app.py

import cv2
import gradio as gr
import tensorflow as tf

title = "Welcome on your first sketch recognition app!"


head = (
  "<center>"
  "<img src='file/mnist-classes.png' width=400>"
  "The robot was trained to classify numbers (from 0 to 9). To test it, write your number in the space provided."
  "</center>"
)

ref = "Find the whole code [here](https://github.com/ovh/ai-training-examples/tree/main/apps/gradio/sketch-recognition)."

img_size = 28
labels = ["zero", "one", "two", "three", "four", "five", "six", "seven", "eight", "nine"]

model = tf.keras.models.load_model("number_recognition_model_colab.keras")


def predict(img):

  img = cv2.resize(img, (img_size, img_size))
  img = img.reshape(1, img_size, img_size, 1)

  preds = model.predict(img)[0]

  return {label: float(pred) for label, pred in zip(labels, preds)}

label = gr.outputs.Label(num_top_classes=3)



interface = gr.Interface(fn=predict, inputs="sketchpad", outputs=label, title=title, description=head, article=ref)
interface.launch()