![]() ![]() Think about how long it would take to load all of them into memory for training, in batches, perhaps hundreds or thousands of times. ImageNet is a well-known public image database put together for training models on tasks like object classification, detection, and segmentation, and it consists of over 14 million images. If you’re interested, you can read more about how convnets can be used for ranking selfies or for sentiment analysis. Algorithms like convolutional neural networks, also known as convnets or CNNs, can handle enormous datasets of images and even learn from them. Increasingly, however, the number of images required for a given task is getting larger and larger. jpg files, is both suitable and appropriate. Even if you’re using the Python Imaging Library (PIL) to draw on a few hundred photos, you still don’t need to. Why would you want to know more about different ways of storing and accessing images in Python? If you’re segmenting a handful of images by color or detecting faces one by one using OpenCV, then you don’t need to worry about it. ![]()
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