INFRARED Computer Vision Project
Updated 2 years ago
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This infrared street scenes computer vision dataset labels cars, people, bicycles, and dogs (although dogs are severely under-represented; see the health check for more info on class distribution). It contains over 10,000 grayscaled thermal images taken with a FLIR camera that can be used for detecting objects at night or in poor lighting conditions.
It may be particularly useful in creating self-driving autonomous vehicles, due to the forward-looking dashcam style footage of roads, pedestrians, and vehicles. There is also a pre-trained model available for testing.
Example use-cases include:
- Prototyping a self-driving vehicle
- Creating a tool that warns drivers if pedestrians are about to cross their path
- Counting cars driving by (or people walking by) at night
- Intelligently turning lights on and off for people and vehicles (but not animals)
- Detecting unauthorized access to unlit facilities
You could also re-label other objects of interest from this dataset to train a model to detect other types of things.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
infrared-6s0ke_dataset,
title = { INFRARED Dataset },
type = { Open Source Dataset },
author = { Calib Buckton },
howpublished = { \url{ https://universe.roboflow.com/calib-buckton/infrared-6s0ke } },
url = { https://universe.roboflow.com/calib-buckton/infrared-6s0ke },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { sep },
note = { visited on 2024-10-07 },
}