Image processing in machine learning has evolved significantly since its inception in the 1960s, with recent advancements in deep learning and open-source projects accelerating its development. This growth has led to the creation of numerous libraries and frameworks, such as OpenCV, TensorFlow, and PyTorch, which facilitate the construction of efficient image processing applications. Additionally, datasets like Diversity in Faces and Waymo Open Dataset provide essential resources for training machine learning models, while ready-made solutions like MobileNet and EDVR offer specialized tools for tasks such as image classification and video frame restoration. These tools and datasets enable developers to enhance their computer vision projects by leveraging pre-built solutions, thereby saving time and resources while improving project outcomes.