app.py

import gradio as gr
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
import requests
from PIL import Image
import numpy as np
import cv2
processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
model = VisionEncoderDecoderModel.from_pretrained("aico/TrOCR-MNIST")


def process_image(image):

    #print(np.shape(image))
    #print(image)
    #rint(image.astype('uint8'))
    #cv2.imwrite("image.png",image.astype('uint8'),(28, 28))
    img = Image.fromarray(image.astype('uint8')).convert("RGB")
    #img = Image.open("image.png").convert("RGB")
    print(img)
    # prepare image
    pixel_values = processor(img, return_tensors="pt").pixel_values

    # generate (no beam search)
    generated_ids = model.generate(pixel_values)

    # decode
    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]

    return generated_text

title = "Interactive demo: Single Digits MNIST"
description = "Aico - University Utrecht"
iface = gr.Interface(fn=process_image, 
                     inputs="sketchpad", 
                     outputs="label",
                     title = title,
                     description = description)
iface.launch(debug=True)