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Fire Detection Video Dataset – 14,592 Videos for Fire and Smoke Recognition

fire detection dataset
fire recognition dataset
fire and smoke detection dataset
fire video dataset
fire identification dataset
flame detection dataset
indoor fire detection dataset

This dataset contains 14,592 fire videos from indoor and outdoor scenes. The data covers multiple scenes, shooting angles, resolutions and time periods. This dataset can be used for tasks such as fire detection, flame recognition, and fire & smoke identification tasks.

Paid Datasets
This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.
SpecificationsSpecifications
Data size
14,592 videos, the total duration is 213 hours 33 minutes 49.7,001 seconds
Collecting environment
including indoor and outdoor scenes
Data diversity
multiple scenes, multiple shooting angles, multiple collecting time, multiple resolution
Device
including surveillance cameras, cellphones
Collecting angle
looking down angle, eye-level angle, looking up angle
Data format
the video data format is .mp4
Accuracy
According to the collecting requirement, the accuracy is more than 98%; The accuracy of label naming is more than 98%
Sample Sample
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What types of computer vision applications can Nexdata’s datasets support?

Nexdata’s computer vision datasets support a wide range of AI applications, including image classification, object detection, image segmentation, facial and human-related recognition, scene understanding, autonomous driving, and other visual perception tasks. Depending on the dataset, data may include images, videos, bounding boxes, polygons, keypoints, segmentation masks, text annotations, and other structured labels.

Can Nexdata customize Computer Vision datasets based on our specific requirements?

Yes. If our off-the-shelf Computer Vision datasets do not fully meet your requirements, Nexdata provides flexible custom data collection, annotation, and curation services. We can customize data based on your target objects, environments, scenarios, camera specifications, geographic locations, data volume, annotation formats, and quality standards to support specific model training and evaluation needs.

How does Nexdata ensure the quality and scalability of its Computer Vision datasets?

Nexdata applies multi-stage quality control throughout data collection, annotation, validation, and delivery. Depending on project requirements, we can implement customized annotation guidelines, multi-level reviews, consistency checks, and quality sampling to ensure dataset accuracy and consistency. Our data collection and processing capabilities can also be scaled to support large-volume Computer Vision projects.

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