Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+import numpy as np
+import tensorflow as tf
+from huggingface_hub import from_pretrained_keras
+
+description = "Keras implementation for Video Vision Transformer to classify samples of medmnist"
+article = "Author:<a href=\"https://huggingface.co/pablorodriper\"> Pablo Rodríguez</a>; Based on the keras example by <a href=\"https://keras.io/examples/vision/vivit/\">Aritra Roy Gosthipaty and Ayush Thakur</a>"
+title = "Video Vision Transformer on medmnist"
+
+def infer(x):
+    return model.predict(tf.expand_dims(x, axis=0))[0]
+
+model = from_pretrained_keras("pablorodriper/vivit")
+
+iface = gr.Interface(
+    fn = infer,
+    inputs = "video",
+    outputs = "number",
+    description = description,
+    title = title,
+    article = article
+    )
+
+iface.launch()