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@ -1,19 +0,0 @@ |
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import json |
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import typing |
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from dataclasses import dataclass |
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from dataclasses_json import dataclass_json |
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@dataclass_json |
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@dataclass |
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class Msg: |
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_from: str |
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cmd: str |
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values: typing.Any |
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def to_json_(self) -> str: |
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"""将数据类序列化为 JSON 字符串""" |
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return self.to_json() |
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@ -1,43 +0,0 @@ |
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import json |
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from dataclasses import dataclass |
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from typing import List |
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@dataclass |
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class SensorImg: |
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base64: str |
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def to_json(self) -> str: |
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"""将数据类序列化为 JSON 字符串""" |
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return json.dumps(self.__dict__, indent=4, default=lambda x: x.__dict__) |
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@classmethod |
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def from_json(cls, json_str: str) -> 'SensorImg': |
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"""从 JSON 字符串反序列化为数据类""" |
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data_dict = json.loads(json_str) |
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return cls(**data_dict) |
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@dataclass |
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class SensorData: |
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pos: str |
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x: float |
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y: float |
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def to_json(self) -> str: |
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"""将数据类序列化为 JSON 字符串""" |
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return json.dumps(self.__dict__, indent=4, default=lambda x: x.__dict__) |
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@classmethod |
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def from_json(cls, json_str: str) -> 'SensorData': |
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"""从 JSON 字符串反序列化为数据类""" |
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data_dict = json.loads(json_str) |
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return cls(**data_dict) |
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@dataclass |
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class AllSensorData: |
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data: List[SensorData] |
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time: str |
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@dataclass |
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class AllImg: |
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image: SensorImg |
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time: str |
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@ -1,112 +0,0 @@ |
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from dataclasses import dataclass, field |
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from typing import Optional, Dict |
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import numpy as np |
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from dataclasses_json import dataclass_json, config |
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import utils |
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@dataclass_json |
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@dataclass |
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class Point: |
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x:float |
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y:float |
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def __iter__(self): # 使对象可迭代，可直接转为元组 |
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yield self.x |
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yield self.y |
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@dataclass |
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class RectangleArea: |
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x: int |
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y: int |
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w: int |
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h: int |
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@classmethod |
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def from_dict(cls, data: dict): |
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return cls( |
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x=data['x'], |
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y=data['y'], |
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w=data['w'], |
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h = data['h']) |
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@dataclass |
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class Threshold: |
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binary: int |
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gauss: int |
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@dataclass_json |
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@dataclass |
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class TargetInfo: |
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# 标靶方形区域 |
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rectangle_area:RectangleArea |
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threshold:Threshold |
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# 标靶物理半径 |
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radius:float=0.0 |
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id:int =-1 |
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desc:str="" |
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base:bool=False |
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def __init__(self,id,desc,rectangle_area:RectangleArea,radius,threshold:Threshold,base:bool,**kwargs): |
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self.id = id |
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self.desc = desc |
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self.rectangle_area=rectangle_area |
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self.radius=radius |
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self.threshold=threshold |
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self.base=base |
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@classmethod |
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def from_dict(cls,data: dict): |
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return cls(data['id'],data['rectangle_area'],data['radius']) |
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@dataclass_json |
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@dataclass |
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class HandlerInfo: |
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# 初始话 |
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is_init=True |
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radius_pix:float= 1.0 |
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pix_length:float=0.0 |
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# 标靶中心 |
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center_point: Optional[Point]= field(default=None, metadata=config(exclude=lambda x: x is None)) |
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center_init : Optional[Point]= field(default=None, metadata=config(exclude=lambda x: x is None)) |
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# 标靶位移(像素) |
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displacement_pix: Optional[Point]= field(default=None, metadata=config(exclude=lambda x: x is None)) |
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displacement_phy: Optional[Point]= field(default=None, metadata=config(exclude=lambda x: x is None)) |
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@dataclass_json |
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@dataclass |
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class CircleTarget: |
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# 标靶方形区域 |
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info:TargetInfo |
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# 标靶透视矩阵 |
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perspective: np.ndarray = field( |
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metadata=config( |
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encoder=utils.encode_perspective, |
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decoder=utils.decode_perspective |
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) |
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) |
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handler_info: Optional[HandlerInfo]=None |
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# def __init__(self,info:TargetInfo,center_point,center_init,displacement_pix,displacement_phy): |
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# self.info=info |
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# self.center_point=center_point |
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# self.center_init=center_init |
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# self. displacement_pix=displacement_pix |
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# self.displacement_phy=displacement_phy |
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@classmethod |
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def init_by_info(cls,t:TargetInfo): |
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return CircleTarget(t,None,None,None,None) |
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def circle_displacement(self): |
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previous = self.handler_info.center_init |
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if previous != (): |
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self.handler_info.displacement_pix = Point(self.handler_info.center_point.x - previous.x, |
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self.handler_info.center_point.y - previous.y) |
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if self.info.radius != 0: |
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# 单位像素距离 |
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self.handler_info.pix_length = self.info.radius / self.handler_info.radius_pix |
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offset_x = round(float(self.handler_info.displacement_pix.x * self.handler_info.pix_length), 5) |
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offset_y = round(float(self.handler_info.displacement_pix.y * self.handler_info.pix_length), 5) |
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self.handler_info.displacement_phy = Point(offset_x, offset_y) |
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return self |
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@ -1,18 +0,0 @@ |
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import signal |
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import sys |
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from dataclasses import dataclass, asdict |
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from datetime import datetime |
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def signal_handler(sig, frame): |
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print(f"收到退出信号 sig={sig}，程序退出") |
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sys.exit(0) |
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signal.signal(signal.SIGINT, signal_handler) # 捕获 Ctrl+C 信号 |
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if __name__ == '__main__': |
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t=datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3] |
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print(t) |
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while True: |
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# 程序主循环 |
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pass |
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@ -1,29 +0,0 @@ |
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import json |
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from dataclasses import asdict |
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import configSer |
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def test_load_config(): |
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config_path = "../config.json" |
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# 读取配置文件 |
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config: configSer.ConfigOperate = configSer.ConfigOperate(config_path) |
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json_str2 = config.config_info.to_json(indent=4) |
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print("json=",json_str2) |
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# 测试修改相机id |
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config.config_info.capture=1 |
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config.save2json_file() |
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# 更新配置文件 |
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updates = { |
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"capture": "rtsp://admin:123456abc@192.168.1.64:554/h264/ch1/main/av_stream", |
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} |
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config.update_dict_config(updates) |
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# 重新读取配置文件，确认更新 |
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updated_config = configSer.ConfigOperate(config_path) |
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print(f"当前新配置capture:{updated_config.capture}") |
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if __name__ == "__main__": |
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test_load_config() |
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import logging |
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from time import sleep |
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import cv2 |
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print(cv2.__version__) |
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def open_video(video_id): |
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cap = cv2.VideoCapture(video_id) |
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if not cap.isOpened(): |
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logging.info("无法打开摄像头") |
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return cap |
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class VideoProcessor: |
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capture: cv2.VideoCapture |
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rtsp_url ="rtsp://admin:123456abc@192.168.1.64:554/h264/ch1/main/av_stream" |
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print("开始读取2") |
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capture=open_video(2) |
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vp = VideoProcessor() |
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vp.capture = capture |
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fps = vp.capture .get(cv2.CAP_PROP_FPS) |
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width = int(vp.capture .get(cv2.CAP_PROP_FRAME_WIDTH)) |
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height = int(vp.capture .get(cv2.CAP_PROP_FRAME_HEIGHT)) |
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print(f"fps={fps}") |
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print("width={width}, height={height}".format(width=width, height=height)) |
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cv2.namedWindow('frame') |
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i = 0 |
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while True: |
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ret, frame = vp.capture .read() |
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if ret: |
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print("-->") |
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cv2.imshow("frame", frame) |
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i=i+1 |
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if i>10: |
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break |
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# 写入帧到输出文件 |
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# out.write(frame) |
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else: |
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logging.info("无法读取图像帧") |
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break |
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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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print("释放2") |
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vp.capture.release() |
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cv2.destroyAllWindows() |
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print("开始读取0") |
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sleep(2) |
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vp.capture = open_video(0) |
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# # 定义视频编 = open_video(0)码器和输出文件 |
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# fourcc = cv2.VideoWriter_fourcc(*'mp4v') |
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# out = cv2.VideoWriter('output.mp4', fourcc, fps, (width, height)) |
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while True: |
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ret, frame = vp.capture .read() |
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if ret: |
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cv2.imshow("frame", frame) |
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# 写入帧到输出文件 |
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# out.write(frame) |
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else: |
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logging.info("无法读取图像帧") |
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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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vp.capture.release() |
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# out.release() |
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@ -1,32 +0,0 @@ |
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from dataclasses import dataclass, field |
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from typing import Optional |
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from dataclasses_json import dataclass_json, config |
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import json |
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import models.target |
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@dataclass_json |
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@dataclass |
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class Rectangle: |
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x: int |
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y: int |
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width: int |
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height: int |
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p: Optional[models.target.Point]= field(default=None, metadata=config(exclude=lambda x: x is None)) |
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# 使用 |
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p=models.target.Point(1,2) |
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rect = Rectangle(0, 0, 100, 100,None) |
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# 序列化 |
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json_str=rect.to_json() |
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# json_str = json.dumps(rect, default=lambda obj: obj.__dict__) |
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print(f"序列化后={json_str}") |
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rect.p.x=2046 |
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print("修改后p.x=",p.x) |
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new_json='{"x": 1, "y": 1, "width": 100, "height": 100, "p": {"x": 2, "y": 2}}' |
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nr=Rectangle.from_json(new_json) |
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print(nr.p) |
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@ -1,73 +0,0 @@ |
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import queue |
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import threading |
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import time |
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import models.msg |
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from upload.RateLimiter import RateLimiter |
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class DataReporter(threading.Thread): |
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call_back=None |
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def __init__(self,data_fps:int,video_fps:int): |
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super().__init__() |
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self.image_queue = queue.Queue(maxsize=video_fps) # 图片队列 |
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self.data_queue = queue.Queue(maxsize=data_fps) # 数据队列 |
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self.image_limiter = RateLimiter(max_rate=video_fps, time_window=1) # 图片限速: 5张/秒 |
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self.data_limiter = RateLimiter(max_rate=data_fps, time_window=1) # 数据限速: 20条/秒 |
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self.running = True |
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self.image_dropped = 0 # 统计丢弃的图片数量 |
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self.data_dropped = 0 # 统计丢弃的数据数量 |
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def register_handler(self,handler_fun): |
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self.call_back = handler_fun |
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def run(self): |
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while self.running: |
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# 优先处理图片上报 |
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if not self.image_queue.empty() and self.image_limiter.allow_request(): |
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try: |
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image_data = self.image_queue.get_nowait() |
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self._report_image(image_data) |
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except queue.Empty: |
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pass |
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# 然后处理数据上报 |
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if not self.data_queue.empty() and self.data_limiter.allow_request(): |
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try: |
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data = self.data_queue.get_nowait() |
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self._report_data(data) |
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except queue.Empty: |
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pass |
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time.sleep(0.02) # 避免CPU占用过高 |
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def _report_image(self, data): |
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# 实现图片上报逻辑 |
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print(f"Reporting image, timestamp: {data[0]}") |
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# 这里替换为实际的上报代码 |
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msg = models.msg.Msg(_from="dev", cmd="image", values=data[1]) |
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msg_json = msg.to_json() |
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self.call_back(msg_json) |
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def _report_data(self, data): |
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# 实现数据上报逻辑 |
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print(f"Reporting data: {data}") |
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# 实际的上报代码,数据结构转换 |
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msg=models.msg.Msg(_from="dev",cmd="data",values=data[1]) |
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msg_json=msg.to_json() |
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self.call_back(msg_json) |
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def stop(self): |
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self.running = False |
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self.join() |
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print(f"Stats: {self.image_dropped} images dropped, {self.data_dropped} data dropped") |
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def adjust_rate(self, new_rate, data_type='image'): |
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if data_type == 'image': |
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with self.image_limiter.lock: |
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self.image_limiter.max_rate = new_rate |
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self.image_queue= queue.Queue(maxsize=new_rate) |
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else: |
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with self.data_limiter.lock: |
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self.data_limiter.max_rate = new_rate |
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self.data_queue = queue.Queue(maxsize=new_rate) |
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@ -1,12 +0,0 @@ |
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import queue |
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class DroppingQueue(queue.Queue): |
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"""自定义队列，满时自动丢弃最旧的数据""" |
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def put(self, item, block=False, timeout=None): |
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try: |
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return super().put(item, block=block, timeout=timeout) |
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except queue.Full: |
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# 队列满时丢弃最旧的一个数据 |
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self.get_nowait() |
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return super().put(item, block=False) |
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@ -1,23 +0,0 @@ |
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import threading |
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import queue |
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import time |
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from collections import deque |
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class RateLimiter: |
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def __init__(self, max_rate, time_window): |
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self.max_rate = max_rate # 最大允许的请求数 |
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self.time_window = time_window # 时间窗口(秒) |
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self.timestamps = deque() |
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self.lock = threading.Lock() |
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def allow_request(self): |
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with self.lock: |
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current_time = time.time() |
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# 移除超出时间窗口的时间戳 |
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while self.timestamps and current_time - self.timestamps[0] > self.time_window: |
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self.timestamps.popleft() |
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if len(self.timestamps) < self.max_rate: |
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self.timestamps.append(current_time) |
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return True |
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return False |
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@ -1,60 +0,0 @@ |
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import cv2 |
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import numpy as np |
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def pingyi(x,y): |
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# 获取图像的大小 |
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height, width = image.shape[:2] |
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|
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|
|
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# 构造平移矩阵：将原点移到图像中心 |
|
||||
M_translate = np.float32([ |
|
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[1, 0, x], |
|
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[0, 1, y], |
|
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[0, 0, 1] |
|
||||
]) |
|
||||
|
|
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return M_translate |
|
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def xuanzhuan_z(z): |
|
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# 构造沿Z轴旋转30度的旋转矩阵 |
|
||||
theta = np.radians(z) |
|
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cos_theta = np.cos(theta) |
|
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sin_theta = np.sin(theta) |
|
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M_z_rotate = np.float32([ |
|
||||
[cos_theta, -sin_theta, 0], |
|
||||
[sin_theta, cos_theta, 0], |
|
||||
[0, 0, 1] |
|
||||
]) |
|
||||
return M_z_rotate |
|
||||
def xuanzhuan_y(y): |
|
||||
# 构造沿Z轴旋转30度的旋转矩阵 |
|
||||
theta = np.radians(y) |
|
||||
rotation_vector = np.array([0, theta, 0]) # 绕Y轴旋转 |
|
||||
|
|
||||
# 计算旋转矩阵 |
|
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rotation_matrix, _ = cv2.Rodrigues(rotation_vector) |
|
||||
return rotation_matrix |
|
||||
if __name__ == '__main__': |
|
||||
# 读取图像 |
|
||||
image = cv2.imread("images/trans/transformed_image.jpg") |
|
||||
# 获取图像的大小 |
|
||||
height, width = image.shape[:2] |
|
||||
|
|
||||
m_pinyi=pingyi(width,0) |
|
||||
# m_xuanzhuan=xuanzhuan_z(30) |
|
||||
m_xuanzhuan = xuanzhuan_y(80) |
|
||||
M_combined = m_pinyi @ m_xuanzhuan |
|
||||
rotation_3d_int = np.clip(M_combined, 0, 255) |
|
||||
# 应用透视变换 |
|
||||
warped_image = cv2.warpPerspective( |
|
||||
image, |
|
||||
M_combined, |
|
||||
(width*2, height*2) |
|
||||
) |
|
||||
|
|
||||
# 显示结果 |
|
||||
cv2.imshow('Original Image', image) |
|
||||
cv2.imshow('Warped Image', warped_image) |
|
||||
cv2.waitKey(0) |
|
||||
cv2.destroyAllWindows() |
|
||||
|
|
||||
|
|
||||
@ -1,47 +0,0 @@ |
|||||
import cv2 |
|
||||
import numpy as np |
|
||||
|
|
||||
|
|
||||
|
|
||||
|
|
||||
def find_line(image): |
|
||||
if image is None: |
|
||||
print("Error: Unable to load image.") |
|
||||
exit() |
|
||||
gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) |
|
||||
blurred_image = cv2.GaussianBlur(gray_frame, (9, 9), 0) |
|
||||
ret, gray_frame = cv2.threshold(blurred_image, 50, 255, cv2.THRESH_BINARY) |
|
||||
cv2.imshow("binary", gray_frame) |
|
||||
# edges = cv2.Canny(blurred_image, 50, 150, apertureSize=3) |
|
||||
# 应用边缘检测 |
|
||||
edges = cv2.Canny(gray_frame, 200, 400, apertureSize=3) |
|
||||
|
|
||||
# 使用标准霍夫变换检测直线 |
|
||||
# 使用标准霍夫变换检测直线 |
|
||||
lines = cv2.HoughLines(edges, rho=3, theta=np.pi / 180, threshold=200) |
|
||||
|
|
||||
# 绘制检测到的直线 |
|
||||
if lines is not None: |
|
||||
for line in lines: |
|
||||
rho, theta = line[0] |
|
||||
a = np.cos(theta) |
|
||||
b = np.sin(theta) |
|
||||
x0 = a * rho |
|
||||
y0 = b * rho |
|
||||
x1 = int(x0 + 1000 * (-b)) |
|
||||
y1 = int(y0 + 1000 * (a)) |
|
||||
x2 = int(x0 - 1000 * (-b)) |
|
||||
y2 = int(y0 - 1000 * (a)) |
|
||||
cv2.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2) |
|
||||
|
|
||||
|
|
||||
|
|
||||
if __name__ == '__main__': |
|
||||
# 读取图像 |
|
||||
img = cv2.imread("images/trans/subRawImg.jpg") |
|
||||
|
|
||||
find_line(img) |
|
||||
# 显示结果 |
|
||||
cv2.imshow("Detected Lines", img) |
|
||||
cv2.waitKey(0) |
|
||||
cv2.destroyAllWindows() |
|
||||
Loading…
Reference in new issue