Places205 Dataset

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Visualization of the Places 205 Dataset in the Deep Lake UI

Places205 Dataset

What is Places205 Dataset?

The Places205 dataset is a large scene-centric dataset with exactly 205 common scene categories. The dataset was created for the task of Scene Recognition. Places205 training dataset contains around 2,500,000 images, with a minimum of 5,000 and a maximum of 15,000 images per scene. The validation set comprises 100 images per category (totaling 20,500 images), and the testing set has 200 images per category (a grand total of 41,000 images).

Downloading Places205 Dataset in Python

Instead of downloading the Places205, you can effortlessly load it in Python via our Deep Lake open-source with just one line of code.

Load Places205 Dataset

				
					import deeplake
ds = deeplake.load("hub://activeloop/places205")

Places205 Dataset Structure

Data Fields

images: tensor containing the image.
labels: an integer from 0 to 244 representing the scene category.

How to use Places205 Dataset with PyTorch and TensorFlow in Python

Places205 with PyTorch in Python.

				
					dataloader = ds.pytorch(num_workers = 2, shuffle = False, batch_size= 4)

2. Places205 with TensorFlow in Python.

				
					ds_tensorflow = ds.tensorflow()

Additional Information about Places205 Dataset.

Places205 Dataset Description

Homepage: http://places.csail.mit.edu/
Paper: B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva. Learning Deep Features for Scene Recognition using Places Database. Advances in Neural Information Processing Systems 27 (NIPS), 2014
Point of contact: http://people.csail.mit.edu/bzhou/

Places205 Dataset Curators

Bolei Zhou, Antonio Torralba, Aude Oliva, Aditya Khosla, Agata Lapedriza.

Places205 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!

Places205 Dataset Citation Information

				
					@inproceedings {NIPS2014_3fe94a00,
author = {Zhou, Bolei and Lapedriza, Agata and Xiao, Jianxiong and Torralba, Antonio and Oliva, Aude}, 
booktitle = {Advances in Neural Information Processing Systems},
editor = {Z. Ghahramani and M. Welling and C. Cortes and N. Lawrence and K. Q. Weinberger}, pages = {}, 
publisher = {Curran Associates, Inc.},
title = {Learning Deep Features for Scene Recognition using Places Database},
url = {https://proceedings.neurips.cc/paper/2014/file/3fe94a002317b5f9259f82690aeea4cd-Paper.pdf}, 
volume = {27},
year = {2014} }

Places205 Dataset FAQs

What is the Places205 dataset for Python?

The Places205 dataset is a large-scale scene-centric dataset with 41,000 images in 205 common scene categories. It has a validation set containing 100 images per category (a total of 20,500 images), and a testing set that contains 200 images per category.

What is the Places205 dataset used for?

The Places205 dataset is often used for scene classification. Since this dataset contains high-coverage and high-diversity images it is a popular dataset to use for visual recognition and scene classification.

How to download the Places205 dataset in Python?

You can load the Places205 dataset with one line of code using the open-source package Activeloop Deep Lake. See detailed instructions on how to load the Places205 dataset.

How can I use the Places205 dataset in PyTorch or TensorFlow?

You can stream the Places205 dataset while training a model in PyTorch or TensorFlow with one line of code using the open-source package Activeloop Deep Lake. See detailed instructions on how to use the Places205 Dataset with PyTorch and TensorFlow in Python.