Abbreviation of OpenCV is an Open-source computer vision library which is developed by Intel in 1999. It is a cross-platform library that works on processing and analyzing the features of capture videos and images. Computer vision that inherits both AI and machine learning enables the machine to identify, understand, and process images like humans. In OpenCV, the computer trains itself by captured images and videos and uses that information to classify the objects, such as the application of face detection and object detection. It works on real-time image processing. It supports various algorithms.
Which programming language is compatible with OpenCV?
It is compatible with C/C++, but Java and Python API can also use OpenCV.
Application Areas of OpenCV
- Face detection and recognition
- Gesture recognition
- Image and object detection
- Image processing
Tensor-flow is an open-source end-to-end library that works on numerical computations. A platform for machine learning has libraries and resources to gather data, train models, predict estimations, and analyze future results. It helps the developer to deploy machine learning-based applications. It is used for SaaS(software as a service) applications.
It is a mathematical library based on data flow that focuses on acquiring data and trains machines according to it. TensorFlow allows the developer to perform the computational task by creating the graph. Every connection and node of the graph shows data and arithmetic operations, respectively. It helps machine learning train models, identify patterns, recognize voice and images, and make decisions with less human interference.
Under the Apache license, TensorFlow was developed by Google Brain Team in 2015 to power machine learning applications and AI development. Google developed it for its internal use.
TensorFlow trains and executes deep neural networks for Algorithms such as NLP (natural language processing), voice search, image recognition. It is a user-friendly, flexible application.
Applications of TensorFlow
Applications related to image recognition, face recognition, such as Google lens
text-based applications, which are use cases of deep neural networks such as language detection, spam email, and threat detection. Google translator is also the most popular implementation area of text-based applications.
Which programming language is compatible with TensorFlow?
Google team built TensorFlow software in C++ language, but developers can also use Python to develop AI-based applications.
OpenCV Vs TensorFlow
|An open-source, cross-platform library that works on real-time computer vision||An open-source platform that works on Tensors which is a generalization of vectors|
|It is designed to increase the computational efficiency of real-time applications.||It is designed for mathematical solutions by using dataflow charts|
|Image processing Tool||Machine Learning tool|
|OpenCV, select by developers for “Computer Vision.”||Coders works on TensorFlow for high performance|
|OpenCV is a library for computer vision||TensorFlow is a framework(foundation where software develops) for Machine-intelligence.|
|Applications are image processing, face detection, gesture recognition||Applications are pattern detection, smart locks, self-driving cars|
|Support C++ and Python language||Support C, C++, Java, and Python language|
In this article, we compare two open-source platforms: OpenCV, which is an image processing tool, and TensorFlow that is a machine learning tool. This article covers OpenCV and TensorFlow definitions, application area, language support, and a to-the-point comparison between OpenCV and TensorFlow.