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tags:
  - image-classification
  - transfer-learning
  - keras
  - tensorflow
  - security
library_name: tensorflow

Fine-Tuned Weapon vs. Not-Weapon Classifier (VGG16)

This repository contains a fine-tuned image classification model designed to distinguish between "Weapon" and "Not-Weapon" classes in images. The model was built using Transfer Learning on the VGG16 architecture.

Model Structure and Training

  • Base Architecture: VGG16 (pre-trained on ImageNet).
  • Training Method: Transfer Learning (Feature Extraction) followed by Fine-Tuning.
  • File: weapon_classifier_final_tuned.keras (This is the final, fine-tuned model file).
  • Input Size: Images must be resized to (224, 224) pixels before prediction.
  • Output Activation: Sigmoid (yielding a single probability value between 0 and 1).

How to Use the Model (Inference)

To use this model, you need a Python environment with TensorFlow installed.

1. Installation

First, ensure you have the required libraries:

pip install tensorflow numpy Pillow