object Tracker Using YOLOv3, Deep SORT and TensorFlow
- Tutorial #1 : Use YOLOv3 : AlexeyAB/darknet (Video files / Webcam) Windows or Linux - YouTube
- Suite와 Valohai로 YOLOv3 파이프라인 설계하기 - Superb AI Blog
- thermal_signature_drone_detection: Detection of drones using their thermal signatures from thermal camera through YOLO-V3 based CNN with modifications to encapsulate drone motion
- v4
- YOLOv4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used) http://pjreddie.com/darknet
- YOLOv4 in the CLOUD: Build and Train Custom Object Detector
- YOLOv4 Object Detection with TensorFlow, TensorFlow Lite and TensorRT Models
- Counting Objects Using YOLOv4 Object Detection | Custom YOLOv4 Functions with TensorFlow
- Object Tracking Using YOLOv4, Deep SORT, and TensorFlow
- YOLOv4 Object Detection Crash Course | YOLO v4 how it works and how to build it
- YOLOv4 in the CLOUD: Build Object Tracking Using DeepSORT in Google Colab (FREE GPU)
- How to Build a Custom YOLOv4 Object Detector using TensorFlow
- Yolo V4 를 이용한 유리층 식별/분류 솔루션
- Object Detection YOLOv4 Darknet 학습하여 Custom 데이터 인식 모델 만들기 (feat. AlexeyAB/darknet)
- v5
- YOLO V4 vs V5 - YouTube
- YOLOv5 is Here: State-of-the-Art Object Detection at 140 FPS
- YOLOv5 compared to Faster RCNN. Who wins? | by Priya Dwivedi | Jul, 2020 | Towards Data Science
- YOLO V5 Model comparison - YouTube
- Yolo V5 Object Detection using Pytorch | On Local & Colab
- "Yolov5 Object Detection Using Google Colab & Python" | KNOWLEDGE DOCTOR | Mishu Dhar - YouTube
- C# 기반 배포 가능한 딥러닝 객체 감지 프로그램 개발(feat. YOLO v5) #1 | by Minsu Cho | Hard Boiled Smith Stories | Apr, 2021 | Medium
- C# 기반 배포 가능한 딥러닝 객체 감지 프로그램 개발(feat. YOLO v5) #2 | by Minsu Cho | Hard Boiled Smith Stories | Jun, 2021 | Medium
- AYolov2
- YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
- yolov5-knowledge-distillation: YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
- v7
- Training YOLOv7 on Custom Data - Colaboratory
- 코딩없이 YOLOv7을 체험해보자! | Smilegate.AI
- yolov7: Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
- yolov7: Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
- MaskRCNN vs YOLOv7: A Comparison of Object Segmentation Algorithms
- v8
- yolox
- Creating a Modern OCR Pipeline Using Computer Vision and Deep Learning
- 카카오 OCR 시스템 구성과 모델
- 아날로그 기상 데이터를 OCR로 디지털화할 수 있을까?
- #42. 사진 속 글자 읽기, OCR (Optical Character Recognition)
- 한국어 OCR 해내기 (With Naver Cloud Platform) 1편: 가뿐하게 OCR API를 만들고 쓰는 법
- 한국어 OCR 해내기 (With Naver Cloud Platform) 2편: 입맛대로 커스텀한 OCR 만들기
- CHARACTER REGION AWARENESS FOR TEXT DETECTION
- 알도개 RPA와 AI
- 파이썬으로 사진에서 문자인식하는 AI 쉽게 만들기 - YouTube
- EasyOCR: Ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai
- master-easy-ocr-wook-2.endpoint.ainize.ai
curl -X POST "https://master-easy-ocr-wook-2.endpoint.ainize.ai/word_extraction" -H "accept: images/*" -H "Content-Type: multipart/form-data" -F "language=ko" -F "base_image=@<file name>.jpg;type=image/jpeg".jpg file이 있는 directory에서 실행
- Inverse-DALL-E-for-Optical-Character-Recognition: Inverse DALL-E for Optical Character Recognition
- kakao API — ocr - Jun - Medium
- kakao API — ocr
- PaddleOCR: Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
- ClojureCL - Parallel computations with OpenCL 2.0 in Clojure High Performance Computing and GPGPU in Clojure: access the supercomputer on your desktop
- DeepCL - OpenCL library to train deep convolutional networks
- EasyOpenCL - The easiest way to get started with OpenCL!
- PyOpenCL lets you access the OpenCL parallel computation API from Python
- Visualizing the Mandelbrot Set
- OpenCV
- awesome-opencv
- Welcome to OpenCV-Python Tutorials’s documentation!
- opencv - Open Source Computer Vision Library http://opencv.org
- Load Caffe framework models
- Scene Reconstruction
- opencv_contrib - Repository for OpenCV's extra modules
- study.marearts.com/search/label/OpenCV
- OpenCV video editing tutorial
- Python 데이터 분석과 이미지 처리
- OpenCV 에서 OpenCL 살짝 써보기
- Which Painting Do You Look Like? Comparing Faces Using Python and OpenCV
- Switching Eds: Face swapping with Python, dlib, and OpenCV
- Playing Pacman with gestures: Python+OpenCV
- Simple algorithme de détection de mouvement avec OpenCV JAVA ★★★
- OpenCV Lecture(korean) / OpenCV 강의(강좌)
- OpenCV Build shared, OpenCV 빌드한 것 공유
- OpenCV 빌드하기 (OpenCV 3.2 + CUDA + TBB)
- OpenCV Build, Ubuntu 20.04 + OpenCV 4.5.2 + CUDA 11.2 - YouTube
- 슬로우캠퍼스 OpenCV 세미나 (명함 인식 만들기) 하이라이트 영상
- OpenCV로 실시간 명함 인식하기
- 리멤버는 어떻게 명함을 정확히 인식할까? : OpenCV 이미지 프로세싱 - DRAMA&COMPANY
- AI 명함 촬영 인식 ‘리오(RIO)’ 적용기 1부 - 명함촬영인식 위한 Instance Segmentation & Computer Vision - DRAMA&COMPANY
- AI 명함촬영인식 리오 적용기 2부 - ML Model Converter와 안드로이드 앱 적용기 - DRAMA&COMPANY
- 리멤버 유저에게 보다 깨끗한 명함 이미지 제공을 위한 이미지 복원 방법 - DRAMA&COMPANY
- Getting Started with OpenCV | Learn OpenCV
- Object Tracking using OpenCV (C++/Python)
- ‘Object Tracking’ 카테고리의 설명
- 3D-Object-Tracking: A simple 3D Object Tracking module for humans 🍺
- Torch와 OpenCV를 활용한 실시간 이미지 분류 데모
- Principles of fMRI 1
- Topics in Computer Vision (CSC2523): Deep Learning in Computer Vision
- Face classification and detection Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV
- face_expression_detector
- python에서 opencv를 사용하여 image crop하기
- Building a Real-Time Object Recognition App with Tensorflow and OpenCV
- 딥러닝과 OpenCV를 활용해 사진 속 글자 검출하기
- 웹어셈블리와 컴퓨터 비전을 사용한 실험
- 라즈베리파이 카메라 OpenCV
- 라즈베리파이 OpenCV 설치(빌드 없이 설치파일로)
- Reading game frames in Python with OpenCV - Python Plays GTA V
- Switching Eds: Face swapping with Python, dlib, and OpenCV
- Playing Pacman with gestures: Python+OpenCV
- OpenCV를 이용한 Image Diff
- 데이터분석/Vision Recognition
- OPENCV 명령어 관련 정리
- OPENCV 빠르게 이용해서 얼굴 판별
- OpenCV 3 + 비주얼 스튜디오 + 윈도우즈10 설치
- OpenCV 라이브러리로, 윤곽에 기반한 자동차 번호판 영역 추출 (License plates recognition)
- Korean-Vehicle-License-Plate-Character-Dataset
- COMPUTER VISION LECTURE - Image Processing, Computer Vision, Machine Learning
- How to Resize, Pad Image to Square Shape and Keep Its Aspect Ratio With Python
- OpenCV: The open source computer vision library for everyone:
- OpenCodeModule Simple function module with Tensorflow C API
- Deep Learning based Edge Detection in OpenCV
- tf_train_opencv_run - It shows how to generate a *.pb file with Tensorflow and how to use the *.pb file in an OpenCV application
- 이미지 프로세싱 & 컴퓨터 시각화 1부
- 이미지 프로세싱 & 컴퓨터 시각화 2부
- 이미지 프로세싱 & 컴퓨터 시각화 3부
- 이미지 프로세싱 & 컴퓨터 시각화 4부
- 이미지 프로세싱 & 컴퓨터 시각화 5부
- 이미지 프로세싱 & 컴퓨터 시각화 6부
- 이미지 프로세싱 & 컴퓨터 시각화 7부
- 이미지 프로세싱 & 컴퓨터 시각화 8부
- 이미지 프로세싱 & 컴퓨터 시각화 9부
- 이미지 프로세싱 & 컴퓨터 시각화 10부 - Blurring & Smoothing (1화)
- 이미지 프로세싱 & 컴퓨터 시각화 11부 - Blurring & Smoothing (2화)
- 이미지 프로세싱 & 컴퓨터 시각화 12부 - Blurring & Smoothing (3화)
- 이미지 프로세싱 & 컴퓨터 시각화 13부 - Morphological Operator(1화)
- 이미지 프로세싱 & 컴퓨터 시각화 14부 - Morphological Operator(2화)
- 이미지 프로세싱 & 컴퓨터 시각화 15부 - Gradient
- 이미지 프로세싱 & 컴퓨터 시각화 16부 - Video (Introduction)
- 이미지 프로세싱 & 컴퓨터 시각화 17부 - Video (drawing)
- 이미지 프로세싱 & 컴퓨터 시각화 18부 - Object Detection (Template Matching)
- 이미지 프로세싱 & 컴퓨터 시각화 19부 - Corner Detection (1부)
- 이미지 프로세싱 & 컴퓨터 시각화 20부 - Corner Detection (2부)
- 이미지 프로세싱 & 컴퓨터 시각화 21부 - Edge Detection
- 이미지 프로세싱 & 컴퓨터 시각화 22부 - Grid Detection
- 이미지 프로세싱 & 컴퓨터 시각화 23부 - Contour Detection
- 이미지 프로세싱 & 컴퓨터 시각화 24부 - Feature Matching (1화)
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