# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import sys
__dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__)
sys.path.append(os.path.abspath(os.path.join(__dir__, '..')))

from ppocr.utils.utility import initial_logger
logger = initial_logger()
import cv2
import numpy as np
import time
from PIL import Image
from ppocr.utils.utility import get_image_file_list
from tools.infer.utility import draw_ocr, draw_boxes

import requests
import json
import base64


def cv2_to_base64(image):
    return base64.b64encode(image).decode('utf8')


def draw_server_result(image_file, res):
    img = cv2.imread(image_file)
    image = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    if len(res) == 0:
        return np.array(image)
    keys = res[0].keys()
    if 'text_region' not in keys: # for ocr_rec, draw function is invalid 
        print("draw function is invalid for ocr_rec!")
        return None
    elif 'text' not in keys: # for ocr_det
        print("draw text boxes only!")
        boxes = []
        for dno in range(len(res)):
            boxes.append(res[dno]['text_region'])
        boxes = np.array(boxes)
        draw_img = draw_boxes(image, boxes)
        return draw_img
    else: # for ocr_system
        print("draw boxes and texts!")
        boxes = []
        texts = []
        scores = []
        for dno in range(len(res)):
            boxes.append(res[dno]['text_region'])
            texts.append(res[dno]['text'])
            scores.append(res[dno]['confidence'])
        boxes = np.array(boxes)
        scores = np.array(scores)
        draw_img = draw_ocr(image, boxes, texts, scores, draw_txt=True, drop_score=0.5)       
        return draw_img


def main(url, image_path):
    image_file_list = get_image_file_list(image_path)
    is_visualize = False
    headers = {"Content-type": "application/json"}
    cnt = 0
    total_time = 0
    for image_file in image_file_list:
        img = open(image_file, 'rb').read()
        if img is None:
            logger.info("error in loading image:{}".format(image_file))
            continue

        # 发送HTTP请求
        starttime = time.time()
        data = {'images':[cv2_to_base64(img)]}
        r = requests.post(url=url, headers=headers, data=json.dumps(data))
        elapse = time.time() - starttime
        total_time += elapse
        print("Predict time of %s: %.3fs" % (image_file, elapse))
        res = r.json()["results"][0]
        # print(res)

        if is_visualize:
            draw_img = draw_server_result(image_file, res)
            if draw_img is not None:
                draw_img_save = "./server_results/"
                if not os.path.exists(draw_img_save):
                    os.makedirs(draw_img_save)
                cv2.imwrite(
                    os.path.join(draw_img_save, os.path.basename(image_file)),
                    draw_img[:, :, ::-1])
                print("The visualized image saved in {}".format(
                    os.path.join(draw_img_save, os.path.basename(image_file))))
        cnt += 1
        if cnt % 100 == 0:
            print(cnt, "processed")
    print("avg time cost: ", float(total_time)/cnt)

if __name__  == '__main__':
    if len(sys.argv) != 3:
        print("Usage: %s server_url image_path" % sys.argv[0])
    else:
        server_url = sys.argv[1]
        image_path = sys.argv[2]
        main(server_url, image_path)