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CARPK Dataset

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Visualization of the CARPK dataset in the Deep Lake UI

CARPK dataset

What is CARPK Dataset?

About 90,000 automobiles gathered by drone photography from four parking lots were assembled into the Car Parking Lot Dataset (CARPK) dataset. The photographs were taken by a drone from a height of around 40 meters. CARPK dataset is a large-scale dataset with an emphasis on automobile counts in various parking lots. Each car’s bounding box is marked on the image set (with the top-left and bottom-right points of each named bounding box precisely denoted).

Download CARPK Dataset in Python

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

Load CARPK Dataset Training Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/carpk-train")

Load CARPK Dataset Testing Subset in Python

				
					import deeplake
ds = deeplake.load("hub://activeloop/carpk-test")

CARPK Dataset Structure

CARPK Data Fields
  • image: tensor containing the image.
  • boxes: tensor to identify cars using a bounding box.
  • labels: tensor to label identifies an object as a car.
CARPK Data Fields

How to use CARPK Dataset with PyTorch and TensorFlow in Python

Train a model on CARPK 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 CARPK dataset with TensorFlow in Python
				
					dataloader = ds.tensorflow()

Additional Information about CARPK Dataset

CARPK Dataset Description

  • Repository: N/A
  • Paper: Meng-Ru Hsieh, Yen-Liang Lin, Winston H. Hsu. Drone-based Object Counting by Spatially Regularized Regional Proposal Networks, ICCV 2017
  • Point of Contact: N/A
CARPK Dataset Curators

Meng-Ru Hsieh, Yen-Liang Lin, Winston H. Hsu

CARPK 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!
CARPK Dataset Licensing Information
				
					@inproceedings{Hsieh_2017_ICCV,
Author = {@inproceedings{Hsieh_2017_ICCV,
Author = {Meng-Ru Hsieh and Yen-Liang Lin and Winston H. Hsu},
Booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
Title = {Drone-based Object Counting by Spatially Regularized Regional Proposal Networks},
Year = {2017},
organization={IEEE}
}},
Booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
Title = {Drone-based Object Counting by Spatially Regularized Regional Proposal Networks},
Year = {2017},
organization={IEEE}
}

CARPK Dataset FAQs

What is the CARPK dataset for Python?

CARPK dataset is a collection of approximately 90,000 cars in 4 distinct parking lots photographed by drones. The (PHANTOM 3 PROFESSIONAL). The photos were taken utilizing a robot at a tallness of around 40 meters. Every vehicle’s jumping enclosure is labeled the picture set. The upper left and base right places of all assigned bouncing boxes have been fastidiously recorded.

How to download the CARPK dataset in Python?

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

How can I use CARPK dataset in PyTorch or TensorFlow?

You can stream the CARPK 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 the CARPK dataset with PyTorch in Python or train a model on the CARPK dataset with TensorFlow in Python.

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