Classification

Image Classification - single class per image

Here, each image is labeled with a class it belongs to. This is called single-label classification.

Examples

Orange

Broccoli

Glasses

Image Classification - multiple classes per image

You may also want to specify more than one class for the image. This is called multi-label classification.

While in single-label classification, the model predicts one of the specified classes that has the highest probability, a multi-label model predicts all of the specified classes that were identified with some probability higher than set threshold.

Note: during the prediction process the optimal thresholds are set automatically, however they can be modified by user.

Example

Violin, trumpet, trombone, drums, clarinet, flute, contrabass, violoncello