Just like the name suggests, computer vision is associated with artificial intelligence that allows computers to extract useful information from digital images and other visual inputs. It is like allowing a machine to see and take actions based on the visual input it gets.

Computer vision is achieved by the implementation of deep learning and complex convolutional neural network. The reason deep learning is being used is because of the complexity in training and for accurate predictions, higher level training is required. The machine learns from a huge amount of data, through multiple iterations until it recognizes the image properly.

The machine learning algorithm teaches itself about the context of visual data. With enough data fed through the system, the machine can easily teach itself to understand one image from the other. The algorithm starts by breaking down the given images into pixels and assigns specific tags or labels to them. These labels are then convoluted and the accuracy of the predicted results will be cross verified. The iterations are continued until the predictions start to come through.

Why computer vision ?

Giving machines the ability to see will help in more than one way for industries. As an example, through computer vision companies that are in the area of manufacturing products can easily sort through products, face detection can help identify individuals from a crowd, autonomous vehicles use this tech to detect and classify nearby objects.

Why python for computer vision.?

Open CV using python is the go-to for beginners looking to enter the field of computer vision. There is plethora of reasons as to why you should use python for doing computer vision. Python has huge number of libraries for OpenCV. The matplotlib visualisations are just as good as the one we get in MATLAB. The code debugging is also easier to do in python. And python has become the scientific language of the modern era, as MATLAB was a few years before.

What will I learn from studying computer vision with python?

You’ll be introduced to the fundamentals of OpenCV and matplotlib in python. All the libraries we could use for computer vision generation. Successful Implementation of OpenCV program, Building computer vision projects on your own, so on and so forth.

Is computer vision with python a good career path?

Having the skills for doing computer vision projects , along with a few other necessary skills like knowledge in fundamentals of machine learning, pattern recognition and designing can help you stand out in the industry that the combination of these skills are very rare and only a few can offer this. Therefore learning computer vision will be a really useful skillset in your arsenal./p>

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Curriculum
  • Indroduction
  • Processing In Python
  • Introduction To Computer Vision
  • Image Recognition
  • Unsupervised Learning Methods
  • Supervised Learning-Classify Images
  • Deep Learning For Image Classification
Projects
  • Develop a Project on Image processing

Just like the name suggests, computer vision is associated with artificial intelligence that allows computers to extract useful information from digital images and other visual inputs. It is like allowing a machine to see and take actions based on it.

Implementing computer vision is hard because of hardware limitations. Real time data processing is dependent on multiple hardware devices and the delay in communication between them makes the computations slow, results in increased network traffic and bottleneck in data flow. Only by overcoming these limitations, we can successfully implement efficient computer vision.

Machine vision is basically a subcategory of computer vision. Where Computer vision is an automated process of capturing and processing digital images, machine vision is used in industries to sniff out faults and defects.

  • OpenCV
  • Tensorflow
  • CUDA
  • VisoSuite
  • Simple CV
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