# see huggingface/BallonsTranslator/main.py
# see huggingface/project/flask_auto_selection.py



from modules.textdetector.ctd.inference import TextDetector as CTDModel
from modules.ocr.mit48px import Model48pxOCR

CTD_ONNX_PATH = 'data/models/comictextdetector.pt.onnx'
device = 'cpu'
detect_size = 1280

ctd_model = CTDModel(CTD_ONNX_PATH, detect_size=detect_size, device=device)


OCR48PXMODEL_PATH = 'data/models/ocr_ar_48px.ckpt'
ocr_model = Model48pxOCR(OCR48PXMODEL_PATH, device)


import json, os, sys, time, io
import os.path as osp

from PIL import Image
import PIL
import cv2
import numpy as np

is_debug = True

dic_cache = {}

from flask import Flask, request, jsonify

app = Flask(__name__)

import base64
import math, re, uuid

def save_json(filename, dics):
    with open(filename, 'w', encoding='utf-8') as fp:
        json.dump(dics, fp, indent=4, ensure_ascii=False)
        fp.close()

def load_json(filename):
    with open(filename, encoding='utf-8') as fp:
        js = json.load(fp)
        fp.close()
        return js

def jsonparse(s):
    return json.loads(s, strict=False)

def jsonstring(d):
    return json.dumps(d, ensure_ascii=False)

def show_img(image, target_width=400):
    # 获取原始图片的宽度和高度
    original_height, original_width = image.shape[:2]
    
    # 计算缩放比例和目标高度
    scale = target_width / original_width
    target_height = int(original_height * scale)
    
    # 等比例缩放图片
    resized_image = cv2.resize(image, (target_width, target_height), interpolation=cv2.INTER_AREA)
    cv2.imshow("green", resized_image)
    cv2.waitKey(0)
    return resized_image

# see utils\io_utils.py
def imread(imgpath, read_type=cv2.IMREAD_COLOR, max_retry_limit=5, retry_interval=0.1):
    if not osp.exists(imgpath):
        return None
    
    num_tries = 0
    while True:
        try:
            img = Image.open(imgpath)
            if read_type == cv2.IMREAD_GRAYSCALE:
                img = img.convert('L')
            img = np.array(img)
            if read_type != cv2.IMREAD_GRAYSCALE:
                if img.ndim == 3 and img.shape[-1] == 1:
                    img = img[..., :2]
                if img.ndim == 2:
                    img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)

            if img.ndim == 3 and img.shape[-1] == 4:
                if np.all(img[..., -1] == 255):
                    img = np.ascontiguousarray(img[..., :3])
            break
        except PIL.UnidentifiedImageError as e:
            # IMG I/O thread might not finished yet
            num_tries += 1
            if max_retry_limit is not None and num_tries >= max_retry_limit:
                return None
            time.sleep(retry_interval)
    
    return img

def chunks(lst, n):
    """Yield successive n-sized chunks from lst."""
    for i in range(0, len(lst), n):
        yield lst[i:i + n]

def ocr(img):

    # All text detectors only support 3 channels input 
    if img.ndim == 3 and img.shape[2] == 4:
        img = cv2.cvtColor(img, cv2.COLOR_RGBA2RGB)

    _, mask, blk_list = ctd_model(img)

    fnt_rsz = 1.0
    fnt_max = -1
    fnt_min = -1
    for blk in blk_list:
        sz = blk._detected_font_size * fnt_rsz
        if fnt_max > 0:
            sz = min(fnt_max, sz)
        if fnt_min > 0:
            sz = max(fnt_min, sz)
        blk.font_size = sz
        blk._detected_font_size = sz

    ksize = 2
    if ksize > 0:
        element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2 * ksize + 1, 2 * ksize + 1),(ksize, ksize)) # 创建一个椭圆形的结构元素（kernel），用于后续的形态学操作  # 元素的尺寸 # (ksize, ksize) ：椭圆的锚点（中心点）
        mask = cv2.dilate(mask, element) # 对 mask 图像进行膨胀操作（dilate），使用上面创建的椭圆结构元素。膨胀操作可以让白色区域（通常是前景或目标区域）变大，常用于去除小的黑洞、连接断开的区域等。

    for blk in blk_list:
        blk.det_model = 'ctd'

    need_save_mask = True
    detect_counter = 0

    detect_counter += 1

    for blk in blk_list:
        blk.text = []

    split_textblk = False
    seg_func = None

    model_text_height = 48
    model_maxwidth = 8100

    from utils.textblock import collect_textblock_regions

    chunk_size = 16

    regions, textblk_lst_indices = collect_textblock_regions(img, blk_list, model_text_height, model_maxwidth, split_textblk, seg_func)


    ocr_model(blk_list, regions, textblk_lst_indices, chunk_size=chunk_size)


    img_draw = img.copy()


    results = []

    # ui\mainwindow.py
    for blk in blk_list:
        texts = blk.text
        lines = blk.lines
        results.append( { "texts": texts, "lines":lines } )
        for line in blk.lines:
            img_draw = cv2.rectangle(img_draw, line[0], line[2], (0, 0, 255), 2) 

    jsn = { "width": img.shape[1], "height": img.shape[0], "prism_wordsInfo": [] }
    for result in results:
        texts, lines = ( result["texts"], result["lines"])
        word = ''.join(texts)
        pos = []
        charInfo = []
        
        min_x = 999
        min_y = 999
        max_x = -1
        max_y = -1

        for text, line in zip(texts, lines):
            lu = line[0]
            ru = line[1]
            rd = line[2]
            ld = line[3]

            minx = min(lu[0], ld[0])
            maxx = max(ru[0], rd[0])
            miny = min(lu[1], ru[1])
            maxy = max(rd[1], ld[1])

            if min_x > minx:
                min_x = minx
            if max_x < maxx:
                max_x = maxx

            if min_y > miny:
                min_y = miny
            if max_y < maxy:
                max_y = maxy

            for c in text:
                charInfo.append( {"word": c, "x":minx , "y":miny, "w":maxx - minx , "h":maxy - miny, "guid": str( uuid.uuid4() ), "isDeleted": 0 } )
                pass
            
        pos = [ { "x":min_x, "y":min_y }, { "x":max_x, "y":min_y }, { "x":max_x, "y":max_y }, { "x":min_x, "y":max_y } ]

        jsn["prism_wordsInfo"].append( { "word":word, "x":min_x, "y":min_y, "width":max_x - min_x, "height":max_y - min_y, "pos":pos, "charInfo":charInfo} )



#     {
#   "width": 1200,
#   "height": 1801,
#   "prism_wordsInfo": [
#     {
#       "word": "# 简易字",
#       "prob": 0.6273085474967957,
#       "x": 593,
#       "y": 54,
#       "width": 127,
#       "height": 25,
#       "pos": [
#         {
#           "x": 593,
#           "y": 54
#         },
#         {
#           "x": 720,
#           "y": 54
#         },
#         {
#           "x": 720,
#           "y": 79
#         },
#         {
#           "x": 593,
#           "y": 79
#         }
#       ],
#       "charInfo": [
#         {
#           "h": 25,
#           "w": 43,
#           "word": " ",
#           "x": 595,
#           "y": 54,
#           "guid": "164e9305-3e8e-4467-bd76-1c13ee9b6a53",
#           "isDeleted": 0
#         },
#         {
#           "h": 25,
#           "w": 36,
#           "word": "易",
#           "x": 638,
#           "y": 54,
#           "guid": "17319ab0-7dca-4492-b5b3-bfe1d3aee0be",
#           "isDeleted": 0
#         },
#         {
#           "h": 25,
#           "w": 46,
#           "word": "字",
#           "x": 674,
#           "y": 54,
#           "guid": "71cdd286-192e-4461-b89f-89b19548e62f",
#           "isDeleted": 0
#         }
#       ]
#     },


    return jsn, img_draw

@app.route('/comicocr', methods=['post'])
def comicocr():
    global dic_cache

    # request.json 只能够接受方法为POST、Body为raw，header 内容为 application/json类型的数据
    # print(request.json, type(request.json))


    img_b64_str = request.json['img']
    img_bytes = base64.b64decode(img_b64_str)
    
    imgData = np.frombuffer(img_bytes, dtype=np.uint8)
    img = cv2.imdecode(imgData, -1)

    # All text detectors only support 3 channels input 
    if img.ndim == 3 and img.shape[2] == 4:
        img = cv2.cvtColor(img, cv2.COLOR_RGBA2RGB)

    
    # cv2.imshow('test', img)
    # cv2.waitKey()

    jsn, img_draw = ocr(img)
    
    return jsonify(jsn)


def main():
    if is_debug:
        img = imread('E:/huggingface/BallonsTranslator/assets/kcc-0010.jpg')
        jsn, img_draw = ocr(img)

        cv2.imwrite("E:/xxxxxxxxxxxxxxxx.jpg", img_draw)

    else:
        app.run(host="0.0.0.0", port=2393, debug=True)
    
    return

    from modules.textdetector.ctd.inference import TextDetector as CTDModel
    from modules.ocr.mit48px import Model48pxOCR
   
    

    CTD_ONNX_PATH = 'data/models/comictextdetector.pt.onnx'
    device = 'cpu'
    detect_size = 1280

    ctd_model = CTDModel(CTD_ONNX_PATH, detect_size=detect_size, device=device)


    OCR48PXMODEL_PATH = 'data/models/ocr_ar_48px.ckpt'
    ocr_model = Model48pxOCR(OCR48PXMODEL_PATH, device)


    img = imread('E:/huggingface/BallonsTranslator/assets/kcc-0010.jpg')
    
    # All text detectors only support 3 channels input 
    if img.ndim == 3 and img.shape[2] == 4:
        img = cv2.cvtColor(img, cv2.COLOR_RGBA2RGB)

    _, mask, blk_list = ctd_model(img)

    fnt_rsz = 1.0
    fnt_max = -1
    fnt_min = -1
    for blk in blk_list:
        sz = blk._detected_font_size * fnt_rsz
        if fnt_max > 0:
            sz = min(fnt_max, sz)
        if fnt_min > 0:
            sz = max(fnt_min, sz)
        blk.font_size = sz
        blk._detected_font_size = sz

    ksize = 2
    if ksize > 0:
        element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2 * ksize + 1, 2 * ksize + 1),(ksize, ksize)) # 创建一个椭圆形的结构元素（kernel），用于后续的形态学操作  # 元素的尺寸 # (ksize, ksize) ：椭圆的锚点（中心点）
        mask = cv2.dilate(mask, element) # 对 mask 图像进行膨胀操作（dilate），使用上面创建的椭圆结构元素。膨胀操作可以让白色区域（通常是前景或目标区域）变大，常用于去除小的黑洞、连接断开的区域等。

    for blk in blk_list:
        blk.det_model = 'ctd'

    need_save_mask = True
    detect_counter = 0

    detect_counter += 1

    # self.ocr.run_ocr(img, blk_list)


    for blk in blk_list:
        blk.text = []

    split_textblk = False
    seg_func = None

    model_text_height = 48
    model_maxwidth = 8100

    from utils.textblock import collect_textblock_regions

    chunk_size = 16

    regions, textblk_lst_indices = collect_textblock_regions(img, blk_list, model_text_height, model_maxwidth, split_textblk, seg_func)


    ocr_model(blk_list, regions, textblk_lst_indices, chunk_size=chunk_size)


    img_draw = img.copy()


    # from qtpy.QtWidgets import QApplication
    # from qtpy.QtGui import QIcon, QFontDatabase, QGuiApplication, QFont, QFontMetrics

    # ui\mainwindow.py
    for blk in blk_list:
        text = blk.get_text()
        for line in blk.lines:
            img_draw = cv2.rectangle(img_draw, line[0], line[3], (0, 0, 255), 2)  # 在一行坚排文字的左边画一条红线
        
        # app_font = QFont('Microsoft YaHei UI')
        # fontMetrics = QFontMetrics(app_font)

        # rect = fontMetrics.boundingRect(text[0])
        # textWidth = rect.width()
        
        pass
        # blk.text = self.ocrSubWidget.sub_text(text)


    cv2.imwrite("E:/xxxxxxxxxxxxxxxx.jpg", img_draw)


    pass


if __name__ == '__main__':
    main()