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[ext] 修改transmit到一半
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README.md
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README.md
@ -4,6 +4,7 @@
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## 如何进行模型训练和部署？
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1. 项目当中需要包含`data`和`models`这两个文件夹，请下载到当前文件夹下,这是链接：[data](https://macrosolid-my.sharepoint.com/personal/feijinti_miaow_fun/_layouts/15/onedrive.aspx?id=%2Fpersonal%2Ffeijinti%5Fmiaow%5Ffun%2FDocuments%2FPycharmProjects%2Ftobacco%5Fcolor%2Fdata&ga=1), [models](https://macrosolid-my.sharepoint.com/:f:/g/personal/feijinti_miaow_fun/EiyBjWEX90JGn8S-e5Kh7N8B1GWvfvDcNbpleWDTwkDm1w?e=wyL4EF)
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2. 使用[01_dataset.ipynb](./01_dataset.ipynb) 进行数据集的分析文件格式需要设置为这种形式：
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```text
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dataset
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@ -14,11 +15,63 @@
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├── img1.bmp
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└── ...
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```
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3. 使用[02_classification.ipynb](./02_classification.ipynb)进行训练
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4. 使用[03_data_update.ipynb](02_classification.ipynb)进行数据的更新与添加
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5. 使用`main_test.py`文件进行读图测试
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6. **部署**，复制`utils.py`、`models.py`、`main.py`、`models/`、`config.py`这5个文件或文件夹，运行main.py来提供预测服务。
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## 如何进行参数调节？
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所有的参数均位于项目文件夹下的`config.py`当中。
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```python
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class Config:
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# 文件相关参数
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nRows, nCols, nBands = 256, 1024, 22
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nRgbRows, nRgbCols, nRgbBands = 1024, 4096, 3
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# 需要设置的谱段等参数
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selected_bands = [127, 201, 202, 294]
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bands = [127, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210,
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211, 212, 213, 214, 215, 216, 217, 218, 219, 294]
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is_yellow_min = np.array([0.10167048, 0.1644719, 0.1598884, 0.31534621])
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is_yellow_max = np.array([0.212984, 0.25896924, 0.26509268, 0.51943593])
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is_black_threshold = np.asarray([0.1369, 0.1472, 0.1439, 0.1814])
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black_yellow_bands = [0, 2, 3, 21]
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green_bands = [i for i in range(1, 21)]
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# 光谱模型参数
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blk_size = 4 # 必须是2的倍数，不然会出错
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pixel_model_path = r"./models/pixel_2022-08-02_15-22.model"
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blk_model_path = r"./models/rf_4x4_c22_20_sen8_9.model"
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spec_size_threshold = 3 # 光谱大小阈值
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# rgb模型参数
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rgb_tobacco_model_path = r"models/tobacco_dt_2022-08-05_10-38.model"
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rgb_background_model_path = r"models/background_dt_2022-08-09_16-08.model"
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threshold_low, threshold_high = 10, 230 # 亮度最高值和最低值
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threshold_s = 190 # 饱和度最高值允许值，超过该饱和度会被当作杂质
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rgb_size_threshold = 4 # RGB大小阈值（在运行时会被界面修改）
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# mask parameter
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target_size = (1024, 1024) # (Width, Height) of mask
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valve_merge_size = 2 # 每两个喷阀当中有任意一个出现杂质则认为都是杂质
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valve_horizontal_padding = 3 # 喷阀横向膨胀的尺寸，应该是奇数,3时表示左右各膨胀1
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max_open_valve_limit = 25 # 最大同时开启喷阀限制,按照电流计算，当前的喷阀可以开启的喷阀 600W的电源 / 12V电源 = 50A, 一个阀门1A
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# save part
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offset_vertical = 0
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# logging
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root_dir = os.path.split(os.path.realpath(__file__))[0]
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```
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## 训练的原理
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为了应对工业环境当中负样本少的特点，我们结合颜色有限空间的特性对我们的训练过程进行了优化，核心的优化方式在于制造负样本。
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80
transmit.py
80
transmit.py
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import multiprocessing
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import os
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import threading
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from multiprocessing import Process, Queue
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import time
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from multiprocessing.synchronize import Lock
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from threading import Lock
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import cv2
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@ -11,13 +14,15 @@ import functools
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import numpy as np
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from config import Config
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from models import SpecDetector, RgbDetector
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from typing import Any
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from typing import Any, Union
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import logging
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logging.basicConfig(format='%(asctime)s %(levelname)s %(name)s %(message)s',
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level=logging.WARNING)
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class Transmitter(object):
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_io_lock: Union[Lock, Lock]
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def __init__(self, job_name:str, run_process:bool = False):
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self.output = None
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self.job_name = job_name
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@ -25,6 +30,7 @@ class Transmitter(object):
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self._thread_stop = threading.Event()
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self._thread_stop.clear()
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self._running_handler = None
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self._io_lock = multiprocessing.Lock() if run_process else threading.Lock()
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def set_source(self, *args, **kwargs):
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"""
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@ -35,13 +41,13 @@ class Transmitter(object):
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"""
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raise NotImplementedError
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def set_output(self, output: ImgQueue):
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def set_output(self, *args, **kwargs):
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"""
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设置单个输出源
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设置输出源
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:param output:
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:return:
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"""
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self.output = output
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raise NotImplementedError
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def start(self, *args, **kwargs):
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"""
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@ -113,6 +119,44 @@ class BeforeAfterMethods:
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return rgb_img
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class FileReceiver(Transmitter):
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def __init__(self, job_name:str, input_dir: str, output_queue:ImgQueue, speed: int=3, name_pattern=None):
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super(FileReceiver, self).__init__(job_name=job_name, run_process=False)
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self.input_dir = input_dir
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self.send_speed = speed
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self.file_names = None
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self.name_pattern = name_pattern
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self.file_idx = 0
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self.output_queue = None
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self.set_source(input_dir, name_pattern)
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self.set_output(output_queue)
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def set_source(self, input_dir, name_pattern=None):
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self.name_pattern = name_pattern if name_pattern is not None else self.name_pattern
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file_names = os.listdir(input_dir)
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if len(file_names) == 0:
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logging.warning('指定了空的文件夹')
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if self.name_pattern is not None:
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file_names = [file_name for file_name in file_names if (self.name_pattern in file_name)]
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else:
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file_names = file_names
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with self._io_lock:
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self.file_names = file_names
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self.file_idx = 0
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def set_output(self, output: ImgQueue):
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with self._io_lock:
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self.output_queue = output
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@Transmitter.job_decorator
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def job_func(self, *args, **kwargs):
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with self._io_lock:
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self.file_idx += 1
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if self.file_idx == len()
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file_name = self.file_names[self.file_idx]
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class FifoReceiver(Transmitter):
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def __init__(self, job_name:str, fifo_path: str, output: ImgQueue,
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read_max_num: int, msg_queue=None):
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@ -169,31 +213,23 @@ class FifoSender(Transmitter):
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os.mkfifo(output_fifo_path, 0o777)
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self._output_fifo_path = output_fifo_path
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def start(self, pre_process=None, name='fifo_receiver'):
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self._running_thread = threading.Thread(target=self._send_thread_func, name=name,
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args=(pre_process, ))
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self._running_thread.start()
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def stop(self):
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self._need_stop.set()
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def _send_thread_func(self, pre_process=None):
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def job_func(self, pre_process, *args, **kwargs):
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"""
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接收线程
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:param pre_process:
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:return:
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"""
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while not self._need_stop.is_set():
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if self._input_source.empty():
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continue
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data = self._input_source.get()
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if pre_process is not None:
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data = pre_process(data)
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output_fifo = os.open(self._output_fifo_path, os.O_WRONLY)
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os.write(output_fifo, data)
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os.close(output_fifo)
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self._need_stop.clear()
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if self._input_source.empty():
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return
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data = self._input_source.get()
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if pre_process is not None:
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data = pre_process(data)
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output_fifo = os.open(self._output_fifo_path, os.O_WRONLY)
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os.write(output_fifo, data)
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os.close(output_fifo)
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def __del__(self):
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self.stop()
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