| 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() |
