Image Classification

Image classification is the task of assigning a label or class to an entire image. Images are expected to have only one class for each image.

For more details about the image-classification task, check out its dedicated page! You will find examples and related materials.

Explore all available models and find the one that suits you best here.

There are currently no snippet examples for the image-classification task, as no providers support it yet.

Headers
authorization	string	Authentication header in the form `'Bearer: hf_**'` when `hf_**` is a personal user access token with “Inference Providers” permission. You can generate one from your settings page.

Payload
inputs*	string	The input image data as a base64-encoded string. If no `parameters` are provided, you can also provide the image data as a raw bytes payload.
parameters	object
function_to_apply	enum	Possible values: sigmoid, softmax, none.
top_k	integer	When specified, limits the output to the top K most probable classes.

Body
(array)	object[]	Output is an array of objects.
label	string	The predicted class label.
score	number	The corresponding probability.

Inference Providers