Create app.py

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+from transformers import pipeline
+
+pipe = pipeline(
+  "automatic-speech-recognition",
+  model="openai/whisper-small",
+  chunk_length_s=30,
+  device=device,
+)
+
+def predict(input_img):
+    predictions = pipeline(input_img)
+    return input_img, {p["label"]: p["score"] for p in predictions} 
+
+gradio_app = gr.Interface(
+    predict,
+    inputs=gr.Image(label="Select hot dog candidate", sources=['upload', 'webcam'], type="pil"),
+    outputs=[gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
+    title="Hot Dog? Or Not?",
+)
+
+if __name__ == "__main__":
+    gradio_app.launch()