修改UI 把yolo_predict寫成threading
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56
Yolo_predict.py
Normal file
56
Yolo_predict.py
Normal file
@ -0,0 +1,56 @@
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import os
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import cv2
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import datetime
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import threading
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from ultralytics import YOLO
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class YoloPredict(threading.Thread):
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""" YOLO 推論執行緒 """
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def __init__(self, image, model_path, save_dir="results", callback=None):
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super(YoloPredict, self).__init__()
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self.image = image
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self.model_path = model_path
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self.save_dir = save_dir
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self.callback = callback # ✅ 設定回呼函數
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self.model = None
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# ✅ 確保 `results/` 資料夾存在
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if not os.path.exists(self.save_dir):
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os.makedirs(self.save_dir)
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def run(self):
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""" 執行 YOLO 推論 """
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if self.image is None:
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print("⚠️ 無影像可進行推論")
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return
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try:
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# ✅ 載入 YOLO 模型
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if self.model is None:
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self.model = YOLO(self.model_path)
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print("✅ YOLO 模型載入成功")
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# ✅ 轉換影像格式 (BGR → RGB)
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image_rgb = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)
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# ✅ 使用 YOLO 模型進行推論
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results = self.model.predict(image_rgb, imgsz=640, conf=0.5)
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print("✅ YOLO 推論完成")
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# ✅ 取得標註結果
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result_image = results[0].plot()
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# ✅ 儲存影像
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timestamp = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
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save_path = os.path.join(self.save_dir, f"{timestamp}.jpg")
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result_image_bgr = cv2.cvtColor(result_image, cv2.COLOR_RGB2BGR)
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cv2.imwrite(save_path, result_image_bgr)
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print(f"✅ 推論結果儲存至: {save_path}")
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# ✅ 回傳結果到主視窗 (`callback` 函數)
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if self.callback:
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self.callback(result_image, save_path)
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except Exception as e:
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print(f"⚠️ 推論時發生錯誤: {e}")
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@ -1,131 +0,0 @@
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# -*- coding: utf-8 -*-
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# Form implementation generated from reading ui file 'Main.ui'
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#
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# Created by: PyQt5 UI code generator 5.15.6
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#
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# WARNING: Any manual changes made to this file will be lost when pyuic5 is
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# run again. Do not edit this file unless you know what you are doing.
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from PyQt5 import QtCore, QtGui, QtWidgets
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class Ui_MainWindow(object):
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def setupUi(self, MainWindow):
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MainWindow.setObjectName("MainWindow")
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MainWindow.resize(1363, 916)
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self.centralwidget = QtWidgets.QWidget(MainWindow)
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self.centralwidget.setObjectName("centralwidget")
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self.widget = QtWidgets.QWidget(self.centralwidget)
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self.widget.setGeometry(QtCore.QRect(20, 140, 2008, 1002))
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self.widget.setObjectName("widget")
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self.horizontalLayout_3 = QtWidgets.QHBoxLayout(self.widget)
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self.horizontalLayout_3.setContentsMargins(0, 0, 0, 0)
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self.horizontalLayout_3.setObjectName("horizontalLayout_3")
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self.label_2 = QtWidgets.QLabel(self.widget)
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self.label_2.setMinimumSize(QtCore.QSize(1000, 1000))
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self.label_2.setMaximumSize(QtCore.QSize(1000, 1000))
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self.label_2.setObjectName("label_2")
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self.horizontalLayout_3.addWidget(self.label_2)
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self.label = QtWidgets.QLabel(self.widget)
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self.label.setMinimumSize(QtCore.QSize(1000, 1000))
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self.label.setMaximumSize(QtCore.QSize(1000, 1000))
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self.label.setObjectName("label")
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self.horizontalLayout_3.addWidget(self.label)
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self.widget1 = QtWidgets.QWidget(self.centralwidget)
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self.widget1.setGeometry(QtCore.QRect(21, 20, 758, 116))
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self.widget1.setObjectName("widget1")
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self.horizontalLayout_6 = QtWidgets.QHBoxLayout(self.widget1)
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self.horizontalLayout_6.setContentsMargins(0, 0, 0, 0)
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self.horizontalLayout_6.setObjectName("horizontalLayout_6")
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self.verticalLayout_2 = QtWidgets.QVBoxLayout()
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self.verticalLayout_2.setObjectName("verticalLayout_2")
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self.horizontalLayout = QtWidgets.QHBoxLayout()
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self.horizontalLayout.setObjectName("horizontalLayout")
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self.bt_camera_connect = QtWidgets.QPushButton(self.widget1)
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self.bt_camera_connect.setMinimumSize(QtCore.QSize(101, 51))
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self.bt_camera_connect.setMaximumSize(QtCore.QSize(101, 51))
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self.bt_camera_connect.setObjectName("bt_camera_connect")
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self.horizontalLayout.addWidget(self.bt_camera_connect)
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self.bt_OneShot = QtWidgets.QPushButton(self.widget1)
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self.bt_OneShot.setMinimumSize(QtCore.QSize(101, 51))
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self.bt_OneShot.setMaximumSize(QtCore.QSize(101, 51))
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self.bt_OneShot.setObjectName("bt_OneShot")
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self.horizontalLayout.addWidget(self.bt_OneShot)
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self.bt_KeetShot = QtWidgets.QPushButton(self.widget1)
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self.bt_KeetShot.setMinimumSize(QtCore.QSize(101, 51))
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self.bt_KeetShot.setMaximumSize(QtCore.QSize(101, 51))
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self.bt_KeetShot.setObjectName("bt_KeetShot")
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self.horizontalLayout.addWidget(self.bt_KeetShot)
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self.verticalLayout_2.addLayout(self.horizontalLayout)
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self.horizontalLayout_4 = QtWidgets.QHBoxLayout()
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self.horizontalLayout_4.setObjectName("horizontalLayout_4")
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self.bt_open_image = QtWidgets.QPushButton(self.widget1)
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self.bt_open_image.setMinimumSize(QtCore.QSize(101, 51))
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self.bt_open_image.setMaximumSize(QtCore.QSize(101, 51))
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self.bt_open_image.setObjectName("bt_open_image")
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self.horizontalLayout_4.addWidget(self.bt_open_image)
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self.bt_save_image = QtWidgets.QPushButton(self.widget1)
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self.bt_save_image.setMinimumSize(QtCore.QSize(101, 51))
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self.bt_save_image.setMaximumSize(QtCore.QSize(101, 51))
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self.bt_save_image.setObjectName("bt_save_image")
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self.horizontalLayout_4.addWidget(self.bt_save_image)
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self.verticalLayout_2.addLayout(self.horizontalLayout_4)
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self.horizontalLayout_6.addLayout(self.verticalLayout_2)
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self.verticalLayout = QtWidgets.QVBoxLayout()
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self.verticalLayout.setObjectName("verticalLayout")
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self.horizontalLayout_5 = QtWidgets.QHBoxLayout()
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self.horizontalLayout_5.setObjectName("horizontalLayout_5")
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self.label_3 = QtWidgets.QLabel(self.widget1)
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self.label_3.setMinimumSize(QtCore.QSize(91, 31))
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self.label_3.setMaximumSize(QtCore.QSize(91, 31))
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self.label_3.setObjectName("label_3")
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self.horizontalLayout_5.addWidget(self.label_3)
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self.Ex_time = QtWidgets.QTextEdit(self.widget1)
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self.Ex_time.setMinimumSize(QtCore.QSize(100, 30))
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self.Ex_time.setMaximumSize(QtCore.QSize(100, 30))
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self.Ex_time.setObjectName("Ex_time")
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self.horizontalLayout_5.addWidget(self.Ex_time)
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spacerItem = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum)
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self.horizontalLayout_5.addItem(spacerItem)
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self.verticalLayout.addLayout(self.horizontalLayout_5)
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self.horizontalLayout_2 = QtWidgets.QHBoxLayout()
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self.horizontalLayout_2.setObjectName("horizontalLayout_2")
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self.threshold = QtWidgets.QTextEdit(self.widget1)
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self.threshold.setMinimumSize(QtCore.QSize(100, 30))
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self.threshold.setMaximumSize(QtCore.QSize(100, 30))
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self.threshold.setObjectName("threshold")
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self.horizontalLayout_2.addWidget(self.threshold)
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self.threshold_value = QtWidgets.QSlider(self.widget1)
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self.threshold_value.setMinimumSize(QtCore.QSize(321, 16))
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self.threshold_value.setMaximumSize(QtCore.QSize(321, 16))
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self.threshold_value.setMaximum(255)
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self.threshold_value.setOrientation(QtCore.Qt.Horizontal)
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self.threshold_value.setObjectName("threshold_value")
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self.horizontalLayout_2.addWidget(self.threshold_value)
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self.verticalLayout.addLayout(self.horizontalLayout_2)
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self.horizontalLayout_6.addLayout(self.verticalLayout)
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MainWindow.setCentralWidget(self.centralwidget)
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self.menubar = QtWidgets.QMenuBar(MainWindow)
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self.menubar.setGeometry(QtCore.QRect(0, 0, 1363, 22))
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self.menubar.setObjectName("menubar")
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MainWindow.setMenuBar(self.menubar)
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self.statusbar = QtWidgets.QStatusBar(MainWindow)
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self.statusbar.setObjectName("statusbar")
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MainWindow.setStatusBar(self.statusbar)
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self.retranslateUi(MainWindow)
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QtCore.QMetaObject.connectSlotsByName(MainWindow)
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def retranslateUi(self, MainWindow):
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_translate = QtCore.QCoreApplication.translate
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MainWindow.setWindowTitle(_translate("MainWindow", "MainWindow"))
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self.label_2.setText(_translate("MainWindow", "二值化"))
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self.label.setText(_translate("MainWindow", "原圖"))
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self.bt_camera_connect.setText(_translate("MainWindow", "相機連線"))
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self.bt_OneShot.setText(_translate("MainWindow", "單張擷取"))
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self.bt_KeetShot.setText(_translate("MainWindow", "連續取像"))
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self.bt_open_image.setText(_translate("MainWindow", "讀入影像"))
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self.bt_save_image.setText(_translate("MainWindow", "儲存影像"))
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self.label_3.setText(_translate("MainWindow", "曝光時間"))
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@ -1,299 +0,0 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<ui version="4.0">
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<class>MainWindow</class>
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<widget class="QMainWindow" name="MainWindow">
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<property name="geometry">
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<rect>
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<x>0</x>
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<y>0</y>
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<width>1363</width>
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<height>916</height>
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</rect>
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</property>
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<property name="windowTitle">
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<string>MainWindow</string>
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</property>
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<widget class="QWidget" name="centralwidget">
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<widget class="QWidget" name="">
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<property name="geometry">
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<rect>
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<x>20</x>
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<y>140</y>
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<width>2008</width>
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<height>1002</height>
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</rect>
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</property>
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<layout class="QHBoxLayout" name="horizontalLayout_3">
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<item>
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<widget class="QLabel" name="label_2">
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<property name="minimumSize">
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<size>
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<width>1000</width>
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<height>1000</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>1000</width>
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<height>1000</height>
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</size>
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</property>
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<property name="text">
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<string>二值化</string>
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</property>
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</widget>
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</item>
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<item>
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<widget class="QLabel" name="label">
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<property name="minimumSize">
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<size>
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<width>1000</width>
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<height>1000</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>1000</width>
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<height>1000</height>
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</size>
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</property>
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<property name="text">
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<string>原圖</string>
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</property>
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</widget>
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</item>
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</layout>
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</widget>
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<widget class="QWidget" name="">
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<property name="geometry">
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<rect>
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<x>21</x>
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<y>20</y>
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<width>758</width>
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<height>116</height>
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</rect>
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</property>
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<layout class="QHBoxLayout" name="horizontalLayout_6">
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<item>
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<layout class="QVBoxLayout" name="verticalLayout_2">
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<item>
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<layout class="QHBoxLayout" name="horizontalLayout">
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<item>
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<widget class="QPushButton" name="bt_camera_connect">
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<property name="minimumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="text">
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<string>相機連線</string>
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</property>
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</widget>
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</item>
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<item>
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<widget class="QPushButton" name="bt_OneShot">
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<property name="minimumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="text">
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<string>單張擷取</string>
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</property>
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</widget>
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</item>
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<item>
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<widget class="QPushButton" name="bt_KeetShot">
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<property name="minimumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="text">
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<string>連續取像</string>
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</property>
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</widget>
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</item>
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</layout>
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</item>
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<item>
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<layout class="QHBoxLayout" name="horizontalLayout_4">
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<item>
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<widget class="QPushButton" name="bt_open_image">
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<property name="minimumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="text">
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<string>讀入影像</string>
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</property>
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</widget>
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</item>
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<item>
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<widget class="QPushButton" name="bt_save_image">
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<property name="minimumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>101</width>
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<height>51</height>
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</size>
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</property>
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<property name="text">
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<string>儲存影像</string>
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</property>
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</widget>
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</item>
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</layout>
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</item>
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</layout>
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</item>
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<item>
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<layout class="QVBoxLayout" name="verticalLayout">
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<item>
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<layout class="QHBoxLayout" name="horizontalLayout_5">
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<item>
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<widget class="QLabel" name="label_3">
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<property name="minimumSize">
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<size>
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<width>91</width>
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<height>31</height>
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</size>
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</property>
|
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<property name="maximumSize">
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<size>
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<width>91</width>
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<height>31</height>
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</size>
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</property>
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<property name="text">
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<string>曝光時間</string>
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</property>
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</widget>
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</item>
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<item>
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<widget class="QTextEdit" name="Ex_time">
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<property name="minimumSize">
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<size>
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<width>100</width>
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<height>30</height>
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</size>
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</property>
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<property name="maximumSize">
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<size>
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<width>100</width>
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<height>30</height>
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</size>
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</property>
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</widget>
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</item>
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<item>
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<spacer name="horizontalSpacer">
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<property name="orientation">
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<enum>Qt::Horizontal</enum>
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</property>
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<property name="sizeHint" stdset="0">
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<size>
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<width>40</width>
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<height>20</height>
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</size>
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</property>
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</spacer>
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</item>
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</layout>
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</item>
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<item>
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<layout class="QHBoxLayout" name="horizontalLayout_2">
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<item>
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<widget class="QTextEdit" name="threshold">
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<property name="minimumSize">
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<size>
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<width>100</width>
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<height>30</height>
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</size>
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</property>
|
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<property name="maximumSize">
|
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<size>
|
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<width>100</width>
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||||
<height>30</height>
|
||||
</size>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
<item>
|
||||
<widget class="QSlider" name="threshold_value">
|
||||
<property name="minimumSize">
|
||||
<size>
|
||||
<width>321</width>
|
||||
<height>16</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximumSize">
|
||||
<size>
|
||||
<width>321</width>
|
||||
<height>16</height>
|
||||
</size>
|
||||
</property>
|
||||
<property name="maximum">
|
||||
<number>255</number>
|
||||
</property>
|
||||
<property name="orientation">
|
||||
<enum>Qt::Horizontal</enum>
|
||||
</property>
|
||||
</widget>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</item>
|
||||
</layout>
|
||||
</widget>
|
||||
</widget>
|
||||
<widget class="QMenuBar" name="menubar">
|
||||
<property name="geometry">
|
||||
<rect>
|
||||
<x>0</x>
|
||||
<y>0</y>
|
||||
<width>1363</width>
|
||||
<height>22</height>
|
||||
</rect>
|
||||
</property>
|
||||
</widget>
|
||||
<widget class="QStatusBar" name="statusbar"/>
|
||||
</widget>
|
||||
<resources/>
|
||||
<connections/>
|
||||
</ui>
|
||||
@ -1,226 +0,0 @@
|
||||
import sys
|
||||
from PyQt5 import QtWidgets, QtGui, QtCore
|
||||
from PyQt5.QtCore import QTimer
|
||||
from PyQt5.QtWidgets import QFileDialog
|
||||
from pypylon import pylon
|
||||
import cv2
|
||||
import numpy as np
|
||||
import os
|
||||
from Main import Ui_MainWindow
|
||||
|
||||
class CameraApp(QtWidgets.QMainWindow, Ui_MainWindow):
|
||||
def __init__(self):
|
||||
super(CameraApp, self).__init__()
|
||||
self.setupUi(self)
|
||||
|
||||
# 連接按鈕事件
|
||||
self.bt_camera_connect.clicked.connect(self.connect_camera)
|
||||
self.bt_OneShot.clicked.connect(self.one_shot_capture)
|
||||
self.bt_KeetShot.clicked.connect(self.keep_shot_capture)
|
||||
self.bt_open_image.clicked.connect(self.open_image)
|
||||
self.bt_save_image.clicked.connect(self.save_image) # 連接儲存影像按鈕事件
|
||||
|
||||
# 初始化變數
|
||||
self.camera = None
|
||||
self.timer = QTimer()
|
||||
self.timer.timeout.connect(self.keep_shot_process)
|
||||
|
||||
# 設定 QSlider 範圍和事件
|
||||
self.threshold_value.setMinimum(0)
|
||||
self.threshold_value.setMaximum(255)
|
||||
self.threshold_value.setValue(127) # 預設閥值
|
||||
self.threshold_value.valueChanged.connect(self.update_threshold)
|
||||
|
||||
self.threshold.setText(str(self.threshold_value.value()))
|
||||
self.current_image = None
|
||||
|
||||
def get_bgr_image(self):
|
||||
"""取得 BGR 格式的影像"""
|
||||
if self.current_image is None:
|
||||
return None
|
||||
|
||||
# 若影像為單通道或 Bayer 格式，進行轉換
|
||||
if len(self.current_image.shape) == 2 or self.current_image.shape[2] == 1:
|
||||
return cv2.cvtColor(self.current_image, cv2.COLOR_BayerBG2BGR)
|
||||
else:
|
||||
return self.current_image
|
||||
|
||||
def connect_camera(self):
|
||||
try:
|
||||
self.camera = pylon.InstantCamera(pylon.TlFactory.GetInstance().CreateFirstDevice())
|
||||
self.camera.Open()
|
||||
self.statusbar.showMessage("相機連線成功")
|
||||
except Exception as e:
|
||||
self.statusbar.showMessage(f"相機連線失敗: {e}")
|
||||
|
||||
def get_exposure_time(self):
|
||||
"""從 QTextEdit 取得曝光時間，若為空則使用預設值"""
|
||||
exposure_time_text = self.Ex_time.toPlainText().strip()
|
||||
|
||||
# 當 QTextEdit 值為空時使用預設值
|
||||
if not exposure_time_text:
|
||||
return 5000 # 預設曝光時間（微秒）
|
||||
|
||||
# 驗證是否為數值
|
||||
if exposure_time_text.isdigit():
|
||||
return int(exposure_time_text)
|
||||
|
||||
self.statusbar.showMessage("請輸入有效的曝光時間（整數），使用預設值 5000 微秒")
|
||||
return 5000
|
||||
|
||||
def one_shot_capture(self):
|
||||
if not (self.camera and self.camera.IsOpen()):
|
||||
self.statusbar.showMessage("請先連接相機")
|
||||
return
|
||||
|
||||
try:
|
||||
exposure_time = self.get_exposure_time()
|
||||
self.camera.ExposureTime.SetValue(float(exposure_time))
|
||||
self.statusbar.showMessage(f"曝光時間設定為 {exposure_time} 微秒")
|
||||
|
||||
if self.camera.IsGrabbing():
|
||||
self.camera.StopGrabbing()
|
||||
|
||||
self.camera.StartGrabbing(1)
|
||||
grab_result = self.camera.RetrieveResult(5000, pylon.TimeoutHandling_Return)
|
||||
|
||||
if grab_result.GrabSucceeded():
|
||||
self.current_image = grab_result.Array
|
||||
self.display_original_image()
|
||||
self.apply_threshold_and_display()
|
||||
self.statusbar.showMessage("單張擷取成功")
|
||||
else:
|
||||
self.statusbar.showMessage("擷取失敗")
|
||||
|
||||
grab_result.Release()
|
||||
|
||||
except Exception as e:
|
||||
self.statusbar.showMessage(f"擷取失敗: {e}")
|
||||
if self.camera.IsGrabbing():
|
||||
self.camera.StopGrabbing()
|
||||
|
||||
def display_original_image(self):
|
||||
"""顯示原始影像到 label 上"""
|
||||
if self.current_image is not None:
|
||||
# 判斷是否需要轉換 Bayer 格式
|
||||
if len(self.current_image.shape) == 2 or self.current_image.shape[2] == 1:
|
||||
# 影像來自相機（Bayer 格式）
|
||||
image_bgr = cv2.cvtColor(self.current_image, cv2.COLOR_BayerBG2BGR)
|
||||
else:
|
||||
# 影像已經是 BGR 格式
|
||||
image_bgr = self.current_image
|
||||
|
||||
# 顯示影像
|
||||
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(self.label.size(), QtCore.Qt.KeepAspectRatio)
|
||||
self.label.setPixmap(pixmap)
|
||||
|
||||
def apply_threshold_and_display(self):
|
||||
"""套用二值化處理並顯示影像到 label_2 上"""
|
||||
if self.current_image is not None:
|
||||
# 判斷是否需要轉換 Bayer 格式
|
||||
if len(self.current_image.shape) == 2 or self.current_image.shape[2] == 1:
|
||||
# 影像來自相機（Bayer 格式）
|
||||
image_bgr = cv2.cvtColor(self.current_image, cv2.COLOR_BayerBG2BGR)
|
||||
else:
|
||||
# 影像已經是 BGR 格式
|
||||
image_bgr = self.current_image
|
||||
|
||||
# 轉換為灰階
|
||||
image_gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)
|
||||
|
||||
# 套用二值化處理
|
||||
threshold_value = self.threshold_value.value()
|
||||
_, thresholded_image = cv2.threshold(image_gray, threshold_value, 255, cv2.THRESH_BINARY)
|
||||
|
||||
# 顯示影像
|
||||
height, width = thresholded_image.shape
|
||||
bytes_per_line = width
|
||||
qimage = QtGui.QImage(thresholded_image.data, width, height, bytes_per_line, QtGui.QImage.Format_Grayscale8)
|
||||
pixmap = QtGui.QPixmap.fromImage(qimage).scaled(self.label_2.size(), QtCore.Qt.KeepAspectRatio)
|
||||
self.label_2.setPixmap(pixmap)
|
||||
|
||||
def update_threshold(self):
|
||||
"""當 QSlider 值改變時更新影像"""
|
||||
self.apply_threshold_and_display()
|
||||
# 更新 QTextEdit 顯示的值
|
||||
self.threshold.setText(str(self.threshold_value.value()))
|
||||
|
||||
def keep_shot_capture(self):
|
||||
if self.camera and self.camera.IsOpen():
|
||||
if not self.timer.isActive():
|
||||
self.camera.StartGrabbing(pylon.GrabStrategy_LatestImageOnly)
|
||||
self.timer.start(30)
|
||||
self.statusbar.showMessage("開始連續取像")
|
||||
else:
|
||||
self.timer.stop()
|
||||
self.camera.StopGrabbing()
|
||||
self.statusbar.showMessage("停止連續取像")
|
||||
else:
|
||||
self.statusbar.showMessage("請先連接相機")
|
||||
|
||||
def keep_shot_process(self):
|
||||
if self.camera and self.camera.IsGrabbing():
|
||||
grab_result = self.camera.RetrieveResult(5000, pylon.TimeoutHandling_ThrowException)
|
||||
if grab_result.GrabSucceeded():
|
||||
self.current_image = grab_result.Array
|
||||
self.display_original_image()
|
||||
self.apply_threshold_and_display()
|
||||
grab_result.Release()
|
||||
|
||||
def open_image(self):
|
||||
options = QFileDialog.Options()
|
||||
file_path, _ = QFileDialog.getOpenFileName(self, "打開影像檔", "", "Images (*.png *.xpm *.jpg *.bmp *.tiff)", options=options)
|
||||
|
||||
if file_path:
|
||||
if not os.path.exists(file_path):
|
||||
self.statusbar.showMessage("檔案不存在或路徑錯誤")
|
||||
return
|
||||
|
||||
image_data = np.fromfile(file_path, dtype=np.uint8)
|
||||
image = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
|
||||
|
||||
if image is not None:
|
||||
self.current_image = image
|
||||
self.display_original_image()
|
||||
self.apply_threshold_and_display()
|
||||
self.statusbar.showMessage("影像載入成功")
|
||||
else:
|
||||
self.statusbar.showMessage("無法讀取影像")
|
||||
def save_image(self):
|
||||
"""將二值化影像儲存到檔案"""
|
||||
if self.current_image is None:
|
||||
self.statusbar.showMessage("沒有影像可儲存")
|
||||
return
|
||||
|
||||
# 使用 QFileDialog 取得儲存檔案路徑和名稱
|
||||
file_path, _ = QFileDialog.getSaveFileName(self, "儲存二值化影像", "", "Images (*.png *.jpg *.bmp *.tiff)")
|
||||
|
||||
if file_path:
|
||||
try:
|
||||
# 取得 BGR 影像並生成二值化影像
|
||||
image_bgr = self.get_bgr_image()
|
||||
if image_bgr is None:
|
||||
self.statusbar.showMessage("無法取得影像")
|
||||
return
|
||||
|
||||
image_gray = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2GRAY)
|
||||
threshold_value = self.threshold_value.value()
|
||||
_, thresholded_image = cv2.threshold(image_gray, threshold_value, 255, cv2.THRESH_BINARY)
|
||||
|
||||
# 儲存影像
|
||||
cv2.imwrite(file_path, thresholded_image)
|
||||
self.statusbar.showMessage(f"二值化影像成功儲存到 {file_path}")
|
||||
|
||||
except Exception as e:
|
||||
self.statusbar.showMessage(f"影像儲存失敗: {e}")
|
||||
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
app = QtWidgets.QApplication(sys.argv)
|
||||
window = CameraApp()
|
||||
window.show()
|
||||
sys.exit(app.exec_())
|
||||
46
detection.py
46
detection.py
@ -1,6 +1,8 @@
|
||||
import sys
|
||||
import cv2
|
||||
import numpy as np
|
||||
import os
|
||||
import datetime
|
||||
import multiprocessing
|
||||
from PyQt5 import QtWidgets, QtGui, QtCore
|
||||
from PyQt5.QtCore import QTimer
|
||||
@ -10,6 +12,7 @@ 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):
|
||||
@ -41,6 +44,10 @@ class DetectionApp(QtWidgets.QMainWindow, Ui_MainWindow):
|
||||
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)
|
||||
@ -59,6 +66,9 @@ class DetectionApp(QtWidgets.QMainWindow, Ui_MainWindow):
|
||||
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)")
|
||||
self.bt_KeepShot.setEnabled(False)
|
||||
self.bt_StopKeepShot.setEnabled(True)
|
||||
self.bt_detection.setEnabled(True)
|
||||
else:
|
||||
print("相機已經在擷取")
|
||||
|
||||
@ -70,7 +80,9 @@ class DetectionApp(QtWidgets.QMainWindow, Ui_MainWindow):
|
||||
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
|
||||
|
||||
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:
|
||||
@ -98,31 +110,25 @@ class DetectionApp(QtWidgets.QMainWindow, Ui_MainWindow):
|
||||
self.log_handler.write_log(f"⚠️ 顯示影像時發生錯誤: {e}")
|
||||
|
||||
def detection(self):
|
||||
""" 使用 YOLO進行推論 """
|
||||
""" 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
|
||||
|
||||
if self.model is None:
|
||||
self.log_handler.write_log("⚠️ YOLO 模型未載入，無法執行推論")
|
||||
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...")
|
||||
|
||||
try:
|
||||
# ✅ 轉換影像格式 (BGR → RGB)
|
||||
image_rgb = cv2.cvtColor(self.latest_image, cv2.COLOR_BGR2RGB)
|
||||
|
||||
# ✅ 使用 YOLO 模型進行推論
|
||||
results = self.model.predict(image_rgb, imgsz=640, conf=0.5) # 影像大小 640, 置信度閾值 0.5
|
||||
self.log_handler.write_log("YOLO 推論完成")
|
||||
|
||||
# ✅ 取得標註結果
|
||||
result_image = results[0].plot() # `plot()` 會回傳畫出標註的影像
|
||||
|
||||
# ✅ 顯示結果
|
||||
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)
|
||||
|
||||
except Exception as e:
|
||||
self.log_handler.write_log(f"⚠️ 推論時發生錯誤: {e}")
|
||||
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(
|
||||
|
||||
@ -1,74 +0,0 @@
|
||||
import cv2
|
||||
import numpy as np
|
||||
import os
|
||||
from tkinter import Tk, filedialog
|
||||
|
||||
def select_image():
|
||||
Tk().withdraw() # 隱藏主視窗
|
||||
file_path = filedialog.askopenfilename(
|
||||
title="選擇影像檔案",
|
||||
filetypes=[("影像檔案", "*.png;*.jpg;*.jpeg;*.bmp")]
|
||||
)
|
||||
return file_path
|
||||
|
||||
def read_image_with_unicode_path(image_path):
|
||||
with open(image_path, 'rb') as file:
|
||||
binary_data = np.asarray(bytearray(file.read()), dtype=np.uint8)
|
||||
image = cv2.imdecode(binary_data, cv2.IMREAD_COLOR)
|
||||
return image
|
||||
|
||||
def save_image(output_path, image):
|
||||
# 儲存影像到指定路徑
|
||||
cv2.imwrite(output_path, image)
|
||||
print(f"影像已儲存至：{output_path}")
|
||||
|
||||
def detect_lines_with_hough(image):
|
||||
# 二值化處理
|
||||
_, binary_image = cv2.threshold(image, 68, 255, cv2.THRESH_BINARY)
|
||||
|
||||
# 儲存二值化影像
|
||||
binary_image_path = os.path.join(r"E:\AP", f"binary.png")
|
||||
save_image(binary_image_path, binary_image)
|
||||
|
||||
# 霍夫直線偵測
|
||||
lines = cv2.HoughLinesP(binary_image, 1, np.pi / 180, threshold=100, minLineLength=1300, maxLineGap=50)
|
||||
|
||||
# 在原影像上繪製直線
|
||||
line_image = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR) # 將灰階影像轉為 BGR 以繪製彩色直線
|
||||
if lines is not None:
|
||||
for line in lines:
|
||||
x1, y1, x2, y2 = line[0]
|
||||
cv2.line(line_image, (x1, y1), (x2, y2), (0, 0, 255), 2)
|
||||
|
||||
return line_image
|
||||
|
||||
def process_image(image_path):
|
||||
# 讀取影像
|
||||
image = read_image_with_unicode_path(image_path)
|
||||
|
||||
if image is None:
|
||||
print("無法讀取影像")
|
||||
return
|
||||
|
||||
# 轉換為灰階影像
|
||||
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
|
||||
|
||||
# 執行霍夫直線偵測（前處理為二值化）
|
||||
line_image = detect_lines_with_hough(gray_image)
|
||||
|
||||
# 取得輸出路徑
|
||||
directory = os.path.dirname(r"E:\AP\img0120")
|
||||
|
||||
gray_image_path = os.path.join(directory, f"gray.png")
|
||||
lines_image_path = os.path.join(directory, f"lines.png")
|
||||
|
||||
# 儲存影像
|
||||
save_image(gray_image_path, gray_image)
|
||||
save_image(lines_image_path, line_image)
|
||||
|
||||
if __name__ == "__main__":
|
||||
file_path = select_image()
|
||||
if file_path:
|
||||
process_image(file_path)
|
||||
else:
|
||||
print("未選擇影像檔案")
|
||||
@ -48,3 +48,14 @@
|
||||
[2025-03-10 21:32:21] YOLO 推論完成
|
||||
[2025-03-10 21:32:32] 相機停止
|
||||
[2025-03-10 21:32:33] 程式關閉
|
||||
[2025-03-10 21:37:06] 程式啟動
|
||||
[2025-03-10 21:37:06] YOLO 模型載入成功
|
||||
[2025-03-10 21:37:08] 相機啟動
|
||||
[2025-03-10 21:37:21] 相機停止
|
||||
[2025-03-10 21:37:21] 相機啟動
|
||||
[2025-03-10 21:37:29] 相機停止
|
||||
[2025-03-10 21:37:31] 相機啟動
|
||||
[2025-03-10 21:37:43] YOLO 推論完成
|
||||
[2025-03-10 21:37:43] ⚠️ 推論時發生錯誤: 'set' object has no attribute 'flush'
|
||||
[2025-03-10 21:38:15] 相機停止
|
||||
[2025-03-10 21:38:17] 程式關閉
|
||||
|
||||
60
predict.py
60
predict.py
@ -1,60 +0,0 @@
|
||||
from ultralytics import YOLO
|
||||
from tkinter import Tk, filedialog
|
||||
import cv2
|
||||
import numpy as np
|
||||
import os
|
||||
|
||||
# 載入模型
|
||||
model = YOLO('./runs/detect/train3/weights/best.pt')
|
||||
|
||||
# 設定輸出資料夾
|
||||
results_dir = "./results"
|
||||
os.makedirs(results_dir, exist_ok=True) # 確保結果資料夾存在
|
||||
|
||||
|
||||
# 使用 tkinter 開啟檔案選擇對話框
|
||||
def select_files():
|
||||
root = Tk()
|
||||
root.withdraw() # 隱藏主視窗
|
||||
file_paths = filedialog.askopenfilenames(
|
||||
title="Select Images",
|
||||
filetypes=[("Image files", "*.bmp;*.png;*.jpg;*.jpeg")]
|
||||
)
|
||||
return file_paths
|
||||
|
||||
|
||||
# 選擇影像檔案
|
||||
image_paths = select_files()
|
||||
if not image_paths:
|
||||
print("No files selected.")
|
||||
else:
|
||||
# 執行推論
|
||||
for image_path in image_paths:
|
||||
results = model(
|
||||
source=image_path, # 輸入圖片路徑
|
||||
save=True, # 儲存推論結果
|
||||
device='0', # 使用 GPU 若發生錯誤改成CPU
|
||||
conf=0.4 # 可以根據需要調整信心度開關
|
||||
)
|
||||
|
||||
# 傾向只顯示方框和信心度
|
||||
image = cv2.imread(image_path)
|
||||
for r in results:
|
||||
if r.boxes is not None:
|
||||
for box in r.boxes:
|
||||
if box.conf.item() > 0.4: # 過濾信心度
|
||||
x1, y1, x2, y2 = map(int, box.xyxy[0].tolist())
|
||||
confidence = box.conf.item()
|
||||
|
||||
# 顯示方框
|
||||
cv2.rectangle(image, (x1, y1), (x2, y2), (255, 0, 0), 2)
|
||||
cv2.putText(image, f'{confidence:.2f}', (x1, y1 - 10),
|
||||
cv2.FONT_HERSHEY_SIMPLEX, 2, (255, 0, 0), 2)
|
||||
|
||||
# 設定輸出路徑到 results 資料夾
|
||||
output_filename = os.path.basename(image_path).replace(".jpg", "_output.jpg").replace(".png", "_output.png")
|
||||
output_path = os.path.join(results_dir, output_filename)
|
||||
cv2.imwrite(output_path, image)
|
||||
print(f"Saved result to {output_path}")
|
||||
|
||||
print("Inference completed!")
|
||||
Loading…
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Reference in New Issue
Block a user