import pandas as pd
import PIL
from PIL import Image
from PIL import ImageDraw
import gradio as gr
import torch
import easyocr
#import cv2
import math
import numpy as np

torch.hub.download_url_to_file('https://i.pinimg.com/originals/45/d0/30/45d03054e15f4be731781eecba7458a4.jpg', 'korean.jpg')

def midpoint(x1, y1, x2, y2):
    x_mid = int((x1 + x2)/2)
    y_mid = int((y1 + y2)/2)
    return (x_mid, y_mid)

def draw_mask(img, bounds):
    draw = ImageDraw.Draw(img)
    
    for bound in bounds:
        p0, p1, p2, p3 = bound[0]
        draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
        
    return imag
    """
    for bound in bounds:
        p0, p1, p2, p3 = bound[0]
        
        x0,y0 = p0
        x1,y1 = p1
        x2,y2 = p2
        x3,y3 = p3
        
        x_mid0, y_mid0 = midpoint(x1, y1, x2, y2)
        x_mid1, y_mi1 = midpoint(x0, y0, x3, y3)
        thickness = int(math.sqrt( (x2 - x1)**2 + (y2 - y1)**2 ))
        
        mask = np.zeros(img.shape[:2], dtype="uint8")
        cv2.line(mask, (x_mid0, y_mid0), (x_mid1, y_mi1), 255, thickness)
        img = cv2.inpaint(img, mask, 7, cv2.INPAINT_NS)

        draw.polygon((*p0, *p1, *p2, *p3), fill=255) 
    
    #masking
       
    return img   
def remove_text(img,imgwmask):
    masked = cv2.bitwise_and(img, img, mask=imgwmask)
    return img
"""        
def inference(img, lang):
    if lang == "english":
        lang = ['en']
    elif lang == "chinese":
        lang = ['ch_sim']
    elif lang == "korean":
        lang = ['ko']
    else:
        lang = ['ja']
    reader = easyocr.Reader(lang)
    bounds = reader.readtext(img.name)
    im = PIL.Image.open(img.name)
    #mask = PIL.Image.new("L", im1.size, 0)
    #w, h = im.size 
    
    #draw_mask(im, bounds)
    #remove_text(im, mask, bounds)
    lang = ""
    im.save('result.jpg')
    #mask.save('mask.png')
    return ['result.jpg', pd.DataFrame(bounds). iloc[: , 1:2]]

title = 'EasyOCR'
description = 'Gradio demo for EasyOCR. EasyOCR demo supports 80+ languages.To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to load them. Read more at the links below.'
article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github Repo</a></p>"
css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
examples = [['korean.jpg',"korean"]]
choices = [
    "chinese",
    "english",
    "japanese",
    "korean"
]
gr.Interface(
    inference,
    [gr.inputs.Image(type='file', label='Input'),gr.inputs.Dropdown(choices, type="value", default="korean", label='language')],
    [gr.outputs.Image(type='file', label='Output'), gr.outputs.Dataframe()],
    title=title,
    description=description,
    article=article,
    examples=examples,
    css=css,
    enable_queue=True
    ).launch(debug=True)