Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
1K - 10K
Tags:
deep-learning
computer-vision
fire-detection
wildfire-detection
image-classification
transfer-learning
License:
File size: 2,774 Bytes
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pretty_name: "Deep Learning Project"
language:
- en
license: other
task_categories:
- image-classification
tags:
- deep-learning
- computer-vision
- fire-detection
- wildfire-detection
- image-classification
- transfer-learning
- severity-classification
- feature-extraction
- recommendation-generation
- tensorflow
- keras
---
# Deep Learning Project
## Dataset Summary
This repository contains the datasets, trained models, notebooks, experiments, feature-extraction outputs, and supporting resources developed for a deep learning project focused on **fire detection, fire severity classification, and related computer vision tasks**.
The project covers multiple stages of a deep learning workflow, including binary fire classification, three-class fire severity classification, feature extraction, dimensionality reduction, clustering, and recommendation generation.
The repository contains approximately **2.1 GB of files across 1,700+ files**.
## Dataset Details
### Dataset Description
The repository is a collection of datasets and machine-learning artifacts rather than a single standardized dataset. It contains resources used across multiple deep learning experiments and application components.
The main components include:
- Fire vs. No-Fire binary image classification
- Three-class fire severity classification
- Feature extraction
- Severity clustering
- Dimensionality reduction
- Recommendation generation
- Generated severity-image samples
- Jupyter notebooks
- Trained models and model checkpoints
- Supporting application resources
### Main Project Components
#### Fire vs. No-Fire Binary Classification
`Fire_vs_No_Fire_Binary_Classification/`
Contains resources for binary image classification between:
- Fire
- No Fire
The project includes experiments using:
- ResNet50
- Custom CNN
- VGG16
- EfficientNetB0
The directory also contains a dataset, trained model resources, and VGG16 checkpoints.
#### Fire Severity Detection
`Severity_Detection_Tri_Classification/`
Contains resources for three-class fire severity classification:
- Mild
- Moderate
- Severe
The project includes experiments using:
- Xception
- EfficientNetB0
Additional components include feature extraction, clustering, dimensionality reduction, and dataset preparation.
#### Severity Dataset
`Severity_Detection_Tri_Classification/Severity_Altered_Dataset/`
Contains an image dataset organized into training, validation, and testing splits.
```text
severity_dataset/
├── train/
│ ├── mild/
│ ├── moderate/
│ └── severe/
├── val/
│ ├── mild/
│ ├── moderate/
│ └── severe/
└── test/
├── mild/
├── moderate/
└── severe/ |