app.py

import re
import jaconv
import gradio as gr
from transformers import AutoTokenizer, AutoFeatureExtractor, VisionEncoderDecoderModel
from PIL import Image
import torch
import cv2
import os
os.system('pip install paddlepaddle')
os.system('pip install paddleocr')
from paddleocr import PaddleOCR, draw_ocr

tokenizer = AutoTokenizer.from_pretrained("kha-white/manga-ocr-base")

model = VisionEncoderDecoderModel.from_pretrained("kha-white/manga-ocr-base")

feature_extractor = AutoFeatureExtractor.from_pretrained("kha-white/manga-ocr-base")

examples = ["japan.jpg"]

def post_process(text):
  text = ''.join(text.split())
  text = text.replace('…', '...')
  text = re.sub('[・.]{2,}', lambda x: (x.end() - x.start()) * '.', text)
  text = jaconv.h2z(text, ascii=True, digit=True)
  return text

def manga_ocr(img):
  ocr = PaddleOCR(use_angle_cls=True, lang='japan',use_gpu=False)
  img_path = img.name
  result = ocr.ocr(img_path, cls=True)
  image = Image.open(img_path).convert('RGB')
  pixel_values = feature_extractor(img, return_tensors="pt").pixel_values
  output = model.generate(pixel_values)[0]
  text = tokenizer.decode(output, skip_special_tokens=True)
  text = post_process(text)
  return text

iface = gr.Interface(
    fn=manga_ocr,
    inputs=[gr.inputs.Image(label="Input", type="pil")],
    outputs="text",
    layout="horizontal",
    theme="huggingface",
    title="Manga OCR",
    description="Optical Character Recognization for Japanese Texts with focus on Mangas. The model is trained by kha-white with Github link: <a href=\"https://github.com/kha-white/manga-ocr\">manga-ocr</a> while the Space App is made by me.",
    allow_flagging='never',
    examples=examples,
    article = "Author: <a href=\"https://huggingface.co/gryan-galario\">Gryan Galario</a>",
)

iface.launch()