Create README.md

README.md

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+---
+license: apache-2.0
+base_model:
+- prithivMLmods/Fire-Detection-Engine
+pipeline_tag: image-classification
+library_name: transformers
+tags:
+- Fire-Detection-engine
+- Precision-98
+---
+![ccccccccccccccccccccccccccc.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/WP5cejlMirz3t6o2_YzVQ.png)
+
+# **Fire-Detection-Engine**
+
+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.
+
+```python
+Classification report:
+
+                    precision    recall  f1-score   support
+
+Fire Needed Action     0.9708    0.9864    0.9785       808
+ Normal Conditions     0.9872    0.9530    0.9698       808
+ Smoky Environment     0.9818    1.0000    0.9908       808
+
+          accuracy                         0.9798      2424
+         macro avg     0.9799    0.9798    0.9797      2424
+      weighted avg     0.9799    0.9798    0.9797      2424
+```
+
+![download.png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/kDS5cVee2ZVOv92rY0lGw.png)
+
+
+# **Mappers**
+
+```python
+Mapping of IDs to Labels: {0: 'Fire Needed Action', 1: 'Normal Conditions', 2: 'Smoky Environment'} 
+
+Mapping of Labels to IDs: {'Fire Needed Action': 0, 'Normal Conditions': 1, 'Smoky Environment': 2}
+```
+
+# **Key Features**
+- **Architecture**: Vision Transformer (ViT) - `google/vit-base-patch16-224-in21k`.
+- **Input**: RGB images resized to 224x224 pixels.
+- **Output**: Binary classification ("Fire Needed Action" or "Normal Conditions" or "Smoky Environment").
+- **Training Dataset**: A curated dataset of fire place conditions.
+- **Fine-Tuning**: The model is fine-tuned using Hugging Face's `Trainer` API with advanced data augmentation techniques.
+- **Performance**: Achieves high accuracy and F1 score on validation and test datasets.