Case Studies (Practical Python and OpenCV) | Adrian Rosebrock | downloadLast Updated on July 5, Computer vision is a subfield of artificial intelligence concerned with understanding the content of digital images, such as photographs and videos. Deep learning has made impressive inroads on challenging computer vision tasks and makes the promise of further advances. Before diving into the application of deep learning techniques to computer vision , it may be helpful to develop a foundation in computer vision more broadly. This may include the foundational and classical techniques, theory, and even basic data handling with standard APIs.
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Own a Raspberry Pi and want to use it to detect faces in video streams? Track objects in video? Or recognize handwriting? No problem! These videos are a fantastic asset to help you learn OpenCV and computer vision. Figure 4: The 2nd edition Ubuntu VirtualBox virtual machine has been re-engineered from the ground-up to support both Python 2. This VM has been re-engineered from the ground up and includes installations of both Python 2.
Has anybody used Practical Python and OpenCV + Case studies book by all practical rather than technical) and many of them are for free (I hope he will.
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Top 5 Computer Vision Textbooks
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I started reading it and then got busy with other things. The past couple of weeks, I decided to give the book another go and was able to finish it. Note that I started reading the 3rd edition of the book without realizing there was a 4th edition. This book contains 11 chapters across pages. It covers Python 3 and OpenCV 4 in the 4th edition. Practical Python and OpenCV is an interesting book. This is kind of an anomaly as a lot of technical books seem to be much longer.