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463 lines
18 KiB
463 lines
18 KiB
from datetime import datetime
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import json
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import queue
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import time
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from time import sleep
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import cv2
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import numpy as np
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import logging
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import configSer
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import models.target
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import models.sampleMsg
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import upload.DataReporter
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import utils
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import videoPush
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from models.msg import Msg
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logging.basicConfig(level=logging.DEBUG)
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drawing: bool = False # 是否正在绘制
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is_video_mode: bool = False # 是否采用标靶图覆盖
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# 定义点
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start_point: models.target.Point
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end_point: models.target.Point
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# 配置
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configObj:configSer.ConfigOperate
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# 鼠标回调函数
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def add_rectangle(event, x, y, flags, param):
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global start_point, end_point, drawing
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if event == cv2.EVENT_LBUTTONDOWN: # 左键按下
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logging.info("左键按下")
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start_point = models.target.Point(x, y)
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end_point = start_point
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drawing = True
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elif event == cv2.EVENT_MOUSEMOVE: # 鼠标移动
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if drawing:
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end_point = models.target.Point(x, y)
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elif event == cv2.EVENT_LBUTTONUP: # 左键抬起
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logging.info("左键抬起")
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drawing = False
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end_point = models.target.Point(x, y)
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if start_point == end_point:
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return
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distance = cv2.norm(tuple(start_point), tuple(end_point), cv2.NORM_L2)
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if distance < 20:
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logging.info("距离小于20,无效区域")
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return
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target_id = len(configObj.config_info.targets)
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# 圆标靶半径 mm
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radius = 20.0
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area=models.target.RectangleArea(int(start_point.x),int(start_point.y),
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int(end_point.x-start_point.x),int(end_point.y-start_point.y))
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t_info=models.target.TargetInfo( target_id,
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"test add",
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area,
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radius,
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models.target.Threshold(190,9),
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False)
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new_target = models.target.CircleTarget(t_info,None,None)
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logging.info(f"新增区域[{target_id}] => {start_point, end_point}")
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configObj.config_info.targets[target_id] = new_target
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def read_target_rectangle():
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return configObj.config_info.targets
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class VideoProcessor:
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reporter: upload.DataReporter.DataReporter
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capture: cv2.VideoCapture
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is_opened: bool= False
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is_running = True
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def __init__(self, reporter:upload.DataReporter.DataReporter):
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self.reporter = reporter
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def on_data(self,msg:Msg):
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global configObj,is_video_mode
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logging.info(f"msg={msg}")
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match msg.cmd:
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case "getPoints":
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targets=configObj.config_info.targets.copy()
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for k,v in targets.items():
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targets[k].handler_info=None
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resp_msg = models.msg.Msg(_from="dev", cmd="getPoints", values={"targets": targets})
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resp_json = resp_msg.to_json_()
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return resp_json
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case "setPoints":
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v=msg.values
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ts=v["targets"]
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# 清空原配置
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configObj.config_info.targets={}
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for _,t in ts.items():
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t_str=json.dumps(t)
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new_c_target = models.target.CircleTarget.from_json(t_str)
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configObj.config_info.targets[new_c_target.info.id] =new_c_target
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configObj.save2json_file()
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resp_msg = models.msg.Msg(_from="dev", cmd="setPoints", values={"operate": True})
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resp_json = resp_msg.to_json()
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return resp_json
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case "videoFps":
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v = msg.values
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fps = v["fps"]
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self.reporter.adjust_rate(fps,"image")
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configObj.config_info.fps.video = fps
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configObj.save2json_file()
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resp_msg = models.msg.Msg(_from="dev", cmd="videoFps", values={"operate": True})
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resp_json = resp_msg.to_json()
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return resp_json
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case "dataFps":
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v = msg.values
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fps = v["fps"]
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self.reporter.adjust_rate(fps,"data")
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configObj.config_info.fps.data=fps
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configObj.save2json_file()
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resp_msg = models.msg.Msg(_from="dev", cmd="dataFps", values={"operate": True})
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resp_json = resp_msg.to_json()
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return resp_json
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case "setCap":
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v = msg.values
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cap = v["cap"]
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self.switch_video(cap)
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resp_msg = models.msg.Msg(_from="dev", cmd="setCap", values={"operate": True})
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resp_json = resp_msg.to_json()
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return resp_json
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case "videoMode":
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v = msg.values
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is_debug = v["debug"]
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is_video_mode=is_debug
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resp_msg = models.msg.Msg(_from="dev", cmd="videoMode", values={"operate": True})
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resp_json = resp_msg.to_json()
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return resp_json
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print("==")
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def pre_handler_img(self,gray_frame,now_str:str):
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# 将灰度图压缩为 JPEG 格式，并存储到内存缓冲区
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img_base64 = utils.frame_to_base64(gray_frame, format="JPEG")
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all_img = models.sampleMsg.AllImg(image=img_base64, time=now_str)
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self.enqueue_image(all_img)
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def draw_rectangle(self,img):
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global configObj,is_video_mode
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gray_frame = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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now_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]
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#图像发送
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if configObj.config_info.fps.video > 0:
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self.pre_handler_img(gray_frame,now_str)
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if len(configObj.config_info.targets)==0: return
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# 基点
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base_point_pix:models.target.Point=None
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#上报有新数据的点
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all_upload_data = models.sampleMsg.AllSensorData(data=[], time=now_str)
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# 绘图-历史点
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for i, tr in configObj.config_info.targets.items():
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if not hasattr(tr, "info"):
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print("====")
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_start_point = models.target.Point(tr.info.rectangle_area.x, tr.info.rectangle_area.y)
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_end_point = models.target.Point(
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tr.info.rectangle_area.x+tr.info.rectangle_area.w,
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tr.info.rectangle_area.y+tr.info.rectangle_area.h)
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#绘制标靶区域
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blue_color = (255, 0, 0)
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if tr.info.base:
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blue_color=(200, 0, 200) #紫红色 基点
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cv2.rectangle(img,tuple(_start_point), tuple(_end_point), blue_color, 2)
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label=f"{tr.info.desc},r={tr.info.radius}"
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cv2.putText(img, label, (_start_point.x,_start_point.y-6), cv2.FONT_HERSHEY_SIMPLEX, 0.6, blue_color,1)
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#检测
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# 获取图像尺寸
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frame_height, frame_width = gray_frame.shape[:2]
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if _end_point.x>frame_width or _end_point.y>frame_height:
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print(f"标靶[{tr.info.desc}]sub_image 超出区域")
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continue
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sub_image = self.extract_sub_image(gray_frame, _start_point, _end_point)
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ret, sub_binary_frame = cv2.threshold(sub_image, tr.info.threshold.binary, 255, cv2.THRESH_BINARY)
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# 高斯滤波
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gauss_size=tr.info.threshold.gauss
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sub_binary_frame = cv2.GaussianBlur(sub_binary_frame, (gauss_size, gauss_size), sigmaX=0,sigmaY=0,borderType=cv2.BORDER_REPLICATE)
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# sub_binary_frame = cv2.bilateralFilter(sub_binary_frame, 5, 50, 50)
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if tr.perspective is not None:
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# 宽度
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sub_width = sub_binary_frame.shape[1]
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# 高度
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sub_height = sub_binary_frame.shape[0]
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sub_binary_frame = cv2.warpPerspective(sub_binary_frame, tr.perspective, (sub_width, sub_height))
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# 覆盖原图
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if is_video_mode:
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sub_c_img= cv2.cvtColor(sub_binary_frame, cv2.COLOR_GRAY2BGR)
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self.cover_sub_image(img,sub_c_img, _start_point, _end_point)
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if __debug__:
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cv2.imshow(f'{tr.info.id}_binaryImg', sub_binary_frame)
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circles = self.circle2_detect(sub_binary_frame)
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if len(circles) == 0:
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continue
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center,radius_pix=self.circle_match(circles,_start_point)
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# 纪录圆心位置
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if tr.handler_info is None:
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tr.handler_info= models.target.HandlerInfo()
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if tr.handler_info.is_init:
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tr.handler_info.is_init=False
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tr.handler_info.center_init = center
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# 数据平滑处理
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smooth_center = tr.handler_info.enqueue_center_point(center)
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# print(f"{tr.info.desc},平滑len={len(tr.handler_info.center_point_queue)},平滑中心点={smooth_center},原始点={center}")
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tr.handler_info.center_point=smooth_center
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# 原始处理 tr.handler_info.center_point=center
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tr.handler_info.radius_pix=radius_pix
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tr.circle_displacement_pix()
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# 基点
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if tr.info.base:
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base_point_pix=tr.handler_info.displacement_pix
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# 画圆
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self.circle_show(img,smooth_center,radius_pix,_start_point,_end_point)
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# 基于像素点计算 物理距离
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for i, tr in configObj.config_info.targets.items():
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if tr.handler_info is None:
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continue
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if tr.handler_info.displacement_pix is None:
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continue
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# 减去基点偏移
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if base_point_pix is not None:
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raw_point=tr.handler_info.displacement_pix
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tr.handler_info.displacement_pix=models.target.Point(
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x=raw_point.x-base_point_pix.x,
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y=raw_point.y-base_point_pix.y)
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if not tr.info.base:
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# print(f"[{tr.info.id}]{tr.info.desc} 原偏 {raw_point} - 基偏{base_point_pix} ={tr.handler_info.displacement_pix}")
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pass
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tr.circle_displacement_phy()
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if tr.handler_info.displacement_phy is not None:
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all_upload_data.data.append(
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models.sampleMsg.SensorData(
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str(tr.info.id),
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tr.handler_info.displacement_phy.x,
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tr.handler_info.displacement_phy.y)
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)
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tr.handler_info.displacement_pix=None
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tr.handler_info.displacement_phy = None
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#过滤无效空数据
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if len(all_upload_data.data)==0:
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return
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if configObj.config_info.fps.data > 0:
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self.enqueue_data(all_upload_data)
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def circle_match(self,circles, rect_s_point:models.target.Point)-> (models.target.Point,float):
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circle = max(circles, key=lambda c: c[2])
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# 绘制圆心
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center = (circle[0] + rect_s_point.x, circle[1] + rect_s_point.y)
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radius = float(np.round(circle[2], 3))
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cp = models.target.Point(x=center[0], y=center[1])
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return cp,radius
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def circle_show(self, img, center: models.target.Point,radius:float, rect_s_point: models.target.Point,rect_e_point: models.target.Point):
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font = cv2.FONT_HERSHEY_SIMPLEX
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color = (255, 0, 0) # 蓝色
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scale = 0.5
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center_int = tuple(int(x) for x in center)
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radius_int = int(radius)
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cv2.circle(img, center_int, 2, (0, 255, 0), 4)
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# 绘制外圆
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cv2.circle(img, center_int, radius_int, (0, 0, 255), 1)
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# 打印圆心坐标
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text1 = f"c:{(center.x,center.y,radius)}"
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txt_location = (rect_s_point.x+2,rect_e_point.y-2)
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# txt_location = (center_int[0] - radius_int, center_int[1] + radius_int + 10)
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cv2.putText(img, text1, txt_location, font, scale, color, 1)
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def circle2_detect(self,img):
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# 圆心距 canny阈值 最小半径 最大半径
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circles_float = cv2.HoughCircles(img, cv2.HOUGH_GRADIENT_ALT, 1, 30, param1=200, param2=0.8, minRadius=15,
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maxRadius=0)
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# 创建一个0行, 2列的空数组
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if circles_float is not None:
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# 提取圆心坐标（保留2位小数）
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centers = [(round(float(x),2), round(float(y),2), round(float(r),2)) for x, y, r in circles_float[0, :]]
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return centers
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else:
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return []
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def extract_sub_image(self,frame, top_left, bottom_right):
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"""
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从帧中截取子区域
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:param frame: 输入的视频帧
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:param top_left: 子图片的左上角坐标 (x1, y1)
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:param bottom_right: 子图片的右下角坐标 (x2, y2)
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:return: 截取的子图片
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"""
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x1, y1 = top_left
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x2, y2 = bottom_right
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return frame[y1:y2, x1:x2]
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def cover_sub_image(self,frame,sub_frame, top_left, bottom_right):
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x1, y1 = top_left
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x2, y2 = bottom_right
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frame[y1:y2, x1:x2]= sub_frame
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return frame
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def open_video(self,video_id):
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sleep(1)
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print(f"打开摄像头 -> {video_id}")
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self.capture = cv2.VideoCapture(video_id)
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frame_width = int(self.capture.get(cv2.CAP_PROP_FRAME_WIDTH))
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frame_height = int(self.capture.get(cv2.CAP_PROP_FRAME_HEIGHT))
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print(f"默认分辨率= {frame_width}*{frame_height}")
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logging.info(f"{video_id}地址->{self.capture}")
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if not self.capture.isOpened():
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self.capture.release()
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logging.info(f"无法打开摄像头{video_id}, release地址 -> {self.capture}")
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return
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fps = self.capture.get(cv2.CAP_PROP_FPS)
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print(f"fps={fps},video_id={video_id},")
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# self.capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1600) # 宽度
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# self.capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 900) # 高度
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self.is_opened=True
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def switch_video(self,video_id:str):
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print(f"切换摄像头 -> {video_id}")
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self.is_opened = False
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self.capture.release()
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cv2.destroyAllWindows()
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if str.isdigit(video_id):
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video_id=int(video_id)
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self.open_video(video_id)
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def show_video(self):
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global sigExit,start_point, end_point, drawing
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if __debug__:
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cv2.namedWindow('Frame')
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cv2.setMouseCallback('Frame', add_rectangle)
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# 读取一帧图像
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while self.is_running:
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if not self.is_opened:
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print(f"摄像头 标记is_opened={self.is_opened}")
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sleep(5)
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continue
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ret, frame = self.capture.read()
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if ret:
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self.frame_handle(frame)
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else:
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logging.info(f"无法读取帧，cap地址- >{self.capture}")
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sleep(1)
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# self.capture.release()
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# self.capture= cv2.VideoCapture(0) # 再次尝试
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cv2.waitKey(1)
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# 显示图像
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if frame is not None:
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if __debug__:
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cv2.imshow('Frame', frame)
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#缓存到推流
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videoPush.update_latest_frame(frame)
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print("退出VideoProcessor")
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def show_image(self,frame):
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global start_point, end_point, drawing
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if __debug__:
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cv2.namedWindow('Frame')
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cv2.setMouseCallback('Frame', add_rectangle)
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# 读取一帧图像
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while True:
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cp_img=frame.copy()
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self.frame_handle(cp_img)
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if cv2.waitKey(1) & 0xFF == ord('q'): # 按'q'退出循环
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break
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cv2.destroyAllWindows()
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def frame_handle(self,frame):
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# 绘图-历史点
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self.draw_rectangle(frame)
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# 绘图-实时
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if drawing:
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cv2.rectangle(frame, tuple(start_point), tuple(end_point), (0, 200, 200), 4)
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# print(f"鼠标位置 {start_point} -> {end_point}")
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def image_mode(self):
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img_raw=cv2.imread('images/trans/_4point.jpg')#images/target/rp80max3.jpg
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# img_raw = cv2.imread('images/trans/_4point.jpg') # images/target/rp80max3.jpg
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# img_raw = cv2.imread('images/target/rp80.jpg') # images/target/rp80max3.jpg
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self.show_image(img_raw)
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# 支持
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def video_mode(self,video_id:str):
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if str.isdigit(video_id):
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video_id=int(video_id)
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self.open_video(video_id)
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self.show_video()
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# 释放摄像头资源并关闭所有窗口
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print("退出 video")
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self.capture.release()
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cv2.destroyAllWindows()
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def rtsp_mode(self,rtsp_url:str):
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# rtsp_url ="rtsp://admin:123456abc@192.168.1.64:554"
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# rtsp_url ="rtsp://admin:123456abc@192.168.1.64:554/h264/ch1/main/av_stream"
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self.open_video(rtsp_url)
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fps = self.capture.get(cv2.CAP_PROP_FPS)
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print(f"rtsp fps={fps}")
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self.show_video()
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|
# 释放摄像头资源并关闭所有窗口
|
|
self.capture.release()
|
|
cv2.destroyAllWindows()
|
|
|
|
def enqueue_data(self,data):
|
|
# 获取当前时间戳
|
|
timestamp = time.time()
|
|
# 将时间戳转换为 datetime 对象
|
|
dt = datetime.fromtimestamp(timestamp).strftime("%Y%m%d%H%M%S%f")[:-3] # 毫秒部分是微秒的前三位
|
|
# 放入图片队列(自动丢弃最旧数据当队列满时)
|
|
try:
|
|
self.reporter.data_queue.put((dt, data), block=False)
|
|
except queue.Full:
|
|
# self.reporter.data_dropped += 1
|
|
pass
|
|
def enqueue_image(self,data):
|
|
# 获取当前时间戳
|
|
timestamp = time.time()
|
|
# 将时间戳转换为 datetime 对象
|
|
dt = datetime.fromtimestamp(timestamp).strftime("%Y%m%d%H%M%S%f")[:-3] # 毫秒部分是微秒的前三位
|
|
# 放入图片队列(自动丢弃最旧数据当队列满时)
|
|
try:
|
|
self.reporter.image_queue.put((dt, data), block=False)
|
|
except queue.Full:
|
|
pass
|
|
#self.reporter.image_dropped += 1
|
|
|
|
def stop(self):
|
|
self.is_running=False
|
|
self.capture.release()
|
|
|
|
|
|
|
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|