The difficulty of computer vision depends on the problem complexity and the tools used. Basic tasks like edge detection or simple object tracking are relatively straightforward and can be achieved with tools like OpenCV.
However, advanced tasks such as real-time object detection or semantic segmentation require expertise in deep learning, access to large datasets, and significant computational resources. Developing robust models for real-world scenarios adds further challenges, including handling varying lighting, angles, and occlusions.
With modern frameworks and pre-trained models, the learning curve has been reduced, but mastery still requires a strong understanding of algorithms, mathematics, and programming.