Fire and Smoke Detection

Collecting over 1000 images of fire and smoke captured by CCTV cameras, followed by labeling each image using labeling tools. Subsequently, training an object detection algorithm on this annotated dataset. Ultimately, the accuracy of our model reached 94% when evaluated on our test dataset.