Create app.py

app.py

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+import requests
+import gradio as gr
+from transformers import pipeline
+
+# make the image classification pipeline
+def classify_image(test_sample):
+    img_class= pipeline(
+        "image-classification", model="AMfeta99/vit-base-oxford-brain-tumor"
+    )
+    results = img_class(our_dataset['test']['image'][0])
+    max_score_result = max(results, key=lambda x: x['score'])
+
+    predictions = max_score_result['label']
+    
+    return predictions
+
+
+
+image = gr.Image()
+label = gr.Label(num_top_classes=1)
+title = "Brain Tumor X-ray Classification"
+description="Worried about whether your brain scan is normal or not? Upload your x-ray and the algorithm will give you an expert opinion.  Check out [the original algorithm](https://huggingface.co/AMfeta99/vit-base-oxford-brain-tumor) that this demo is based off of."
+article="<p style='text-align: center'>Image Classification | Demo Model</p>"
+demo = gr.Interface(fn=classify_image, inputs=image , outputs=label, description=description,article=article,title=title)
+
+demo.launch(share=True)