People Detection Computer Vision Project
yoloV5
Updated 5 months ago
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Classes (63)
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Bicycle Bike Car Cyclist Pedestrian Pedestrians Persona Pessoa
Signboard
Stopper
aeroplane auto bag berdiri
bicycle bike bird boat bottle bus car cat chair cow cyclist dianzhuan
diningtable dog face football forklift handbag head helmet high
horse jatuh
laptop low
medium
motorbike number_plate people person persons player pottedplant refrigerator sheep sofa teddy bear train truck tv
tvmonitor vase Metrics
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Description
Detect people in all kinds of scenarios using this generalized dataset.
For this dataset, we curated images and annotations from various projects from Universe to create a well performing model regardless of scenario by pulling from a variety of specialized datasets.
We selected data that ranged in type, context, annotation size, annotation count and cameras.
This dataset used images and/or annotations from the following Universe projects:
- First Pedestrian Test (CC BY 4.0 license)
- person_camera_security1 (CC BY 4.0 license)
- Human Action Recognition 2000 (CC BY 4.0 license)
- People Detection (CC BY 4.0 license)
- contador-de-gente teste 3 (CC BY 4.0 license)
- OD3 (CC BY 4.0 license)
- Person Detection (CC BY 4.0 license)
- MOT17-03-DPM
- The Curve (CC BY 4.0 license)
- pedestrain safety (CC BY 4.0 license)
- People Detection (CC BY 4.0 license)
- people、rabish (CC BY 4.0 license)
- Pascal VOC 2012 (CC BY 4.0 license)
- Person Detection (General) (CC BY 4.0 license)
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
people-detection-o4rdr-emua6_dataset,
title = { People Detection Dataset },
type = { Open Source Dataset },
author = { yoloV5 },
howpublished = { \url{ https://universe.roboflow.com/yolov5-ihl1p/people-detection-o4rdr-emua6 } },
url = { https://universe.roboflow.com/yolov5-ihl1p/people-detection-o4rdr-emua6 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2025 },
month = { jan },
note = { visited on 2025-06-17 },
}