Create app.py

app.py

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+import gradio as gr
+
+from . import OffTopicDetector
+
+detector = OffTopicDetector("openai/clip-vit-base-patch32")
+
+def validate(item_id: str, threshold: float):
+    images, domain, probas, valid_probas, invalid_probas = detector.predict_item_probas(item_id)
+    valid_images = [x for i, x in enumerate(images) if valid_probas[i].squeeze() >= threshold]
+    invalid_images = [x for i, x in enumerate(images) if valid_probas[i].squeeze() < threshold]
+    return valid_images, invalid_images
+
+
+with gr.Blocks() as demo:
+    with gr.Tabs():
+        with gr.Tab("From Item ID"):
+            item_id = gr.Textbox(label="Item ID")
+            threshold = gr.Number(label="Threshold", value=0.5)
+            submit = gr.Button("Submit")
+            valid = gr.Gallery(label="Valid images").style(grid=[1, 2, 3], height="auto")
+            invalid = gr.Gallery(label="Invalid images").style(grid=[1, 2, 3], height="auto")
+            submit.click(inputs=[item_id, threshold], outputs=[valid, invalid], fn=validate)
+
+
+demo.launch()
+            
+