import base64
import json
import logging
import os
import sys
import time
import traceback
from glob import glob
import numpy as np
import cv2
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
sys.path.append(os.path.dirname(os.path.abspath(__file__)) + "/../")
import tensorflow as tf
from flask import Flask, request
from utils import np2bytes, request_post, bytes2np, get_anchors, get_classes, get_colors, base64_decode, rgba_to_rgb
from puzzle_detect.inference_yolo_puzzle import get_tiny_inference_model, detect

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
tf.compat.v1.disable_eager_execution()
sess = tf.compat.v1.Session(graph=tf.Graph())

package_dir = os.path.abspath(os.path.dirname(__file__))
model_path = package_dir + "/models/puzzle_yolo_loss_4.15.h5"
anchors = get_anchors(package_dir + "/yolo_data/my_anchors_puzzle.txt")
classes = get_classes(package_dir + "/yolo_data/my_classes_puzzle.txt")
colors = get_colors(len(classes))

# 接口配置
app = Flask(__name__)


@app.route('/pzd', methods=['POST'])
def pzd():
    start_time = time.time()
    logging.info("into pzd_interface pzd")
    try:
        # 接收网络数据
        if not request.form:
            logging.info("pzd no data!")
            return json.dumps({"data": "", "success": 0})
        data = request.form.get("data")
        logging.info("pzd_interface get data time" + str(time.time()-start_time))

        # 加载模型
        pzd_model = globals().get("global_pzd_model")
        if pzd_model is None:
            print("=========== init pzd model ===========")
            pzd_model = PzdModels().get_model()
            globals().update({"global_pzd_model": pzd_model})

        # 数据转换
        # print("base64_data", data)
        data = base64_decode(data)
        image_np = bytes2np(data, unchanged=True)

        # 处理透明通道
        rgba_flag = 0
        position_list = []
        if image_np.shape[2] == 4:
            # 将透明部分置为黑色，转为3通道输出
            rgba_flag = 1
            image_np, position_list = rgba_to_rgb(image_np, return_position=True)

        # 预测
        _, out_boxes, out_classes = detect(image_np, pzd_model, sess)

        if len(out_boxes) == 0 and rgba_flag and position_list:
            logging.info('pzd 直接输出透明位置1')
            out_boxes = [position_list[0]]
        if len(out_boxes) >= 1 and rgba_flag and len(position_list) == 1:
            logging.info('pzd 直接输出透明位置2')
            out_boxes = [position_list[0]]

        return json.dumps({"data": out_boxes, "success": 1})
    except:
        traceback.print_exc()
        return json.dumps({"data": "", "success": 0})
    finally:
        logging.info("pzd interface finish time " + str(time.time()-start_time))


class PzdModels:
    def __init__(self):
        # detect
        with sess.as_default():
            with sess.graph.as_default():
                self.model = get_tiny_inference_model(anchors, len(classes), weights_path=model_path)

    def get_model(self):
        return self.model


def get_puzzle_tip_location(image_base64):
    """
    获取提示拼图的位置高度

    :param image_base64:
    :return:
    """
    image_bytes = base64_decode(image_base64)
    image_np = bytes2np(image_bytes)

    # image_np = cv2.imread(r'C:\Users\Administrator\Desktop\test_capture\puzzle2.jpg')
    # print(image_np)
    # image_np = np.mean(image_np, axis=0)
    hs = np.where(image_np > 20)[0]
    h1 = hs[0]
    h2 = hs[-1]
    # cv2.line(image_np, (0, h1), (image_np.shape[1], h1), (0, 0, 255))
    # cv2.line(image_np, (0, h2), (image_np.shape[1], h2), (0, 0, 255))
    # print('hs', hs)
    # cv2.imshow('img', image_np)
    # cv2.waitKey(0)
    return [h1, h2]


def test_pzd_model(from_remote=1, read_base64_file=0):
    paths = glob('puzzle4.png')
    for file_path in paths:

        if not read_base64_file:
            img_np = cv2.imread(file_path)
            file_bytes = np2bytes(img_np)
            file_base64 = base64.b64encode(file_bytes)
        else:
            with open('base64.txt', 'r') as f:
                file_base64 = f.read()
            file_bytes = base64_decode(file_base64)
            img_np = bytes2np(file_bytes, unchanged=True)
            img_np = rgba_to_rgb(img_np)
            # cv2.imshow('img', img_np)
            # cv2.waitKey(0)

        if from_remote:
            _url = "http://192.168.2.103:17059/pzd"
        else:
            _url = "http://127.0.0.1:17059/pzd"
        file_json = {"data": file_base64}
        result = json.loads(request_post(_url, file_json))
        if result.get("success"):
            out_boxes = result.get("data")
            print("out_boxes", out_boxes)
            for box in out_boxes:
                cv2.rectangle(img_np, (box[0], box[1]), (box[2], box[3]), (0, 0, 255))
            cv2.imshow("img_np", img_np)
            cv2.waitKey(0)
        else:
            print("failed!")


if __name__ == "__main__":
    # app.run(host='127.0.0.1', port=17059, debug=False)

    test_pzd_model()

    # get_puzzle_tip_location(None)