AP/detection.py

import sys
import cv2
import numpy as np
import multiprocessing
from PyQt5 import QtWidgets, QtGui, QtCore
from PyQt5.QtCore import QTimer
from ultralytics import YOLO

from Detection_window import Ui_MainWindow
from camera.camera_process import CameraProcess
from read_ini import ConfigReader
from log_handler import LogHandler
from Yolo_predict import YoloPredict

class DetectionApp(QtWidgets.QMainWindow, Ui_MainWindow):
    def __init__(self):
        super(DetectionApp, self).__init__()
        self.setupUi(self)

        self.log_handler = LogHandler()  # ✅ 建立 LogHandler 物件
        self.log_handler.write_log("程式啟動")  # ✅ 寫入 log: 程式啟動

        # ✅ 讀取 `exposure_time`
        self.config_reader = ConfigReader()
        self.exposure_time = self.config_reader.get_exposure_time()

        # ✅ 先初始化 image_queue，再啟動相機擷取
        self.image_queue = multiprocessing.Queue(maxsize=1)
        self.camera_process = None  # 相機進程尚未啟動
        self.latest_image = None  # 存儲最新影像

        # ✅ 載入 YOLO模型
        try:
            self.model = YOLO("model/best.pt")
            self.log_handler.write_log("YOLO 模型載入成功")
        except Exception as e:
            self.log_handler.write_log(f"⚠️ YOLO 模型載入失敗: {e}")
            self.model = None

        # ✅ 連接按鈕事件
        self.bt_KeepShot.clicked.connect(self.KeepShot)
        self.bt_StopKeepShot.clicked.connect(self.StopKeepShot)
        self.bt_detection.clicked.connect(self.detection)

        # 鎖定檢測按鈕及停止相機連續取像
        self.bt_detection.setEnabled(False)
        self.bt_StopKeepShot.setEnabled(False)

        # ✅ 設定 QTimer，每 100ms 更新影像
        self.timer = QTimer(self)
        self.timer.timeout.connect(self.update_view_origin)
        self.timer.start(100)  # 每 100ms 更新一次影像

    def KeepShot(self):
        """ 啟動相機擷取 """
        if self.camera_process is None or not self.camera_process.is_alive():
            self.StopKeepShot()  # 確保先停止舊的 Process，避免衝突

            # ✅ 重新建立 Queue，避免殘留影像影響新擷取
            self.image_queue = multiprocessing.Queue(maxsize=1)

            # ✅ 使用 `exposure_time` 啟動相機
            self.camera_process = CameraProcess(self.image_queue, exposure_time=self.exposure_time)
            self.camera_process.start()
            self.log_handler.write_log("相機啟動")  # ✅ 寫入 log: 相機啟動
            self.statusbar.showMessage(f"開始擷取影像 (曝光時間: {self.exposure_time} 微秒)")

            # 按鈕setEnable
            self.bt_KeepShot.setEnabled(False)
            self.bt_StopKeepShot.setEnabled(True)
            self.bt_detection.setEnabled(True)
        else:
            print("相機已經在擷取")

    def StopKeepShot(self):
        """ 停止相機擷取 """
        if self.camera_process and self.camera_process.is_alive():
            self.camera_process.stop()  # 停止擷取
            self.camera_process.join()  # 等待進程完全結束
            self.camera_process = None
            print("已停止影像擷取")
            self.log_handler.write_log("相機停止")  # ✅ 寫入 log: 相機停止

            # 按鈕setEnable
            self.bt_KeepShot.setEnabled(True)
            self.bt_StopKeepShot.setEnabled(False)
            self.bt_detection.setEnabled(False)
        # ✅ 清空 Queue，確保新擷取不會讀取到舊影像
        while not self.image_queue.empty():
            try:
                self.image_queue.get_nowait()
            except:
                break

    def update_view_origin(self):
        """ 從 Queue 獲取影像並顯示在 QLabel (view_origin) 上 """
        if not self.image_queue.empty():
            image = self.image_queue.get()  # 取得最新影像
            self.latest_image = image  # 存儲最新影像
            self.display_image(image, self.view_origin)

    def display_image(self, image, label):
        """ 顯示影像到 QLabel """
        try:
            image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) if len(image.shape) == 2 else image
            height, width, channel = image_bgr.shape
            bytes_per_line = 3 * width
            qimage = QtGui.QImage(image_bgr.data, width, height, bytes_per_line, QtGui.QImage.Format_BGR888)
            pixmap = QtGui.QPixmap.fromImage(qimage).scaled(label.size(), QtCore.Qt.KeepAspectRatio)
            label.setPixmap(pixmap)
        except Exception as e:
            self.log_handler.write_log(f"⚠️ 顯示影像時發生錯誤: {e}")

    def detection(self):
        """ 啟動 YOLO 推論執行緒 """
        if self.latest_image is None:
            self.log_handler.write_log("⚠️ 無影像可進行推論")
            return

        # ✅ 啟動 YOLO 推論執行緒
        self.yolo_thread = YoloPredict(
            image=self.latest_image,
            model_path="model/best.pt",
            callback=self.on_detection_complete  # ✅ 設定回呼函數
        )
        self.yolo_thread.start()
        self.log_handler.write_log("YOLO 推論執行中...")

    def on_detection_complete(self, result_image, save_path):
        """ YOLO 推論完成後的回呼函數 """
        self.display_image(result_image, self.view_predict)
        self.statusbar.showMessage(f"推論結果已儲存: {save_path}")
        self.log_handler.write_log(f"推論結果儲存至: {save_path}")

    def closeEvent(self, event):
        reply = QtWidgets.QMessageBox.question(
            self, "確認", "確定要關閉應用程式嗎？",
            QtWidgets.QMessageBox.Yes | QtWidgets.QMessageBox.No, QtWidgets.QMessageBox.No
        )

        if reply == QtWidgets.QMessageBox.Yes:
            self.StopKeepShot()  # 停止相機
            self.log_handler.write_log("程式關閉")  # ✅ 寫入 log: 程式關閉
            event.accept()  # 允許視窗關閉
        else:
            event.ignore()  # 阻止視窗關閉

if __name__ == "__main__":
    multiprocessing.freeze_support()  # 在 Windows 上執行 multiprocessing 需要這行
    app = QtWidgets.QApplication(sys.argv)
    window = DetectionApp()
    window.show()
    sys.exit(app.exec_())