Create app.py

app.py

@@ -0,0 +1,66 @@
+import gradio as gr
+from PIL import Image
+
+from model_human import predict_human_nsfw
+from model_anime import predict_anime_nsfw
+
+def nsfw_detector(image: Image.Image, model_type: str):
+    if image is None:
+        return "<div class='result-box'>Pls upload an img</div>"
+
+    if model_type == "Human":
+        label, confidence = predict_human_nsfw(image)
+    else:
+        label, confidence = predict_anime_nsfw(image)
+
+    result = (
+        f"<div class='result-box'>"
+        f"<strong>Model:</strong> {model_type}<br>"
+        f"<strong>Prediction:</strong> {label}<br>"
+        f"<strong>Confidence:</strong> {confidence:.2%}"
+        f"</div>"
+    )
+    return result
+
+custom_css = """
+.result-box {
+    background-color: oklch(0.718 0.202 349.761);
+    padding: 20px;
+    border-radius: 12px;
+    box-shadow: 0 0 15px oklch(0.718 0.202 349.761);
+    color: white;
+    font-size: 1.2rem;
+    text-align: center;
+    font-weight: bold;
+    width: 100%;
+}
+.gradio-container { max-width: 900px; margin: auto; }
+"""
+
+with gr.Blocks(css=custom_css) as demo:
+    gr.Markdown("## NSFW Detector (Human + Anime/Cartoon)")
+    gr.Markdown(
+        "Upload an image and select the appropriate model for detection. "
+        "No data is stored. This is a side project — results may not be fully accurate."
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            model_choice = gr.Radio(
+                ["Human", "Anime"],
+                label="Select Model Type",
+                value="Human"
+            )
+            image_input = gr.Image(type="pil", label="Upload Image")
+        with gr.Column(scale=1):
+            output_box = gr.HTML("<div class='result-box'>Awaiting input...</div>")
+
+    # Trigger detection when image is uploaded
+    image_input.change(
+        fn=nsfw_detector,
+        inputs=[image_input, model_choice],
+        outputs=output_box
+    )
+
+if __name__ == "__main__":
+    demo.launch()