app.py

import os
from doctr.io import DocumentFile
from doctr.models import ocr_predictor, from_hub
import gradio as gr

os.environ['USE_TORCH'] = '1'
reco_model = from_hub('ayymen/crnn_mobilenet_v3_large_tifinagh')
predictor = ocr_predictor(reco_arch=reco_model, pretrained=True)

title = "Tifinagh OCR"
description = "Upload an image to get the OCR results!"

def ocr(img):
    img.save("out.jpg")
    doc = DocumentFile.from_images("out.jpg")
    output = predictor(doc)
    res = ""
    for obj in output.pages:
        for obj1 in obj.blocks:
            for obj2 in obj1.lines:
                for obj3 in obj2.words:
                    res=res + " " + obj3.value
            res = res + "\n"
        res = res + "\n\n"
    _output_name = "RESULT_OCR.txt"
    open(_output_name, 'w', encoding="utf-8").close() # clear file
    with open(_output_name, "w", encoding="utf-8", errors="ignore") as f:
        f.write(res)
        print("Writing into file")
    return res, _output_name

demo = gr.Interface(fn=ocr,
                    inputs=gr.Image(type="pil"),
                    outputs=[
                        gr.Textbox(lines=10, label="Full Text"),
                        gr.File(label="Download OCR Results")
                    ],
                    title=title,
                    description=description,
                    examples=[["Examples/1.jpg"],["Examples/2.jpg"],["Examples/3.png"]]
                    )

demo.launch(debug=True)