import socket
import cv2
import numpy as np
import json
import struct
import time
import re
def getseeds(image, dislen=89.01):
    frame = image
    # 将图像从BGR转换为HSV
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    # 定义橘红色在HSV颜色空间中的范围
    # 色调(H)：橘红色大致在0-20之间
    # 饱和度(S)：通常较高的值表示更纯的颜色
    # 亮度(V)：根据具体需求调整，这里我们选择较低的阈值以包含较暗的部分
    lower_orange_red = np.array([0, 100, 80])
    upper_orange_red = np.array([50, 255, 255])

    # 创建掩码
    mask = cv2.inRange(hsv, lower_orange_red, upper_orange_red)

    # 找到符合条件的像素坐标
    orange_red_points = cv2.findNonZero(mask)

    frameshow = frame.copy()
    # 创建一个与原图大小相同的空白掩码
    mask = np.zeros_like(frame[:, :, 0])  # 单通道掩码

    if orange_red_points is not None:
        for point in orange_red_points:
            x, y = point[0]
            cv2.circle(frameshow, (x, y), 1, (0, 255, 0), -1)  # 使用绿色标记点
            cv2.circle(mask, (x, y), 1, 255, -1)  # 使用白色标记点

    # 查找轮廓
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    if contours:
        for max_contour in contours:
            # 计算最小边界矩形（旋转）
            rect = cv2.minAreaRect(max_contour)
            box = cv2.boxPoints(rect)
            box = np.int32(box)
            
            # 计算边界框的宽度和高度
            width = int(rect[1][0])
            height = int(rect[1][1])

            if dislen > 20 and rect[1][0] > 25 and rect[1][1] > 25:
                ww = rect[1][0] * 3.0 / dislen
                hh = rect[1][1] * 3.0 / dislen
                # 格式化输出保留两位有效数字
                ww_text = f"w=: {ww:.2f}"
                hh_text = f"h=: {hh:.2f}"

                # 计算中心点
                x = int(np.mean(box[:, 0]))
                y = int(np.mean(box[:, 1]))

                # 设置字体、缩放比例、颜色和厚度
                font = cv2.FONT_HERSHEY_SIMPLEX
                font_scale = 2
                color = (0, 0, 255)  # BGR颜色格式，这里是蓝色
                thickness = 2

                # 显示宽度信息
                cv2.putText(frameshow, ww_text, (x, y-10), font, font_scale, color, thickness)

                # 显示高度信息
                cv2.putText(frameshow, hh_text, (x, y - 40), font, font_scale, color, thickness)

                # 在原图上绘制边界框
                cv2.drawContours(frameshow, [box], 0, (0, 0, 255), 2)
    
    try:
        ww_text
        hh_text
    except NameError:
        ww_text = "w=: 0.00"
        hh_text = "h=: 0.00"

    return ww_text,hh_text,frameshow

def extract_number_from_string(value_str):
    """从字符串中提取数字部分"""
    try:
        # 如果已经是数字类型，直接返回
        if isinstance(value_str, (int, float)):
            return float(value_str)
        
        # 如果是字符串，使用正则表达式提取数字
        if isinstance(value_str, str):
            # 匹配数字（包括小数）
            match = re.search(r'\d+\.?\d*', value_str)
            if match:
                return float(match.group())
            else:
                print(f"无法从字符串 '{value_str}' 中提取数字")
                return 0.0
        
        # 其他情况返回0
        return 0.0
    except Exception as e:
        print(f"提取数字时出错: {e}")
        return 0.0

def receive_image(sock):
    """从socket接收图像数据"""
    try:
        # 首先接收图像数据长度
        raw_msglen = recvall(sock, 4)
        if not raw_msglen:
            return None
        msglen = struct.unpack('>I', raw_msglen)[0]
        print(f"准备接收图像，大小: {msglen} 字节")
        
        # 接收图像数据
        raw_data = recvall(sock, msglen)
        if not raw_data:
            return None
        
        # 将字节数组转换为numpy数组，然后解码为图像
        nparr = np.frombuffer(raw_data, np.uint8)
        img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
        return img
    except Exception as e:
        print(f"接收图像时发生错误: {e}")
        return None

def send_image(sock, img, width, height):
    """通过socket发送图像数据"""
    try:
        # 将图像编码为jpg格式
        _, encoded_img = cv2.imencode('.jpg', img, [cv2.IMWRITE_JPEG_QUALITY, 80])
        data = encoded_img.tobytes()
        
        width_float = extract_number_from_string(width)
        height_float = extract_number_from_string(height)

        # 发送数据长度
        sock.sendall(struct.pack('>I', len(data)))
         # 发送width
        sock.sendall(struct.pack('>f', float(width_float)))
        # 发送height
        sock.sendall(struct.pack('>f', float(height_float)))
        # 发送图像数据
        sock.sendall(data)
        
        return True
    except Exception as e:
        print(f"发送图像时发生错误: {e}")
        return False

def recvall(sock, n):
    """辅助函数，确保接收到n个字节的数据"""
    data = bytearray()
    while len(data) < n:
        packet = sock.recv(n - len(data))
        if not packet:
            return None
        data.extend(packet)
    return data

def main():
    server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    server_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
    
    # 绑定IP和端口
    HOST = '127.0.0.1'
    PORT = 8888 
    server_socket.bind((HOST, PORT))
    server_socket.listen(1)
    
    print(f"Python图像检测服务器启动，监听 {HOST}:{PORT}")
    
    while True:
        try:
            # 等待客户端连接
            client_socket, addr = server_socket.accept()
            print(f"客户端连接来自: {addr}")
            
            while True:
                # 接收图像
                image = receive_image(client_socket)
                if image is None:
                    print("客户端断开连接")
                    break
                
                print(f"接收到图像，大小: {image.shape}")
                
                # 进行图像检测处理
                dislen = 147.50  # 固定值，也可以根据需要调整
                width, height, processed_image = getseeds(image, dislen)
                
                # 发送处理结果
                if not send_image(client_socket, processed_image, width, height):
                    print("发送结果图像失败")
                    break
                    
                print("结果图像发送成功")
                
        except Exception as e:
            print(f"处理客户端连接时发生错误: {e}")
        finally:
            client_socket.close()

if __name__ == "__main__":
    main()