In the remainder of today’s blog post I’ll be demonstrating how you can use Google Images to quickly (and easily) gather training data for your deep learning models.
So is there a way to leverage the power of Google Images to quickly gather training images and thereby cut down on the time it takes to build your dataset? How in the world do you gather enough images when training deep learning models?ĭeep learning algorithms, especially Convolutional Neural Networks, can be data hungry beasts.Īnd to make matters worse, manually annotating an image dataset can be a time consuming, tedious, and even expensive process. José has a point - without enough training data, your deep learning and machine learning models can’t learn the underlying, discriminative patterns required to make robust classifications. I’m confident I can solve this project, but I need more data.
I’ve found a small dataset (~100 images per class), but my models are quick to overfit and far from accurate. I’m working on a project where I need to classify the scenes of outdoor photographs into four distinct categories: cities, beaches, mountains, and forests. This is by far the best resource I’ve seen for deep learning. Hey Adrian, thanks for putting together Deep Learning for Computer Vision with Python.
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