| 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("keras-io/video-vision-transformer") | |
| iface = gr.Interface( | |
| fn = infer, | |
| inputs = "video", | |
| outputs = "number", | |
| description = description, | |
| title = title, | |
| article = article | |
| ) | |
| iface.launch() |