Update README.md

README.md

@@ -1,15 +1,25 @@
----
-license: mit
-pipeline_tag: image-segmentation
----
+---
+license: mit
+pipeline_tag: image-segmentation
+tags:
+- anomaly-detection
+- image-anomaly-detection
+- explainable-ai
+- vision-transformer
+- attention-mechanism
+- digital-forensics
+- image-forensics
+- weakly-supervised
+- localization
+---
 # VAAS: Vision-Attention Anomaly Scoring
 
 ## Model Summary
 
-VAAS (Vision-Attention Anomaly Scoring) is a dual-module vision framework for image anomaly detection and localisation.
-It combines global attention-based reasoning with patch-level self-consistency analysis to produce a continuous and interpretable anomaly score alongside spatial anomaly maps.
+VAAS (Vision-Attention Anomaly Scoring) is a dual-module vision framework for **image anomaly detection and localization**.
+It combines **global attention-based reasoning** with **patch-level self-consistency analysis** to produce a **continuous, interpretable anomaly score** alongside dense spatial anomaly maps.
 
-The model is designed to indicate **where anomalies occur** and **how strongly they deviate from expected visual consistency**, supporting explainable image analysis and integrity assessment.
+Rather than making binary decisions, VAAS estimates **where anomalies occur** and **how strongly they deviate from learned visual regularities**, enabling explainable image analysis and integrity assessment.
 
 Paper link: *to be added upon publication*
 ---
@@ -68,23 +78,34 @@ GPU usage is recommended for faster processing but is not required.
 
 ## Installation
 
-VAAS is distributed as a lightweight inference library.
-Users must install **PyTorch** separately to match their system (CPU or GPU).
+VAAS is distributed as a **lightweight inference library** and can be installed instantly.
 
-*This model was produced using `vaas==0.1.6`, but newer versions of VAAS
-may also be compatible for inference.*
+PyTorch is **only required when running inference or loading pretrained models**.  
+This allows users to inspect, install, and integrate VAAS without heavy dependencies.
 
-### 1. Install PyTorch
+*This model was produced using `vaas==0.1.6`, but newer versions of VAAS may also be compatible for inference.*
 
-Follow the official PyTorch installation guide for your platform:
-[https://pytorch.org/get-started/locally/](https://pytorch.org/get-started/locally/)
+---
 
-### 2. Install VAAS
+### 1. Install VAAS
 
 ```bash
 pip install vaas
 ```
----
+You can now safely run:
+```bash
+import vaas
+```
+
+### 2. Install PyTorch
+
+To run inference or load pretrained VAAS models, install PyTorch and torchvision for your system (CPU or GPU).
+Follow the official PyTorch installation guide for your platform:
+
+[https://pytorch.org/get-started/locally/](https://pytorch.org/get-started/locally/)
+
+VAAS will automatically detect PyTorch at runtime and raise a clear error if it is missing.
+
 
 ## Usage