Datasets:
Tasks:
Object Detection
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
< 1K
License:
File size: 3,032 Bytes
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---
license: mit
task_categories:
- object-detection
language:
- en
tags:
- crowd-counting
- cnn
- detection
pretty_name: crowd counting
size_categories:
- n<1K
---
# Dataset Card for Dataset Name
<!-- Provide a quick summary of the dataset. -->
This dataset card has 6 .h5 and 6 .mat files that are used by the crowd counting demo
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
- **Curated by:** Rootstrap
- **License:** MIT
### Dataset Sources
<!-- Provide the basic links for the dataset. -->
- **Repository:** https://www.kaggle.com/datasets/tthien/shanghaitech
## Uses
<!-- Address questions around how the dataset is intended to be used. -->
The dataset is used for the demo
### Direct Use
<!-- This section describes suitable use cases for the dataset. -->
This dataset is intended to use only for the demo
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
This dataset was not used for training the model and can not be used for training a new model as it is very limited.
## Dataset Structure
<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
The dataset consist of 6 .h5 and 6 .mat.
## Dataset Creation
### Curation Rationale
<!-- Motivation for the creation of this dataset. -->
This dataset was created for the demo
### Source Data
<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
This .mat files where obtained from the ShangaiTech Dataset and the .h5 were generated from the .mat files using python.
#### Data Collection and Processing
<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
The ShangaiTech Dataset part B has 400 images. From this original dataset, 6 random files were gathered.
#### Who are the source data producers?
<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
@inproceedings{zhang2016single, title={Single-image crowd counting via multi-column convolutional neural network}, author={Zhang, Yingying and Zhou, Desen and Chen, Siqin and Gao, Shenghua and Ma, Yi}, booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, pages={589--597}, year={2016} }
## Bias, Risks, and Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
As we stated before, this dataset is only ment to be used for the demo and cannot be reproduced in any way.
## Dataset Card Authors
Rootstrap
## Dataset Card Contact
[email protected] |