The performance of classification is generally better if:
the training images are representative of the variation typically found within the object class. For example, to train a "dog" class, use images of dogs of different sizes, breeds, colors, and from different viewpoints.
the longest dimension (width or height) of the training image is at least 500 pixels - smaller images might result in reduced accuracy.
High-resolution images where the object covers a small proportion of the image make poor training images. If you have a large image showing the object and it can be cropped such that its longest dimension still exceeds 500 pixels, HPE recommends cropping the image. If you crop an image, leave a gap around the object of at least 16 pixels.
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