Update app.py

app.py

@@ -42,7 +42,7 @@ def predict(image, model_type):
         pred_class = torch.argmax(probs, dim=1).item()
         confidence = probs[0][pred_class].item()
 
-    label = "NSFW" if pred_class == 1 else "SFW"
+    label = "NSFW" if pred_class == 0 else "SFW"
     return f"""
     <div class='result-box'>
         <strong>Model:</strong> {model_type}<br>
@@ -54,10 +54,10 @@ def predict(image, model_type):
 # Custom glow box CSS
 custom_css = """
 .result-box {
-    background-color: oklch(0.718 0.202 349.761);
+    background-color: black; /* dark inside */
     padding: 20px;
     border-radius: 12px;
-    box-shadow: 0 0 15px oklch(0.718 0.202 349.761);
+    box-shadow: 0 0 20px oklch(0.718 0.202 349.761); /* outer glow only */
     color: white;
     font-size: 1.2rem;
     text-align: center;
@@ -69,10 +69,9 @@ custom_css = """
 
 # Gradio UI
 with gr.Blocks(css=custom_css) as demo:
-    gr.Markdown("## NSFW Detector (Human + Anime/Cartoon)")
+    gr.Markdown("## NSFW Detector (Human and Anime/Cartoon)")
     gr.Markdown(
-        "Upload an image and select the appropriate model. The system will detect whether the content is NSFW or SFW. "
-        "This is a side project. Results are not guaranteed. No images are stored."
+        "Upload an img and select the appropriate model. The system will detect whether the content is NSFW or SFW. "
     )
 
     with gr.Row():
@@ -85,5 +84,18 @@ with gr.Blocks(css=custom_css) as demo:
     image_input.change(fn=predict, inputs=[image_input, model_choice], outputs=output_box)
     model_choice.change(fn=predict, inputs=[image_input, model_choice], outputs=output_box)
 
+gr.Markdown(
+        "<div class='disclaimer'>This is a side project. Results are not guaranteed. No images are stored.</div>"
+    )
+.disclaimer {
+    color: white;
+    font-size: 0.9rem;
+    text-align: center;
+    margin-top: 40px;
+    text-shadow: 0 0 10px oklch(0.718 0.202 349.761); /* soft outer glow */
+}
+
+
+
 if __name__ == "__main__":
     demo.launch()