Add demo files

.gitignore

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+
+.vscode/

app.py

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+import gradio as gr
+from transformers import pipeline
+
+pipe = pipeline("image-classification", "trpakov/vit-pneumonia")
+
+
+def classify_image(image):
+    outputs = pipe(image)
+    outputs = {
+        x["label"]: x["score"] for x in sorted(outputs, key=lambda x: x["label"])
+    }
+    return outputs
+
+
+with gr.Blocks(
+    title="ViT Chest X-ray Classification",
+) as demo:
+    gr.Markdown("# ViT Chest X-ray Pneumonia Classification")
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown(
+                "Classify chest x-ray scans as either having or not having pneumonia"
+            )
+            input_image = gr.Image(type="pil")
+            classify_button = gr.Button("Classify!")
+        with gr.Column():
+            output_label = gr.Label(label="Probabilities", num_top_classes=2)
+
+    with gr.Row():
+        gr.Examples(
+            "./samples",
+            inputs=input_image,
+            outputs=output_label,
+            cache_examples=True,
+            fn=classify_image,
+            run_on_click=True,
+        )
+
+    classify_button.click(fn=classify_image, inputs=input_image, outputs=output_label)
+
+
+demo.launch(debug=True, enable_queue=True)