Method for image data augmentation, method for training model using augmented image data and non-transitory computer-readable medium

A method for training model using augmented image data, performed in a computer system, comprising:

• retrieving multiple images, and respectively performing a data augmentation procedure on the multiple images, wherein any of the multiple images is randomly cropped multiple times at different positions to form multiple image blocks with random sizes;
• after a size of each of the multiple image blocks is adjusted, the multiple image blocks are randomly arranged and recombined to form an augmented image, and multiple ones of the augmented image are generated from the multiple images;
• and
• performing a deep-learning algorithm for training an intelligent model by a training set that is formed by the multiple augmented images.

A non-transitory computer-readable medium, which is used to store an instruction set including a first set of program codes to be performed by one or more processors of a computer system to implement a method for image data augmentation, wherein the method comprises:

• receiving multiple images;
• and
• respectively performing a data augmentation procedure on the multiple images, wherein the data augmentation procedure comprises:
• randomly cropping any of the multiple images multiple times at different positions to form multiple image blocks with random sizes;
• and
• adjusting a size of each of the multiple image blocks, randomly arranging the multiple image blocks, and recombining the multiple image blocks to be an augmented image;
• wherein, after repeatedly performing the data augmentation procedure, multiple ones of the augmented image are generated from the multiple images to form a training set used to train an intelligent model.