What is Tensorflow OpenCV?

Data Science, AI and ML
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#1

Tensorflow OpenCV

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#2

TensorFlow is a free open source math library required for implementing neural networks. It uses Python to provide a convenient front-end API for building applications with the framework while executing those applications in high-performance C++.

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#3

OpenCV is a library which is widely used for Computer Vision. For ex. Facial recognition, Optical character recognition.

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#4

OpenCv is basically a programming library we use in Computer Vision where we see the real time data

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#6

First I should point out that you are trying to compare two different things namely a framework and a library. TensorFlow is a framework for machine learning, and OpenCV is a library for computer vision.

OpenCV (Open Source Computer Vision Library) acts as a toolkit for computer vision . It contains built-in classes and methods that can be used for image and video processing and analyses. You can also do machine learning in OpenCV. Most of its built-in machine learning algorithms are built for its primary purpose which is computer vision.

Tensorflow is commonly used for machine learning specifically the family of deep leaning algorithms. These will take a long time to finish and that’s where the use of GPUs come in because they provide better processing speed compared to CPUs. OpenCV GPU module is used for that. You will be the one to pick which classes and methods to use so at least some knowledge about GPU programming will be helpful.

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OpenCV (Open Source Computer Vision Library) acts as a toolkit for computer vision . It contains built-in classes and methods that can be used for image and video processing and analyses. You can also do machine learning in OpenCV. Most of its built-in machine learning algorithms are built for its primary purpose which is computer vision. It has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
Read more here (About - OpenCV library).
Tensorflow is commonly used for machine learning specifically the family of deep leaning algorithms. These will take a long time to finish and that’s where the use of GPUs come in because they provide better processing speed compared to CPUs. OpenCV GPU module is used for that. You will be the one to pick which classes and methods to use so at least some knowledge about GPU programming will be helpful. In Tensorflow, you can easily use the GPU implementation by setting the number of GPUs you have or if you want to use both. Here’s a documentation on how easy you can do it: https://www.tensorflow.org/tutorials/using_gpu
Overall, if you really want to learn about how computer vision works from the initial steps to the last, I suggest you learn OpenCV first then use Tensorflow when you’re ready to train a deep learning algorithm for better performance/accuracy results.