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README.md

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+# Guns-100-11m
+
+## Model Overview
+
+**Architecture:** YOLOv11  
+**Training Epochs:** 100  
+**Batch Size:** 32  
+**Optimizer:** auto  
+**Learning Rate:** 0.0005  
+**Data Augmentation Level:** Moderate
+
+## Training Metrics
+
+- **[email protected]:** 0.85476
+
+## Class IDs
+
+| Class ID | Class Name |
+|----------|------------|
+| 0 | Gun |
+| 1 | Knife |
+
+
+## Datasets Used
+
+- gun-detection-xwosb_v8
+- gun-sqvhj_v1
+- people_with_guns_2-pvcnk_v9
+- police1_v1
+- soldier-wclp7_v1
+- test-e46au_v1
+- weapon-rl8c4_v3
+- weapondetection-fdzlo_v4
+- weapons-detection-x9fnq_v3
+- wepon_detection_v1
+
+## Class Image Counts
+
+| Class Name | Image Count |
+|------------|-------------|
+| Gun | 44219 |
+| Knife | 4038 |
+
+
+## Description
+
+This model was trained using the YOLOv11 architecture on a custom dataset. The training process involved 100 epochs with a batch size of 32. The optimizer used was **auto** with an initial learning rate of 0.0005. Data augmentation was set to the **Moderate** level to enhance model robustness.
+
+## Usage
+
+To use this model for inference, follow the instructions below:
+
+```python
+from ultralytics import YOLO
+
+# Load the trained model
+model = YOLO('best.pt')
+
+# Perform inference on an image
+results = model('path_to_image.jpg')
+
+# Display results
+results.show()