import datetime
import threading
import cv2
import numpy as np
import statistics
import math
from Post import post
from PIL import ImageDraw, ImageFont
from PIL import Image


def fall_detect(cnts, defined_min_area, frame, prevX, prevY, xList, yList, centerV, alert, pre):
    for c in cnts:
        # exclusion
        if cv2.contourArea(c) < defined_min_area:
            continue

        # outer bounding box
        (x_b, y_b, w_b, h_b) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x_b, y_b), (x_b + w_b, y_b + h_b), (0, 255, 255), 2)  # 黄色矩形

        # rotating bounding box
        rect = cv2.minAreaRect(c)  # 得到最小外接矩形的（中心(x,y), (宽,高), 旋转角度）
        box = cv2.boxPoints(rect)  # 获取最小外接矩形的4个顶点坐标
        box = np.int0(box)
        cv2.drawContours(frame, [box], 0, (0, 0, 255), 2)

        # averaging line
        rows, cols = frame.shape[:2]
        [vx, vy, x, y] = cv2.fitLine(c, cv2.DIST_L2, 0, 0.01, 0.01)
        lefty = (-x * vy / vx) + y
        righty = ((cols - x) * vy / vx) + y
        cv2.line(frame, (cols - 1, righty), (0, lefty), (255, 0, 0), 2)

        # ellipse
        elps = cv2.fitEllipse(c)
        (x, y), (MA, ma), angle = cv2.fitEllipse(c)
        cv2.ellipse(frame, elps, (255, 0, 0), 3)  # red

        # Aspect Ratio
        AR = MA / ma

        # Center Speed - acceleration
        prevX = 0.0
        prevY = 0.0
        centerSpeed = 0
        if xList.full():
            prevX = statistics.median(list(xList.queue))
            prevY = statistics.median(list(yList.queue))
            xList.get()
            yList.get()

        xList.put(elps[0][0])
        yList.put(elps[0][1])
        X = statistics.median(list(xList.queue))
        Y = statistics.median(list(yList.queue))

        if xList.full():
            dx = abs(prevX - X)
            dy = abs(prevY - Y)
            centerV = math.sqrt(dx ** 2 + dy ** 2)

        # calculate probabilities for the 4 features
        pAngle = (abs(angle - 90) - 50) / 10
        pAngle = 1 / (math.exp(pAngle) + 1)

        pAR = 10 * AR - 5
        pAR = 1 / (math.exp(pAR) + 1)

        ACS = centerV - 9
        try:
            ACS = 1 / (math.exp(ACS) + 1)
        except:
            ACS = 1 / (float('inf') + 1)
        # print("pAngle : ", pAngle)
        # print("pAR : ", pAR)
        # print("ACS : ", ACS)

        # confidence
        P_FALL = pAngle * pAR * ACS + 0.5
        # print("P_FALL1 : ", P_FALL)

        P_FALL = 1 / (math.exp(-(P_FALL - 0.65) * 10) + 1)
        # print("P_FALL2: ", P_FALL)

        # status display
        # cv2.putText(frame, "Status : ", (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 14)
        # cv2.putText(frame, "Fall Confidence: {0:.2f} ".format(P_FALL), (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
        #             (0, 128, 255), 14)
        # cv2.putText(frame, "Angle: {0:.2f}".format(angle), (10, 220),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 14)
        # cv2.putText(frame, "AR: {0:.2f}".format(AR), (10, 237),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 14)
        # cv2.putText(frame, "Center Speed: {0:.2f}".format(centerV), (10, 256),cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 0), 14)

        # fall
        if P_FALL > 0.88:
            if alert > 3:
                # print("fall")
                font = ImageFont.truetype("simsun.ttc", 30, index=1)
                img_rd = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
                draw = ImageDraw.Draw(img_rd)
                draw.text((10, 10), text="Fall Detected", font=font,
                          fill=(255, 0, 0))
                frame = cv2.cvtColor(np.array(img_rd), cv2.COLOR_RGB2BGR)
                time_snap = datetime.datetime.now()
                cv2.imwrite('fall_detection' + str(time_snap).replace(':', '') + '.jpg', frame)
                if (datetime.datetime.now() - pre).total_seconds() > 5:
                    t = threading.Thread(
                        target=post(event=3, imagePath='fall_detection' + str(time_snap).replace(':', '') + '.jpg'))
                    t.setDaemon(False)
                    t.start()
                    pre = datetime.datetime.now()
                # cv2.imwrite("report.jpg", frame)
                # send_alert.SendMail("report.jpg")
                alert = alert + 1
            else:
                alert = alert + 1

    return frame, alert, pre