Update README.md

README.md

@@ -16,6 +16,18 @@ tags:
 - Anime
 ---
 
+# **Mature-Content-Detection**
+
+> **Mature-Content-Detection** is an image classification vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for a single-label classification task. It is designed to classify images into various mature or neutral content categories using the **SiglipForImageClassification** architecture.
+
+The model categorizes images into five classes:
+
+- **Class 0:** Anime Picture  
+- **Class 1:** Hentai  
+- **Class 2:** Neutral  
+- **Class 3:** Pornography  
+- **Class 4:** Enticing or Sensual  
+
 ```py
 Classification Report:
                      precision    recall  f1-score   support
@@ -32,3 +44,70 @@ Enticing or Sensual     0.7699    0.8979    0.8290      5600
 ```
 
 ![download (2).png](https://cdn-uploads.huggingface.co/production/uploads/65bb837dbfb878f46c77de4c/ca-xwkO8_dmywConDiO7g.png)
+
+# **Run with Transformers 🤗**
+
+```python
+!pip install -q transformers torch pillow gradio
+```
+
+```python
+import gradio as gr
+from transformers import AutoImageProcessor
+from transformers import SiglipForImageClassification
+from transformers.image_utils import load_image
+from PIL import Image
+import torch
+
+# Load model and processor
+model_name = "prithivMLmods/Mature-Content-Detection"
+model = SiglipForImageClassification.from_pretrained(model_name)
+processor = AutoImageProcessor.from_pretrained(model_name)
+
+# Updated labels
+labels = {
+    "0": "Anime Picture",
+    "1": "Hentai",
+    "2": "Neutral",
+    "3": "Pornography",
+    "4": "Enticing or Sensual"
+}
+
+def mature_content_detection(image):
+    """Predicts the type of content in the 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()
+
+    predictions = {labels[str(i)]: round(probs[i], 3) for i in range(len(probs))}
+    
+    return predictions
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=mature_content_detection,
+    inputs=gr.Image(type="numpy"),
+    outputs=gr.Label(label="Prediction Scores"),
+    title="Mature Content Detection",
+    description="Upload an image to classify whether it contains anime, hentai, neutral, pornographic, or enticing/sensual content."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()
+```
+
+---
+
+# **Intended Use:**
+
+The **Mature-Content-Detection** model is designed to classify visual content for moderation and filtering purposes. Potential use cases include:
+
+- **Content Moderation:** Automatically flagging explicit or sensitive content on platforms.  
+- **Parental Control Systems:** Filtering inappropriate material for child-safe environments.  
+- **Search Engine Filtering:** Improving search results by categorizing Un-Safe content.  
+- **Dataset Cleaning:** Assisting in curation of safe training datasets for other AI models.