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- Fire-Detection-engine
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- Precision-98
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---
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```
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Classification report:
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weighted avg 0.9799 0.9798 0.9797 2424
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- Fire-Detection-engine
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---
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# **Fire-Detection-Engine**
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The **Fire-Detection-Engine** is a state-of-the-art deep learning model designed to detect fire-related conditions in images. It leverages the **Vision Transformer (ViT)** architecture, specifically the `google/vit-base-patch16-224-in21k` model, fine-tuned on a dataset of fire and non-fire images. The model is trained to classify images into one of the following categories: "Fire Needed Action," "Normal Conditions," or "Smoky Environment," making it a powerful tool for detecting fire hazards.
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```
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Classification report:
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weighted avg 0.9799 0.9798 0.9797 2424
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# **Mappers**
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```python
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Mapping of IDs to Labels: {0: 'Fire Needed Action', 1: 'Normal Conditions', 2: 'Smoky Environment'}
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Mapping of Labels to IDs: {'Fire Needed Action': 0, 'Normal Conditions': 1, 'Smoky Environment': 2}
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```
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# **Key Features**
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- **Architecture**: Vision Transformer (ViT) - `google/vit-base-patch16-224-in21k`.
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- **Input**: RGB images resized to 224x224 pixels.
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- **Output**: Binary classification ("Fire Needed Action" or "Normal Conditions" or "Smoky Environment").
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- **Training Dataset**: A curated dataset of fire place conditions.
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- **Fine-Tuning**: The model is fine-tuned using Hugging Face's `Trainer` API with advanced data augmentation techniques.
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- **Performance**: Achieves high accuracy and F1 score on validation and test datasets.
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