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Commercial
Crowd Counting Dataset
Crowd counting dataset is a labeled dataset including images of dense crowds with key point annotations and metadata on crowd sizes, designed for training deep learning models in crowd counting, object detection, and data analysis across a larger scale of counting datasets
-
- Photos
- 647
-
- People in a crowd
- 1,000 - 13,000
- Smart City
- Computer Vision
- Machine Learning
- Keypoint Detection
- Security
- Smart City
- Computer Vision
- Machine Learning
- Keypoint Detection
- Security
Crowd counting dataset is a labeled dataset including images of dense crowds with key point annotations and metadata on crowd sizes, designed for training deep learning models in crowd counting, object detection, and data analysis across a larger scale of counting datasets
- Smart City
- Computer Vision
- Machine Learning
- Keypoint Detection
- Security
-
- Photos
- 647
-
- People in a crowd
- 1,000 - 13,000
Dataset Info
| Characteristic | Data |
| Description | Crowd photos with labeling for determining crowd density and movement, and counting the number of people |
| Data types | Image |
| Tasks | Crowd control, object detection, and computer vision |
| Total number of photos | 647 |
| Type of crowd density | 0-1000, 1000-2000, 2000-3000, 3000-4000, 4000-5000 |
| Labeling | Metadata (type of crowd density) and key points labeling |
Technical
Characteristics
| Characteristic | Data |
| Image Extensions | JPG |
| Extension of labeling file | JSON |
Statistics
- Number of images by the type of a crowd:
Dataset Use Cases
FAQs
What types of annotations are provided?
The dataset provides metadata about crowd density categories as well as key point labeling for individuals in images.
How was the data collected?
Crowd Counting Dataset was created by parsing images from the internet, including protests, concerts, and other large-scale gatherings. This approach ensures a wide range of crowd sizes and environments, giving researchers diverse training data for crowd analysis and recognition technology.
How long does it take to receive the dataset?
The process begins once you submit a request. Our team will review the details with you and complete the necessary documents. After signing and payment, the dataset is delivered within 3–10 days.
Is this a real-world dataset or synthetic data?
Crowd Counting Dataset is a real-world dataset, not synthetic data. It contains photos of actual crowds taken from events such as protests, concerts, and other mass gatherings.
What crowd density range does the dataset cover?
Images are categorized into five density bands: 0–1,000, 1,000–2,000, 2,000–3,000, 3,000–4,000, and 4,000–5,000 people. This banding lets models train on a graduated scale from sparse gatherings to dense crowds.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. Each dataset is fully GDPR-compliant and meets data protection obligations. All collected information comes from permissible sources.
What is key point annotation, and why does it matter for crowd counting?
Key point annotation marks the location of each individual within a crowd image, rather than using bounding boxes. This precision is critical for accurately estimating headcounts in dense, overlapping scenes.
How are Unidata datasets licensed?
Unidata datasets run on a dual licensing model: free evaluation samples are provided, while the entire dataset must be purchased.
Still have questions about using Unidata datasets?
Read our user-guides
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