Caltech 256 Dataset

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Visualization of the Caltech 256 dataset in the Deep Lake UI

Caltech 256 dataset

What is Caltech 256 Dataset?

Caltech-256 is an object recognition dataset of 30,607 real-world images. The images of the dataset are of various sizes. Caltech-256 contains 257 classes (256 object classes and an additional clutter class). Each class in Caltech-256 is represented by at least 80 images. The dataset is often considered an improvement to the Caltech 101 dataset since it has new features such as larger category sizes, new and larger clutter categories, and overall increased difficulty.

Download Caltech 256 Dataset in Python

Instead of downloading the Caltech 256 dataset in Python, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code.

Load Caltech 256 Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/caltech256")

Caltech 256 Dataset Structure

Caltech 256 Data Fields

image: tensor containing the image.
labels: tensor that identifies the object in an image.

Caltech 256 Data Splits

The Caltech 256 dataset training set is composed of 30607 images.

How to use Caltech 256 Dataset with PyTorch and TensorFlow in Python

Train a model on Caltech 256 dataset with PyTorch in Python

Let’s use Deep Lake built-in PyTorch one-line dataloader to connect the data to the compute:

				
					dataloader = ds.pytorch(num_workers=0, batch_size=4, shuffle=False)

Train a model on Caltech 256 dataset with TensorFlow in Python

				
					dataloader = ds.tensorflow()

Additional Information about Caltech 256 Dataset

Caltech 256 Dataset Description

Homepage:http://www.vision.caltech.edu/datasets/
Paper: Griffin, G. Holub, AD. Perona, P. The Caltech 256
Point of Contact: N/A

Caltech 256 Dataset Curators

Griffin, G. Holub, AD. Perona

Caltech 256 Dataset Licensing Information

Deep Lake users may have access to a variety of publicly available datasets. We do not host or distribute these datasets, vouch for their quality or fairness, or claim that you have a license to use the datasets. It is your responsibility to determine whether you have permission to use the datasets under their license.

If you’re a dataset owner and do not want your dataset to be included in this library, please get in touch through a GitHub issue. Thank you for your contribution to the ML community!

Caltech 256 Dataset Citation Information

				
					@inproceedings{,
  title = {The Caltech 256},
  author = {Griffin, G. Holub, AD. Perona},
}

Caltech 256 Dataset FAQs

What is the Caltech 256 dataset for Python?

Caltech-256 is an object category dataset consisting of 256 object categories and including a total of 30607 images. It is an improvement to Caltech-101 as it has over double the number of categories, and the minimum number of image categories is increased by 49. Also, artifacts due to image rotation are avoided.

How to download the Caltech 256 dataset in Python?

You can load Caltech 256 dataset fast with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to load Caltech 256 dataset training subset in Python.

How can I use Caltech 256 dataset in PyTorch or TensorFlow?

You can stream Caltech 256 dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake in Python. See detailed instructions on how to train a model on Caltech 256 dataset with PyTorch in Python or train a model on Caltech 256 dataset with TensorFlow in Python.