![]() ![]() In these situations a camera solution could complement a traditional detector, in order to improve response times or to provide additional metrics such as the size and location of a fire. from toasters) and do not localise the fire particularly well. However they are prone to false detections (e.g. Traditional smoke detectors work by detecting the physical presence of smoke particles. ![]() Segmentation: requires annotation Motivation and challenges After a few hours of experimentation I generated a model of of 0.657, Precision of 0.6, Recall of 0.7, trained on 1155 images (337 base images + augmentation).Ĭlassification: I have yet to train my own model, but 95% accuracy is reported using ResNet50 Object detection: After experimenting with various model architectures I settled on Yolov5 pytorch model (see pytorch/object-detection/yolov5/experiment1/best.pt). In use this model will place a bounding box around any fire in an image. ![]() The purpose of this repo is to demonstrate a fire detection neural net model. ![]()
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