What do you like best?
Image processing like pixel editing and geometric transformations.
Video operations like object tracking face detection.
Support for machine learning techniques.
It is fast and open source.
What do you dislike?
Most of the times it uses single cores, hence not efficient at using the available processing resources.
Ease of use is less than Matlab, we may have to write lots of code to even load an image in OpenCV.
It's a little programming intensive. Could have been more user-friendly, where a whole lot of code can be written in a single line.
Recommendations to others considering the product
OpenCV is best for image processing in Python. It is faster than other available options.
It can be integrated with other python libraries like the tensorflow or keras to build sophisticated image and video processing models.
People with a little bit of programming knowledge should use this as it involves coding.
OpenCV is used for all sorts of image and video analysis, like facial recognition and detection, license plate reading, photo editing, advanced robotic vision, optical character recognition, and a whole lot more.
What business problems are you solving with the product? What benefits have you realized?
To process a video frame by frame. To resize each frame for prediction.
Subtracting the background. A lot of image and video analysis boils down to simplifying the source as much as possible. This almost always begins with a conversion to grayscale, but it can also be a color filter, gradient, or a combination of these.
Made processing a video faster and provided ease in python integration.