OAD
computervision-recipes
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| OAD | computervision-recipes | |
|---|---|---|
| 1 | 1 | |
| 118 | 9,115 | |
| 3.4% | - | |
| 6.1 | 3.9 | |
| 12 days ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| GNU General Public License v3.0 only | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
OAD
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Anyone know of any microscope that has an API that I can buy. Or in other words, one that I can programmatically control via coding?
All motorised microscopes can be controlled by the software provided/sold by the manufacturer (eg ZEN for ZEISS, NIS for Nikon, LAS for Leica etc). ZEISS also offers interfaces to control the microscope using your own code (eg in Python or MATLAB): https://github.com/zeiss-microscopy/OAD
computervision-recipes
What are some alternatives?
VevestaX - 2 Lines of code to track ML experiments + EDA + check into Github
fastdup - fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.
oemer - End-to-end Optical Music Recognition (OMR) system. Transcribe phone-taken music sheet image into MusicXML, which can be edited and converted to MIDI.
VIAME - Video and Image Analytics for Multiple Environments
PUMA - 3D Printed Microscope
Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.
BioImager - A .NET microscopy imaging application based on Bio library. Supports various microscopes by using imported libraries & GUI automation. Supports XInput game controllers to move stage, take images, run ImageJ macros on images or Bio C# scripts.
One-Piece-Image-Classifier - A quick image classifier trained with manually selected One Piece images.
smletsexchangeconnector - SMLets PowerShell based Exchange Connector for controlling Microsoft System Center Service Manager 2016+
sod - An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)
MLB-Pitch-Identification-with-ML - Identify the name of a pitch being thrown using a machine learning model.
opencv - Experimenting using Machine Vision OpenCV and Python to create software suitable for driving a Golf launch monitor similar to technology like SkyTrak, GC2 and GC Quad