Fire-Flame-Dataset
An image dataset for training fire and frame detection AI
Fire-Flame-Dataset is a dataset collected in order to train machine learning model to recognize Fire, smoke, and neutral(images without fire or smoke).This a dataset containing about 3000 images and 3 classes which include:
- Fire
- Smoke
- neutral
There are 1000 images in each category and 900 for train and 100 for testing
Download, Training and Prediction
The Fire-Flame-Dataset is provided for download in the release section of this repository. You can download the dataset via this link Fire-Flame-Dataset.
The implementation code in which the model was train with has been provide in this repository. The model was trained with train with resnet50 and a accuracy of 85% on the test data was achieved. The python codebase is contained in fire_flame.ipynb.
Some of the prediction results are shown below:
('Image of:', 'Class: Fire', 'Confidence score: 1.0')
('Image of:', 'Class: Fire', 'Confidence score: 0.990234375')
('Image of:', 'Class: Neutral', 'Confidence score: 0.99365234375')
('Image of:', 'Class: Neutral', 'Confidence score: 1.0')
('Image of:', 'Class: Smoke', 'Confidence score: 0.4462890625')
('Image of:', 'Class: Smoke', 'Confidence score: 0.9970703125')
Reqirements
- Python 3
- Pytorch
- Numpy
- Matplotlib
- TorchFussion