[ext] 修改transmit到一半

README.md

@@ -4,6 +4,7 @@
 
 ## 如何进行模型训练和部署？
 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)
+
 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：
     ```text
     dataset
@@ -14,11 +15,63 @@
         ├── img1.bmp
         └── ...
     ```
+
 3. 使用[02_classification.ipynb](./02_classification.ipynb)进行训练
+
 4. 使用[03_data_update.ipynb](02_classification.ipynb)进行数据的更新与添加
+
 5. 使用`main_test.py`文件进行读图测试
+
 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。
 
+## 如何进行参数调节？
+
+所有的参数均位于项目文件夹下的`config.py`当中。
+
+```python
+class Config:
+    # 文件相关参数
+    nRows, nCols, nBands = 256, 1024, 22
+    nRgbRows, nRgbCols, nRgbBands = 1024, 4096, 3
+
+    # 需要设置的谱段等参数
+    selected_bands = [127, 201, 202, 294]
+    bands = [127, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210,
+             211, 212, 213, 214, 215, 216, 217, 218, 219, 294]
+    is_yellow_min = np.array([0.10167048, 0.1644719, 0.1598884, 0.31534621])
+    is_yellow_max = np.array([0.212984, 0.25896924, 0.26509268, 0.51943593])
+    is_black_threshold = np.asarray([0.1369, 0.1472, 0.1439, 0.1814])
+    black_yellow_bands = [0, 2, 3, 21]
+    green_bands = [i for i in range(1, 21)]
+
+    # 光谱模型参数
+    blk_size = 4  # 必须是2的倍数，不然会出错
+    pixel_model_path = r"./models/pixel_2022-08-02_15-22.model"
+    blk_model_path = r"./models/rf_4x4_c22_20_sen8_9.model"
+    spec_size_threshold = 3 # 光谱大小阈值
+
+    # rgb模型参数
+    rgb_tobacco_model_path = r"models/tobacco_dt_2022-08-05_10-38.model"
+    rgb_background_model_path = r"models/background_dt_2022-08-09_16-08.model"
+    threshold_low, threshold_high = 10, 230 # 亮度最高值和最低值
+    threshold_s = 190 # 饱和度最高值允许值，超过该饱和度会被当作杂质
+    rgb_size_threshold = 4 # RGB大小阈值（在运行时会被界面修改）
+
+    # mask parameter
+    target_size = (1024, 1024)  # (Width, Height) of mask
+    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
+    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
+    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
+
+    # save part
+    offset_vertical = 0
+
+    # logging
+    root_dir = os.path.split(os.path.realpath(__file__))[0]
+```
+
+
+
 
 ## 训练的原理
 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。

transmit.py

@@ -1,7 +1,10 @@
+import multiprocessing
 import os
 import threading
 from multiprocessing import Process, Queue
 import time
+from multiprocessing.synchronize import Lock
+from threading import Lock
 
 import cv2
 
@@ -11,13 +14,15 @@ import functools
 import numpy as np
 from config import Config
 from models import SpecDetector, RgbDetector
-from typing import Any
+from typing import Any, Union
 import logging
 logging.basicConfig(format='%(asctime)s %(levelname)s %(name)s %(message)s',
                     level=logging.WARNING)
 
 
 class Transmitter(object):
+    _io_lock: Union[Lock, Lock]
+
     def __init__(self, job_name:str, run_process:bool = False):
         self.output = None
         self.job_name = job_name
@@ -25,6 +30,7 @@ class Transmitter(object):
         self._thread_stop = threading.Event()
         self._thread_stop.clear()
         self._running_handler = None
+        self._io_lock = multiprocessing.Lock() if run_process else threading.Lock()
 
     def set_source(self, *args, **kwargs):
         """
@@ -35,13 +41,13 @@ class Transmitter(object):
         """
         raise NotImplementedError
 
-    def set_output(self, output: ImgQueue):
+    def set_output(self, *args, **kwargs):
         """
-        设置单个输出源
+        设置输出源
         :param output:
         :return:
         """
-        self.output = output
+        raise NotImplementedError
 
     def start(self, *args, **kwargs):
         """
@@ -113,6 +119,44 @@ class BeforeAfterMethods:
             return rgb_img
 
 
+class FileReceiver(Transmitter):
+    def __init__(self, job_name:str, input_dir: str, output_queue:ImgQueue, speed: int=3, name_pattern=None):
+        super(FileReceiver, self).__init__(job_name=job_name, run_process=False)
+        self.input_dir = input_dir
+        self.send_speed = speed
+        self.file_names = None
+        self.name_pattern = name_pattern
+        self.file_idx = 0
+        self.output_queue = None
+        self.set_source(input_dir, name_pattern)
+        self.set_output(output_queue)
+
+    def set_source(self, input_dir, name_pattern=None):
+        self.name_pattern = name_pattern if name_pattern is not None else self.name_pattern
+        file_names = os.listdir(input_dir)
+        if len(file_names) == 0:
+            logging.warning('指定了空的文件夹')
+        if self.name_pattern is not None:
+            file_names = [file_name for file_name in file_names if (self.name_pattern in file_name)]
+        else:
+            file_names = file_names
+
+        with self._io_lock:
+            self.file_names = file_names
+            self.file_idx = 0
+
+    def set_output(self, output: ImgQueue):
+        with self._io_lock:
+            self.output_queue = output
+
+    @Transmitter.job_decorator
+    def job_func(self, *args, **kwargs):
+        with self._io_lock:
+            self.file_idx += 1
+            if self.file_idx == len()
+            file_name = self.file_names[self.file_idx]
+
+
 class FifoReceiver(Transmitter):
     def __init__(self, job_name:str, fifo_path: str, output: ImgQueue,
                  read_max_num: int, msg_queue=None):
@@ -169,31 +213,23 @@ class FifoSender(Transmitter):
             os.mkfifo(output_fifo_path, 0o777)
         self._output_fifo_path = output_fifo_path
 
-    def start(self, pre_process=None, name='fifo_receiver'):
-        self._running_thread = threading.Thread(target=self._send_thread_func, name=name,
-                                                args=(pre_process, ))
-        self._running_thread.start()
 
-    def stop(self):
+    def job_func(self, pre_process, *args, **kwargs):
-        self._need_stop.set()
-
-    def _send_thread_func(self, pre_process=None):
         """
         接收线程
 
         :param pre_process:
         :return:
         """
-        while not self._need_stop.is_set():
+        if self._input_source.empty():
-            if self._input_source.empty():
+            return
-                continue
+        data = self._input_source.get()
-            data = self._input_source.get()
+        if pre_process is not None:
-            if pre_process is not None:
+            data = pre_process(data)
-                data = pre_process(data)
+        output_fifo = os.open(self._output_fifo_path, os.O_WRONLY)
-            output_fifo = os.open(self._output_fifo_path, os.O_WRONLY)
+        os.write(output_fifo, data)
-            os.write(output_fifo, data)
+        os.close(output_fifo)
-            os.close(output_fifo)
+
-        self._need_stop.clear()
 
     def __del__(self):
         self.stop()