Update README.md

README.md

@@ -15,5 +15,89 @@ tags:
 - finance
 ---
 
-> [!Important]
-> Coming Soon ...
+
+# **Document-Type-Detection**
+
+> **Document-Type-Detection** is a multi-class image classification model based on `google/siglip2-base-patch16-224`, trained to detect and classify **types of documents** from scanned or photographed images. This model is helpful for **automated document sorting**, **OCR pipelines**, and **digital archiving systems**.
+
+---
+
+## **Label Classes**
+
+The model classifies images into the following document types:
+
+```
+0: Advertisement-Doc  
+1: Hand-Written-Doc  
+2: Invoice-Doc  
+3: Letter-Doc  
+4: News-Article-Doc  
+5: Resume-Doc
+```
+
+---
+
+## **Installation**
+
+```bash
+pip install transformers torch pillow gradio
+```
+
+---
+
+## **Example Inference Code**
+
+```python
+import gradio as gr
+from transformers import AutoImageProcessor, SiglipForImageClassification
+from PIL import Image
+import torch
+
+# Load model and processor
+model_name = "prithivMLmods/Document-Type-Detection"
+model = SiglipForImageClassification.from_pretrained(model_name)
+processor = AutoImageProcessor.from_pretrained(model_name)
+
+# ID to label mapping
+id2label = {
+    "0": "Advertisement-Doc",
+    "1": "Hand-Written-Doc",
+    "2": "Invoice-Doc",
+    "3": "Letter-Doc",
+    "4": "News-Article-Doc",
+    "5": "Resume-Doc"
+}
+
+def detect_doc_type(image):
+    image = Image.fromarray(image).convert("RGB")
+    inputs = processor(images=image, return_tensors="pt")
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+        probs = torch.nn.functional.softmax(logits, dim=1).squeeze().tolist()
+
+    prediction = {id2label[str(i)]: round(probs[i], 3) for i in range(len(probs))}
+    return prediction
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=detect_doc_type,
+    inputs=gr.Image(type="numpy"),
+    outputs=gr.Label(num_top_classes=6, label="Document Type"),
+    title="Document-Type-Detection",
+    description="Upload a document image to classify it as one of: Advertisement, Hand-Written, Invoice, Letter, News Article, or Resume."
+)
+
+if __name__ == "__main__":
+    iface.launch()
+```
+
+---
+
+## **Applications**
+
+* **Automated Document Sorting**
+* **Digital Libraries and Archives**
+* **OCR Preprocessing**
+* **Enterprise Document Management**