Footpath Image Dataset Computer Vision Project
Updated 6 months ago
7
1
About Dataset This dataset is collected by DataCluster Labs. To download the full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai
This dataset is an extremely challenging set of over 500+ originally Footpath images captured and crowdsourced from over 200+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.
Dataset Features
- Dataset size: 500+
- Captured by: Over 100+ crowdsource contributors
- Resolution: 100% images HD and above (1920x1080 and above)
- Location: Captured with 200+ cities across India
- Diversity: Various lighting conditions like day, night, varied distances, viewpoints, etc.
- Device used: Captured using mobile phones in 2022-2023
Potential Applications:
This dataset can be used for training and evaluating machine learning models for various tasks related to autonomous vehicles, including:
- Footpath detection: Identifying areas suitable for pedestrian walking.
- Pedestrian path planning: Enabling autonomous vehicles to navigate safely around pedestrians.
- Object recognition: Distinguishing footsteps from other objects on the road (e.g., debris, puddles).
Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record
The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
footpath-image-dataset_dataset,
title = { Footpath Image Dataset Dataset },
type = { Open Source Dataset },
author = { DataCluster Labs },
howpublished = { \url{ https://universe.roboflow.com/datacluster-labs-agryi/footpath-image-dataset } },
url = { https://universe.roboflow.com/datacluster-labs-agryi/footpath-image-dataset },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { may },
note = { visited on 2024-11-21 },
}