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https://github.com/Ertugrul-Kurubal/awesome-cv
Collection of useful sources that related to computer vision mostly.
https://github.com/Ertugrul-Kurubal/awesome-cv
List: awesome-cv
Last synced: 3 months ago
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Collection of useful sources that related to computer vision mostly.
- Host: GitHub
- URL: https://github.com/Ertugrul-Kurubal/awesome-cv
- Owner: Ertugrul-Kurubal
- Created: 2021-08-06T07:42:00.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-08-01T12:06:17.000Z (over 3 years ago)
- Last Synced: 2024-04-20T11:08:49.002Z (7 months ago)
- Homepage:
- Size: 22.5 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome-cv - Collection of useful sources that related to computer vision mostly. (Other Lists / PowerShell Lists)
README
## Index
* [General Sources(Computer Vision)](#general-sourcescomputer-vision)
* [Digital Image Processing](#digital-image-processing)
* [Deep Learning](#deep-learning)
* [General](#general)
* [Networks](#networks)
* [Convolutional Neural Networks](#convolutional-neural-networks)
* [Generative Adversarial Networks](#generative-adversarial-networks)
* [Recurrent Neural Networks](#recurrent-neural-networks)
* [Problems](#problems)
* [Object Detection](#object-detection)
* [Pose Estimation](#posegaze-estimation)
* [Datasets](#datasets)* [Photography and Camera Specs](#photography-and-camera-specs)
* [Stereo Vision](#stereo-vision)
* [3D Laser Scanning and Structured Light](#3d-laser-scanning-and-structured-light)
* [Photogrammetry and 3D Reconstruction](#photogrammetry-and-3d-reconstruction)
* [Video Streaming](#video-streaming)
* [Math](#math)
* [Production Level](#production-level)
* [IoT](#iot)
* [OOP](#oop)
* [Linux](#linux)
* [Tools](#tools)
* [Mix of interesting and cool stuff](#mix-of-interesting-and-cool-stuff)
---
## General Sources(Computer Vision)
* [Computer Vision for Visual Effects (ECSE-6969) Lectures Spring 2014](https://www.youtube.com/playlist?list=PLuh62Q4Sv7BUJlKlt84HFqSWfW36MDd5a)
* [The Ancient Secrets of Computer Vision](https://youtube.com/playlist?list=PLjMXczUzEYcHvw5YYSU92WrY8IwhTuq7p)
* [First Principles of Computer Vision Youtube Channel](https://www.youtube.com/channel/UCf0WB91t8Ky6AuYcQV0CcLw/videos)
* [Autonomous Vision Group, CVPR 2020 Keynote Talks](https://youtube.com/playlist?list=PLeCNfJWZKqxsIpTbl4e677aOWSnnv5NCm)
-------------
## Digital Image Processing
* [Intro to Digital Image Processing (ECSE-4540) Lectures, Spring 2015](https://youtube.com/playlist?list=PLuh62Q4Sv7BUf60vkjePfcOQc8sHxmnDX)* [Image Processing: What are occlusions?](https://stackoverflow.com/a/2764623/14884085)
* [Ordering coordinates clockwise with Python and OpenCV](https://www.pyimagesearch.com/2016/03/21/ordering-coordinates-clockwise-with-python-and-opencv/)
* [OpenCV Object Tracking](https://www.pyimagesearch.com/2018/07/30/opencv-object-tracking/)
* [Principal Component Analysis](https://www.youtube.com/watch?v=M6fBAzcw1Ps)
* [Optical Flow in OpenCV (C++/Python)](https://learnopencv.com/optical-flow-in-opencv/#sparse-optical-flow-lk)
* [Faster alternatives for calcOpticalFlowSF](https://stackoverflow.com/a/16120630/14884085)
* [Principal Component Analysis | LearnOpenCV](https://learnopencv.com/principal-component-analysis/)
---
## Deep Learning
### General
* [Machine Learning & Deep Learning Fundamentals](https://youtube.com/playlist?list=PLZbbT5o_s2xq7LwI2y8_QtvuXZedL6tQU)
* [Dive into Deep Learning](http://d2l.ai/chapter_introduction/index.html)* [Deep Learning Materials by Deep Learning Wizard](https://github.com/ritchieng/deep-learning-wizard)
* [The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.](https://github.com/ritchieng/the-incredible-pytorch)
* [Awesome-Pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list)
### Networks
* #### Convolutional Neural Networks
* [Intuitively Understanding Convolutions for Deep Learning](https://towardsdatascience.com/intuitively-understanding-convolutions-for-deep-learning-1f6f42faee1)
* [Lecture Collection | Convolutional Neural Networks for Visual Recognition (Spring 2017)](https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv)
* [How Convolutional Neural Networks work](https://www.youtube.com/watch?v=FmpDIaiMIeA)
* [How convolutional neural networks work, in depth](https://www.youtube.com/watch?v=JB8T_zN7ZC0)
* [Convolutional Neural Networks for Visual Recognition (Spring 2017)](https://youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv)
* [What is the vanishing gradient problem?](https://www.quora.com/What-is-the-vanishing-gradient-problem)
* [Deep Residual Learning for Image Recognition (Paper Explained)](https://www.youtube.com/watch?v=GWt6Fu05voI)
* [Convolution arithmetic](https://github.com/vdumoulin/conv_arithmetic#convolution-arithmetic)
* [A Gentle Introduction to Batch Normalization for Deep Neural Networks](https://machinelearningmastery.com/batch-normalization-for-training-of-deep-neural-networks/)
* #### Generative Adversarial Networks
* [A Friendly Introduction to Generative Adversarial Networks ](https://www.youtube.com/watch?v=8L11aMN5KY8)* [Image Deblurring using Generative Adversarial Networks](https://github.com/KupynOrest/DeblurGAN)
* #### Recurrent Neural Networks
* [Recurrent Neural Networks - EXPLAINED!](https://www.youtube.com/watch?v=yZv_yRgOvMg)
* [MIT 6.S191: Recurrent Neural Networks](https://www.youtube.com/watch?v=qjrad0V0uJE)
* [Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)](https://www.youtube.com/watch?v=WCUNPb-5EYI)
* [An introduction to ConvLSTM](https://medium.com/neuronio/an-introduction-to-convlstm-55c9025563a7)
* [What is the difference between ConvLSTM and CNN LSTM?](https://www.quora.com/What-is-the-difference-between-ConvLSTM-and-CNN-LSTM)
* [Video Classification with CNN, RNN, and PyTorch](https://medium.com/howtoai/video-classification-with-cnn-rnn-and-pytorch-abe2f9ee031)
* [PyTorch Implementation of ConvLSTM Cell](https://github.com/jhhuang96/ConvLSTM-PyTorch)
### Problems
* #### Object Detection
* [Zero to Hero: Guide to Object Detection using Deep Learning: Faster R-CNN,YOLO,SSD](https://cv-tricks.com/object-detection/faster-r-cnn-yolo-ssd/)
* [Non-maximum Suppression (NMS)](https://towardsdatascience.com/non-maximum-suppression-nms-93ce178e177c)
* [Selective Search for Object Detection | R-CNN](https://www.geeksforgeeks.org/selective-search-for-object-detection-r-cnn/)
* [PyTorch Tutorial to Object Detection.(SSD)](https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Object-Detection)
* [Object Detection Accuracy (mAP) Cheat Sheet](https://towardsdatascience.com/object-detection-accuracy-map-cheat-sheet-8f710fd79011)
* [Tackling the Small Object Problem in Object Detection](https://blog.roboflow.com/detect-small-objects/)
* [YOLOv4 - Ten Tactics to Build a Better Model](https://blog.roboflow.com/yolov4-tactics/)
* [The Power of Tiling for Small Object Detection](https://openaccess.thecvf.com/content_CVPRW_2019/papers/UAVision/Unel_The_Power_of_Tiling_for_Small_Object_Detection_CVPRW_2019_paper.pdf)
* [An Improved Faster R-CNN for Small Object Detection](https://www.researchgate.net/profile/Zengyan-Wu/publication/334904435_An_Improved_Faster_R-CNN_for_Small_Object_Detection/links/5e917edf299bf130798fb809/An-Improved-Faster-R-CNN-for-Small-Object-Detection.pdf)
* [Real-time Hand-Detection using Neural Networks (SSD) on Tensorflow](https://github.com/victordibia/handtracking)
* [Object Detection with RetinaNet(Keras)](https://keras.io/examples/vision/retinanet/)
* #### Pose/Gaze Estimation
* [Real time human head pose estimation using TensorFlow and OpenCV](https://github.com/yinguobing/head-pose-estimation)
* [GazeFollow: Where are they looking?(2015)](http://gazefollow.csail.mit.edu/index.html)
* [Where are they looking? PyTorch Implementation](https://github.com/rohitgajawada/Where-are-they-looking-PyTorch)
* [Believe It or Not, We Know What You Are Looking at!(Paper-2018)](https://arxiv.org/pdf/1907.02364.pdf)
* [Believe It or Not, We Know What You Are Looking at!(PyTorch Implementation)](https://github.com/svip-lab/GazeFollowing)
---
## Datasets
* [Middlebury Stereo Datasets](https://vision.middlebury.edu/stereo/data/)
* [VisDrone Aerial Dataset](https://github.com/VisDrone/VisDrone-Dataset)
* [HMDB: a large human motion database](https://serre-lab.clps.brown.edu/resource/hmdb-a-large-human-motion-database/#overview)
* [UCF101 – Action Recognition Data Set](https://www.crcv.ucf.edu/research/data-sets/ucf101/)
* [CelebFaces Attributes Dataset (CelebA)](http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html)
* [Kinetics: large-scale, high-quality human actions dataset](https://deepmind.com/research/open-source/kinetics)
---
## Photography and Camera Specs
* [Angle of view](https://en.wikipedia.org/wiki/Angle_of_view#Derivation_of_the_angle-of-view_formula)
* [What Is Exposure? (A Beginner’s Guide)](https://photographylife.com/what-is-exposure)
* [Rolling Shutter vs Global Shutter: What’s the difference?](https://www.premiumbeat.com/blog/know-the-basics-of-global-shutter-vs-rolling-shutter/)
* [EXPOSURE TRIANGLE: APERTURE, ISO & SHUTTER SPEED](https://www.cambridgeincolour.com/tutorials/camera-exposure.htm)
* [What are Global Shutter and Rolling shutter? How to choose the one that fits the application?](https://www.e-consystems.com/blog/camera/what-are-global-shutter-and-rolling-shutter-how-to-choose-the-one-that-fits-the-application/)
* [What Is Focal Length in Photography?](https://photographylife.com/what-is-focal-length-in-photography)
* [Focal Length vs Effective Focal Length](https://www.photographytalk.com/focal-length-vs-effective-focal-length)
* [What is a pinhole camera?](https://www.pinhole.cz/en/pinholecameras/whatis.html)
* [What is Lens Distortion?](https://photographylife.com/what-is-distortion )
---
## Stereo Vision
* [Object Distance Measurement By Stereo Vision](https://towardsdatascience.com/object-distance-measurement-by-stereo-vision-37897a7ecb62 )
* [Variants of depth cameras](https://miro.medium.com/max/2000/1*jQFsh5Osm0iPGTUmVyz0yA.png)* [Image Rectification](https://upload.wikimedia.org/wikipedia/commons/2/2d/Image_rectification.png)
* [ActiveStereoNet: The first deep learning solution for active stereo systems](https://heartbeat.fritz.ai/activestereonet-the-first-deep-learning-solution-for-active-stereo-systems-f52ed2c6cd2)
* [What Is Camera Calibration?](https://www.mathworks.com/help/vision/ug/camera-calibration.html)
* [Camera Calibration Video Series](https://youtube.com/playlist?list=PL2zRqk16wsdoCCLpou-dGo7QQNks1Ppzo)
* [CS6320: 3D Computer Vision Project 2 Stereo and 3D Reconstruction from Disparity](http://www.sci.utah.edu/~acoste/uou/3dcv/project2/ArthurCOSTE_project2.pdf)
* [3D, Depth Perception, and Stereo(The Ancient Secrets of Computer Vision )](https://www.youtube.com/watch?v=AA8FEwutsVk&list=PLjMXczUzEYcHvw5YYSU92WrY8IwhTuq7p&index=10)
* [A High-Precision Calibration Method for Stereo Vision System](https://www.researchgate.net/profile/Yandong-Tang-2/publication/221909973_A_High-Precision_Calibration_Method_for_Stereo_Vision_System/links/0deec522932b1a5915000000/A-High-Precision-Calibration-Method-for-Stereo-Vision-System.pdf)
* [Epipolar geometry](https://www.youtube.com/watch?v=QzYn0OPO0Yw&list=PLuh62Q4Sv7BUJlKlt84HFqSWfW36MDd5a&index=15)
* [Stereo Correspondence Algorithms](https://youtu.be/kxsvG4sSuvA)
* [Middlebury Stereo Vision Page](https://vision.middlebury.edu/stereo/)
* [Multiple View Geometry in Computer Vision Second Edition](http://www.r-5.org/files/books/computers/algo-list/image-processing/vision/Richard_Hartley_Andrew_Zisserman-Multiple_View_Geometry_in_Computer_Vision-EN.pdf)
* [A video that includes techniques for improvement accuracy of stereo system precision](https://www.youtube.com/watch?v=hUVyDabn1Mg&list=PL2zRqk16wsdoCCLpou-dGo7QQNks1Ppzo&index=5)
* [How to verify the correctness of calibration of a webcam?](https://stackoverflow.com/questions/12794876/how-to-verify-the-correctness-of-calibration-of-a-webcam/12821056#12821056)
* [Is reprojection error enough in stereo calibration?](https://stackoverflow.com/questions/42434420/is-reprojection-error-enough-in-stereo-calibration?rq=1)
* [Does a smaller reprojection error always means better calibration?](https://stackoverflow.com/questions/11918315/does-a-smaller-reprojection-error-always-means-better-calibration?rq=1 )
* [What to Expect from a Stereo Vision System](https://zone.ni.com/reference/en-XX/help/372916T-01/nivisionconcepts/stereo_what_to_expect_from_a_stereo_vision_system/)
* [The Depth I: Stereo Calibration and Rectification(OpenCV)](https://python.plainenglish.io/the-depth-i-stereo-calibration-and-rectification-24da7b0fb1e0)
* [The Depth II: Block Matching(OpenCV)](https://python.plainenglish.io/the-depth-ii-block-matching-d599e9372712)
* [Calibration of Stereo Cameras for Mobile Robots](http://www.diag.uniroma1.it//~iocchi/stereo/calib.html#:~:text=Calibrating%20stereo%20cameras%20is%20usually,Closed%20form%20solution.)
* [Disparity map post-filtering](https://docs.opencv.org/master/d3/d14/tutorial_ximgproc_disparity_filtering.html)
* [Effect of Baseline On Stereo Vision Systems](https://scholarworks.calstate.edu/downloads/rx913p90h)
* [How field of view changes depth estimation in stereo vision?](https://stackoverflow.com/questions/19421003/how-field-of-view-changes-depth-estimation-in-stereo-vision)
* [Design parameters for adjusting the visual field of binocular stereo cameras](https://riunet.upv.es/bitstream/handle/10251/84981/Rovira%20-%20Design%20parameters%20for%20adjusting%20the%20visual%20field%20of%20binocular%20stereo%20cameras.pdf?sequence=1)
* [Large-Field-of-View Stereo for Automotive Applications](https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.101.2554&rep=rep1&type=pdf)
---
## 3D Laser Scanning and Structured Light* [CVFX Lecture 24: Structured light scanning ](https://www.youtube.com/watch?v=ZC7CIlAVkIA)
* [Third Dimension Youtube Channel](https://www.youtube.com/c/GapGunTV/videos)
* [Udacity Structured light](https://www.youtube.com/watch?v=mSsnf5tqXnA)
* [I3D Past Projects Youtube Channel](https://www.youtube.com/channel/UCFGXYrIrc_27FroFOH36mVw/videos)
* [FabScan PI - An Open-Source 3D Laser Scanner](https://github.com/mariolukas/FabScanPi-Server)
---
## Photogrammetry and 3D Reconstruction
* [Zhaoyang Wang's Homepage](https://sites.google.com/cardinalmail.cua.edu/wangz/)
* [AliceVision Framework](https://github.com/alicevision/AliceVision)
* [PCL(Point Cloud Library)](https://github.com/PointCloudLibrary/pcl)
* [Open3D: A Modern Library for 3D Data Processing](https://github.com/intel-isl/Open3D)
* [Andreas Geiger Youtube Channel](https://www.youtube.com/user/cvlibs/videos)
* [3d Scan Anything Using Just a Camera](https://www.instructables.com/3d-Scan-Anything-Using-Just-a-Camera/)
* [Deep Learning for “Exotic” Data Like 3D Meshes and Point-Clouds](https://www.youtube.com/watch?v=fY_BzTmU9io)
---
## Video Streaming
* [GStreamer Tutorials](https://gstreamer.freedesktop.org/documentation/tutorials/index.html?gi-language=c)
* [Repo of collected sources and projects related to GStreamer](https://github.com/jackersson/awesome-gstreamer)
* [FFmpeg plugin for Flutter](https://github.com/tanersener/flutter-ffmpeg)
* [Gstreamer command-line cheat sheet](https://github.com/matthew1000/gstreamer-cheat-sheet)
* [GStreamer UDP stream examples](https://gist.github.com/reinzor/812a1dadd62dcf2a309c9c99af92244f)
* [RTSP test stream URL(Big Buck Bunny)](rtsp://wowzaec2demo.streamlock.net/vod/mp4:BigBuckBunny_115k.mov)
* [Install All Essential Media Codecs in Ubuntu With This Single Command ](https://itsfoss.com/install-media-codecs-ubuntu/)
* [What’s the Difference Between Codecs & Containers?](https://www.encoding.com/blog/2014/01/13/whats-difference-codecs-containers/#:~:text=Simply%20put%2C%20a%20codec%20is,for%20compressing%20data%2C%20especially%20video.&text=In%20comparison%2C%20a%20container%20is,referred%20to%20as%20a%20format.)
* [Gstreamer basic real time streaming tutorial](http://www.einarsundgren.se/gstreamer-basic-real-time-streaming-tutorial/)
* [Stream Video using Gstreamer RTSP Server](https://pmungekar7.medium.com/stream-video-using-gstreamer-rtsp-server-ca498f4a54bd)
* [The All You Need Guide to Video Codecs and Compression](https://tubularinsights.com/guide-video-codecs-compression/)
* [Accelerated GStreamer User Guide](https://developer.download.nvidia.com/embedded/L4T/r32_Release_v1.0/Docs/Accelerated_GStreamer_User_Guide.pdf?i_Y2wpVYeC4aKDkehQNi7nZijaqPu-zUqO228keXSjtyD_7FHVxEAYFmYhzbmT-MgdoAimuP1FuS62KQPIADER2TQ0BaCa0MJNpQLjDYzEzqhZtQEKo6q2RiyXtc4vhbHiUxfvJ8mfLS8Sn-_USkttoqhaLmk5Epe_--Sh4rapNOZ-lHYq8)
* [How to Build Gstreamer RTSP Server](https://askubuntu.com/a/1095607)
* [How to make a Raspberry Pi an RTSP streamer and how to consume this?](https://gist.github.com/lemonlatte/799a43288b0e093f9c95ad83ae4962a3)
* [How to setup an RTSP server on Headless Raspberry Pi and stream RPi Camera data using GStreamer?](https://github.com/mucozcan/rpi-rtsp-stream)
* [Video streaming from Raspberry PI - Python vs. raspivid + netcat](https://stackoverflow.com/questions/54942027/video-streaming-from-raspberry-pi-python-vs-raspivid-netcat)
* [complete list of ffmpeg flags / commands](https://gist.github.com/tayvano/6e2d456a9897f55025e25035478a3a50)
---
## Math
* [Eigenvectors and eigenvalues](https://www.youtube.com/watch?v=PFDu9oVAE-g)
---
## Production Level
* [Optimizing TensorFlow Models for Serving (Google Cloud AI Huddle)](https://www.youtube.com/watch?v=fesdKLTZFBE)
* [Implementing YOLOv4 with TensorFlow, TFLite and TensorRT](https://www.youtube.com/watch?v=iPwepy-SVCQ)
* [How to Build Object Detection APIs Using TensorFlow and Flask](https://www.youtube.com/watch?v=_UqmgHKdntU)
* [An introduction to MLOps on Google Cloud](https://www.youtube.com/watch?v=6gdrwFMaEZ0)
* [Accelerating Machine Learning App Development with Kubeflow Pipelines (Cloud Next '19)](https://www.youtube.com/watch?v=TZ1lGrJLEZ0)
* [TensorFlow Lite Flutter Plugin](https://github.com/am15h/tflite_flutter_plugin)
* [FFmpeg plugin for Flutter](https://github.com/tanersener/flutter-ffmpeg)
* [NVIDIA Jetson Nano and NVIDIA Jetson AGX Xavier for Kubernetes (K8s) and machine learning (ML) for smart IoT](https://github.com/helmut-hoffer-von-ankershoffen/jetson)
* [Submit it!: a lightweight tool for submitting Python functions for computation within a Slurm cluster](https://github.com/facebookincubator/submitit)
----------------------------------------------------------------
## IoT
* [Eclipse Mosquitto - An open source MQTT broker](https://github.com/eclipse/mosquitto)
* [MQTT client/broker using Python asynchronous I/O](https://github.com/beerfactory/hbmqtt)* [Zetta: An API-first, open source software platform for the Internet of Things.](https://github.com/zettajs/zetta)
---------------
## OOP
* [Interfaces and Metaclasses in Python ](https://www.godaddy.com/engineering/2018/12/20/python-metaclasses/#:~:text=Unfortunately%2C%20Python%20doesn't%20have,in%20order%20to%20be%20initialized.)* [Actor Model Design Pattern(Python)](https://pykka.readthedocs.io/en/stable/)
---
## Linux
* [Renaming files in a folder to sequential numbers](https://stackoverflow.com/a/34153342)
* [How to Connect to a Raspberry Pi Remotely via SSH](https://howchoo.com/g/mgi3mdnlnjq/how-to-log-in-to-a-raspberry-pi-via-ssh)
* [DebuggingWithGdb](https://wiki.python.org/moin/DebuggingWithGdb)
* [How to fix a broken package, when “apt-get install -f” does not work?](https://askubuntu.com/questions/141370/how-to-fix-a-broken-package-when-apt-get-install-f-does-not-work)
* [Linux From Scratch](https://www.linuxfromscratch.org/lfs/downloads/stable-systemd/LFS-BOOK-10.1-systemd.pdf)
* [How do I make a RAM disk?](https://askubuntu.com/questions/152868/how-do-i-make-a-ram-disk)
* [Better Than Top: 7 System Monitoring Tools for Linux to Keep an Eye on Vital System Stats](https://itsfoss.com/linux-system-monitoring-tools/)
* [Sharing WiFi Connection over Ethernet on Ubuntu 18.04](https://crookm.com/journal/2018/sharing-wifi-connection-over-ethernet)
* [How to check if port is in use on Linux or Unix](https://www.cyberciti.biz/faq/unix-linux-check-if-port-is-in-use-command/)
---
## Tools
* [Optuna - A hyperparameter optimization framework](https://optuna.org/)
* [A Neural Network Playground](https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.32994&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false)
* [Make Sense - Image Annotation Tool](https://www.makesense.ai/)
* [Netron - Neural Network Viewer](https://netron.app/)
* [Lens Focal Length and Stereo Baseline Calculator](https://nerian.com/support/calculator)
* [Lightning: The ultimate PyTorch research framework ](https://pytorchlightning.ai/)
* [FiftyOne: The open-source tool for building high-quality datasets and computer vision models](https://github.com/voxel51/fiftyone)
* [youtube-dl: Command-line program to download videos from YouTube.com and other video sites](https://github.com/ytdl-org/youtube-dl/)
---
## Mix of interesting and cool stuff
* [Human Vision](https://www.youtube.com/watch?v=-nt80JUNwlw&list=PLjMXczUzEYcHvw5YYSU92WrY8IwhTuq7p&index=2)
* [Mercedes-Benz MAGIC BODY CONTROL | S-Class](https://www.youtube.com/watch?v=ScpgI1w5F6A)
* [LiDAR vs Computer Vision - Why Tesla Autonomy Will Win](youtube.com/watch?v=WGm5Yc4JWug)
* [How AI Powers Self-Driving Tesla with Elon Musk and Andrej Karpathy](https://www.youtube.com/watch?v=FnFksQo-yEY)
* [Andrej Karpathy - AI for Full-Self Driving at Tesla](https://www.youtube.com/watch?v=hx7BXih7zx8)
* [OpenPilot](https://github.com/commaai/openpilot)
* [Yannic Kilcher Youtube Channel](https://www.youtube.com/c/YannicKilcher/videos)
---