Add ImageRecognitionDemo App

app.py

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+import gradio as gr
+from transformers import AutoFeatureExtractor, AutoModelForImageClassification, AutoTokenizer, AutoModelForSequenceClassification
+from transformers import pipeline 
+
+image_model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch16-224")
+extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
+
+image_pipe = pipeline("image-classification", model=image_model, feature_extractor=extractor)
+
+# classify the image and returns the results 
+def classify_image(inp):
+  results = image_pipe(inp)
+  return {result["label"]: result["score"] for result in results}
+
+gr.Interface(fn=classify_image, 
+             inputs=gr.Image(type="pil"),
+             outputs=gr.Label(num_top_classes=5)).launch()