What is data augmentation in computer vision?
An example of an AI chatbot conversation about data augmentation techniques in computer vision.
What is data augmentation in computer vision?
Data augmentation is a technique used to increase the diversity of your training dataset by applying various transformations.
What are some common techniques used for data augmentation?
Common techniques include rotation, flipping, scaling, cropping, and color adjustments.
How does data augmentation help improve model performance?
It helps by providing more varied examples, reducing overfitting, and improving the model's ability to generalize.
Can you give an example of how to implement data augmentation in Python?
Sure! You can use libraries like TensorFlow or PyTorch. For example, in TensorFlow, you can use the ImageDataGenerator class.
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