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main_en.py
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from PySide6.QtWidgets import QApplication, QMainWindow, QFileDialog, QMenu
from PySide6.QtGui import QImage, QPixmap, QColor
from PySide6.QtCore import QTimer, QThread, Signal, QObject, QPoint, Qt
from ui.CustomMessageBox import MessageBox
from ui.home import Ui_MainWindow
from UIFunctions import *
from core_en import YoloPredictor
from pathlib import Path
from utils.rtsp_win import Window
import traceback
import json
import sys
import cv2
import os
class MainWindow(QMainWindow, Ui_MainWindow):
main2yolo_begin_sgl = Signal() # Signal to send execution signal from main window to YOLO instance
def __init__(self, parent=None):
super(MainWindow, self).__init__(parent)
# Basic interface setup
self.setupUi(self)
self.setAttribute(Qt.WA_TranslucentBackground) # Rounded corners and transparency
self.setWindowFlags(Qt.FramelessWindowHint) # Set window flags: hide window border
UIFuncitons.uiDefinitions(self) # Custom interface definitions
# Initial page setup
self.task = ''
self.PageIndex = 1
self.content.setCurrentIndex(self.PageIndex)
self.pushButton_detect.clicked.connect(self.button_detect)
self.pushButton_pose.clicked.connect(self.button_pose)
self.pushButton_classify.clicked.connect(self.button_classify)
self.pushButton_segment.clicked.connect(self.button_segment)
self.pushButton_track.clicked.connect(self.button_track)
self.src_home_button.setEnabled(False)
self.src_file_button.setEnabled(False)
self.src_img_button.setEnabled(False)
self.src_cam_button.setEnabled(False)
self.src_rtsp_button.setEnabled(False)
self.src_home_button.clicked.connect(self.return_home)
#################################### Image or Video ####################################
# Display module shadow
UIFuncitons.shadow_style(self, self.Class_QF, QColor(162, 129, 247))
UIFuncitons.shadow_style(self, self.Target_QF, QColor(251, 157, 139))
UIFuncitons.shadow_style(self, self.Fps_QF, QColor(170, 128, 213))
UIFuncitons.shadow_style(self, self.Model_QF, QColor(64, 186, 193))
# YOLO-v8 thread
overrides = {'batch': 1} # Preset batch size (default 16)
self.yolo_predict = YoloPredictor(cfg=DEFAULT_CFG, overrides=overrides) # Create YOLO instance
self.select_model = self.model_box.currentText() # Default model
self.yolo_thread = QThread() # Create YOLO thread
self.yolo_predict.yolo2main_pre_img.connect(lambda x: self.show_image(x, self.pre_video, 'img'))
self.yolo_predict.yolo2main_res_img.connect(lambda x: self.show_image(x, self.res_video, 'img'))
self.yolo_predict.yolo2main_status_msg.connect(lambda x: self.show_status(x))
self.yolo_predict.yolo2main_fps.connect(lambda x: self.fps_label.setText(x))
self.yolo_predict.yolo2main_class_num.connect(lambda x: self.Class_num.setText(str(x)))
self.yolo_predict.yolo2main_target_num.connect(lambda x: self.Target_num.setText(str(x)))
self.yolo_predict.yolo2main_progress.connect(lambda x: self.progress_bar.setValue(x))
self.main2yolo_begin_sgl.connect(self.yolo_predict.run)
self.yolo_predict.moveToThread(self.yolo_thread)
self.Qtimer_ModelBox = QTimer(self) # Timer: monitor model file changes every 2 seconds
self.Qtimer_ModelBox.timeout.connect(self.ModelBoxRefre)
self.Qtimer_ModelBox.start(2000)
# Model parameters
self.model_box.currentTextChanged.connect(self.change_model)
self.iou_spinbox.valueChanged.connect(lambda x: self.change_val(x, 'iou_spinbox')) # IOU text box
self.iou_slider.valueChanged.connect(lambda x: self.change_val(x, 'iou_slider')) # IOU slider
self.conf_spinbox.valueChanged.connect(lambda x: self.change_val(x, 'conf_spinbox')) # Confidence text box
self.conf_slider.valueChanged.connect(lambda x: self.change_val(x, 'conf_slider')) # Confidence slider
self.speed_spinbox.valueChanged.connect(lambda x: self.change_val(x, 'speed_spinbox')) # Speed text box
self.speed_slider.valueChanged.connect(lambda x: self.change_val(x, 'speed_slider')) # Speed slider
# Initialize hint window
self.Class_num.setText('--')
self.Target_num.setText('--')
self.fps_label.setText('--')
self.Model_name.setText(self.select_model)
# Select folder source
self.src_file_button.clicked.connect(self.open_src_file) # Select local file
# Single file
self.src_img_button.clicked.connect(self.open_src_img) # Select local file
# Start test button
self.run_button.clicked.connect(self.run_or_continue) # Pause/Start
self.stop_button.clicked.connect(self.stop) # Stop
# Other function buttons
self.save_res_button.toggled.connect(self.is_save_res) # Save image option
self.save_txt_button.toggled.connect(self.is_save_txt) # Save label option
#################################### Image or Video ####################################
#################################### Camera ####################################
# Display cam module shadow
UIFuncitons.shadow_style(self, self.Class_QF_cam, QColor(162, 129, 247))
UIFuncitons.shadow_style(self, self.Target_QF_cam, QColor(251, 157, 139))
UIFuncitons.shadow_style(self, self.Fps_QF_cam, QColor(170, 128, 213))
UIFuncitons.shadow_style(self, self.Model_QF_cam, QColor(64, 186, 193))
# YOLO-v8-cam thread
overrides = {'batch': 1} # Preset batch size (default 16)
self.yolo_predict_cam = YoloPredictor(cfg=DEFAULT_CFG, overrides=overrides) # Create YOLO instance
self.select_model_cam = self.model_box_cam.currentText() # Default model
self.yolo_thread_cam = QThread() # Create YOLO thread
self.yolo_predict_cam.yolo2main_pre_img.connect(lambda c: self.cam_show_image(c, self.pre_cam))
self.yolo_predict_cam.yolo2main_res_img.connect(lambda c: self.cam_show_image(c, self.res_cam))
self.yolo_predict_cam.yolo2main_status_msg.connect(lambda c: self.show_status(c))
self.yolo_predict_cam.yolo2main_fps.connect(lambda c: self.fps_label_cam.setText(c))
self.yolo_predict_cam.yolo2main_class_num.connect(lambda c: self.Class_num_cam.setText(str(c)))
self.yolo_predict_cam.yolo2main_target_num.connect(lambda c: self.Target_num_cam.setText(str(c)))
self.yolo_predict_cam.yolo2main_progress.connect(self.progress_bar_cam.setValue(0))
self.main2yolo_begin_sgl.connect(self.yolo_predict_cam.run)
self.yolo_predict_cam.moveToThread(self.yolo_thread_cam)
self.Qtimer_ModelBox_cam = QTimer(self) # Timer: monitor model file changes every 2 seconds
self.Qtimer_ModelBox_cam.timeout.connect(self.ModelBoxRefre)
self.Qtimer_ModelBox_cam.start(2000)
# Cam model parameters
self.model_box_cam.currentTextChanged.connect(self.cam_change_model)
self.iou_spinbox_cam.valueChanged.connect(lambda c: self.cam_change_val(c, 'iou_spinbox_cam')) # IOU text box
self.iou_slider_cam.valueChanged.connect(lambda c: self.cam_change_val(c, 'iou_slider_cam')) # IOU slider
self.conf_spinbox_cam.valueChanged.connect(lambda c: self.cam_change_val(c, 'conf_spinbox_cam')) # Confidence text box
self.conf_slider_cam.valueChanged.connect(lambda c: self.cam_change_val(c, 'conf_slider_cam')) # Confidence slider
self.speed_spinbox_cam.valueChanged.connect(lambda c: self.cam_change_val(c, 'speed_spinbox_cam')) # Speed text box
self.speed_slider_cam.valueChanged.connect(lambda c: self.cam_change_val(c, 'speed_slider_cam')) # Speed slider
# Initialize hint window
self.Class_num_cam.setText('--')
self.Target_num_cam.setText('--')
self.fps_label_cam.setText('--')
self.Model_name_cam.setText(self.select_model_cam)
# Select detection source
self.src_cam_button.clicked.connect(self.cam_button) # Select camera
# Start test button
self.run_button_cam.clicked.connect(self.cam_run_or_continue) # Pause/Start
self.stop_button_cam.clicked.connect(self.cam_stop) # Stop
# Other function buttons
self.save_res_button_cam.toggled.connect(self.cam_is_save_res) # Save image option
self.save_txt_button_cam.toggled.connect(self.cam_is_save_txt) # Save label option
#################################### Camera ####################################
#################################### RTSP ####################################
self.src_rtsp_button.clicked.connect(self.rtsp_button)
#################################### RTSP ####################################
self.ToggleBotton.clicked.connect(lambda: UIFuncitons.toggleMenu(self, True)) # Left navigation button
# Initialization
self.load_config()
def return_home(self):
# 0: image/video page
# 1: home page
# 2: camera page
if self.PageIndex != 1:
self.PageIndex = 1
self.content.setCurrentIndex(1)
self.yolo_predict_cam.source = ''
self.src_home_button.setEnabled(False)
self.src_file_button.setEnabled(False)
self.src_img_button.setEnabled(False)
self.src_cam_button.setEnabled(False)
self.src_rtsp_button.setEnabled(False)
# Terminate thread if running
self.yolo_thread_cam.quit()
self.cam_stop()
self.yolo_thread.quit()
self.stop()
self.show_status("Welcome to the YOLOv8 detection system, please select Mode")
def button_classify(self):
self.task = 'Classify'
self.yolo_predict.task = self.task
self.yolo_predict_cam.task = self.task
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.src_home_button.setEnabled(True)
self.src_file_button.setEnabled(True)
self.src_img_button.setEnabled(True)
self.src_cam_button.setEnabled(True)
self.src_rtsp_button.setEnabled(True)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Load model directory
self.pt_list = os.listdir('./models/classify/')
self.pt_list = [file for file in self.pt_list if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list.sort(key=lambda x: os.path.getsize('./models/classify/' + x)) # Sort by file size
self.model_box.clear()
self.model_box.addItems(self.pt_list)
self.yolo_predict.new_model_name = "./models/classify/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/classify/%s" % self.select_model_cam
# Load camera model directory
self.pt_list_cam = os.listdir('./models/classify/')
self.pt_list_cam = [file for file in self.pt_list_cam if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list_cam.sort(key=lambda x: os.path.getsize('./models/classify/' + x)) # Sort by file size
self.model_box_cam.clear()
self.model_box_cam.addItems(self.pt_list_cam)
self.show_status("Current page: image or video detection page, Mode: Classify")
def button_detect(self):
self.task = 'Detect'
self.yolo_predict.task = self.task
self.yolo_predict_cam.task = self.task
self.yolo_predict.new_model_name = "./models/detect/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/detect/%s" % self.select_model_cam
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.src_home_button.setEnabled(True)
self.src_file_button.setEnabled(True)
self.src_img_button.setEnabled(True)
self.src_cam_button.setEnabled(True)
self.src_rtsp_button.setEnabled(True)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Load model directory
self.pt_list = os.listdir('./models/detect/')
self.pt_list = [file for file in self.pt_list if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list.sort(key=lambda x: os.path.getsize('./models/detect/' + x)) # Sort by file size
self.model_box.clear()
self.model_box.addItems(self.pt_list)
self.yolo_predict.new_model_name = "./models/detect/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/detect/%s" % self.select_model_cam
# Load camera model directory
self.pt_list_cam = os.listdir('./models/detect/')
self.pt_list_cam = [file for file in self.pt_list_cam if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list_cam.sort(key=lambda x: os.path.getsize('./models/detect/' + x)) # Sort by file size
self.model_box_cam.clear()
self.model_box_cam.addItems(self.pt_list_cam)
self.show_status("Current page: image or video detection page, Mode: Detect")
def button_pose(self):
self.task = 'Pose'
self.yolo_predict.task = self.task
self.yolo_predict_cam.task = self.task
self.yolo_predict.new_model_name = "./models/pose/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/pose/%s" % self.select_model_cam
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.src_home_button.setEnabled(True)
self.src_file_button.setEnabled(True)
self.src_img_button.setEnabled(True)
self.src_cam_button.setEnabled(True)
self.src_rtsp_button.setEnabled(True)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Load model directory
self.pt_list = os.listdir('./models/pose/')
self.pt_list = [file for file in self.pt_list if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list.sort(key=lambda x: os.path.getsize('./models/pose/' + x)) # Sort by file size
self.model_box.clear()
self.model_box.addItems(self.pt_list)
self.yolo_predict.new_model_name = "./models/pose/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/pose/%s" % self.select_model_cam
# Load camera model directory
self.pt_list_cam = os.listdir('./models/pose/')
self.pt_list_cam = [file for file in self.pt_list_cam if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list_cam.sort(key=lambda x: os.path.getsize('./models/pose/' + x)) # Sort by file size
self.model_box_cam.clear()
self.model_box_cam.addItems(self.pt_list_cam)
self.show_status("Current page: image or video detection page, Mode: Pose")
def button_segment(self):
self.task = 'Segment'
self.yolo_predict.task = self.task
self.yolo_predict_cam.task = self.task
self.yolo_predict.new_model_name = "./models/segment/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/segment/%s" % self.select_model_cam
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.src_home_button.setEnabled(True)
self.src_file_button.setEnabled(True)
self.src_img_button.setEnabled(True)
self.src_cam_button.setEnabled(True)
self.src_rtsp_button.setEnabled(True)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Load model directory
self.pt_list = os.listdir('./models/segment/')
self.pt_list = [file for file in self.pt_list if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list.sort(key=lambda x: os.path.getsize('./models/segment/' + x)) # Sort by file size
self.model_box.clear()
self.model_box.addItems(self.pt_list)
self.yolo_predict.new_model_name = "./models/segment/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/segment/%s" % self.select_model_cam
# Load camera model directory
self.pt_list_cam = os.listdir('./models/segment/')
self.pt_list_cam = [file for file in self.pt_list_cam if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list_cam.sort(key=lambda x: os.path.getsize('./models/segment/' + x)) # Sort by file size
self.model_box_cam.clear()
self.model_box_cam.addItems(self.pt_list_cam)
self.show_status("Current page: image or video detection page, Mode: Segment")
def button_track(self):
self.task = 'Track'
self.yolo_predict.task = self.task
self.yolo_predict_cam.task = self.task
self.yolo_predict.new_model_name = "./models/track/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/track/%s" % self.select_model_cam
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.src_home_button.setEnabled(True)
self.src_file_button.setEnabled(True)
self.src_img_button.setEnabled(True)
self.src_cam_button.setEnabled(True)
self.src_rtsp_button.setEnabled(True)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Load model directory
self.pt_list = os.listdir('./models/track/')
self.pt_list = [file for file in self.pt_list if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list.sort(key=lambda x: os.path.getsize('./models/track/' + x)) # Sort by file size
self.model_box.clear()
self.model_box.addItems(self.pt_list)
self.yolo_predict.new_model_name = "./models/track/%s" % self.select_model
self.yolo_predict_cam.new_model_name = "./models/track/%s" % self.select_model_cam
# Load camera model directory
self.pt_list_cam = os.listdir('./models/track/')
self.pt_list_cam = [file for file in self.pt_list_cam if file.endswith(('.pt', 'onnx', 'engine'))]
self.pt_list_cam.sort(key=lambda x: os.path.getsize('./models/track/' + x)) # Sort by file size
self.model_box_cam.clear()
self.model_box_cam.addItems(self.pt_list_cam)
self.show_status("Current page: image or video detection page, Mode: Track")
####################################image or video####################################
# Open local file
def open_src_file(self):
if self.task == 'Classify':
self.show_status("Current page: image or video detection page, Mode: Classify")
if self.task == 'Detect':
self.show_status("Current page: image or video detection page, Mode: Detect")
if self.task == 'Pose':
self.show_status("Current page: image or video detection page, Mode: Pose")
if self.task == 'Segment':
self.show_status("Current page: image or video detection page, Mode: Segment")
if self.task == 'Track':
self.show_status("Current page: image or video detection page, Mode: Track")
# Terminate cam thread to save resources
if self.yolo_thread_cam.isRunning():
self.yolo_thread_cam.quit()
self.cam_stop()
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Set the configuration file path
config_file = 'config/fold.json'
# Read the configuration file content
config = json.load(open(config_file, 'r', encoding='utf-8'))
# Get the last opened folder path
open_fold = config['open_fold']
# Use the current working directory if the last opened folder does not exist
if not os.path.exists(open_fold):
open_fold = os.getcwd()
FolderPath = QFileDialog.getExistingDirectory(self, 'Select your Folder', open_fold)
# If the user selects a file
if FolderPath:
FileFormat = [".jpg", ".png", ".jpeg", ".bmp", ".dib", ".jpe", ".jp2"]
Foldername = [(FolderPath + "/" + filename) for filename in os.listdir(FolderPath) for jpgname in FileFormat
if jpgname in filename]
if Foldername:
# Set the selected file path as the source for yolo_predict
self.yolo_predict.source = Foldername
# Display the folder load status
self.show_status('Load folder: {}'.format(os.path.dirname(FolderPath)))
# Update the last opened folder path in the configuration file
config['open_fold'] = os.path.dirname(FolderPath)
# Write the updated configuration file back to the file
config_json = json.dumps(config, ensure_ascii=False, indent=2)
with open(config_file, 'w', encoding='utf-8') as f:
f.write(config_json)
# Stop detection
self.stop()
else:
self.show_status('There are no pictures in the folder...')
# Open local file
def open_src_img(self):
if self.task == 'Classify':
self.show_status("Current page: image or video detection page, Mode: Classify")
if self.task == 'Detect':
self.show_status("Current page: image or video detection page, Mode: Detect")
if self.task == 'Pose':
self.show_status("Current page: image or video detection page, Mode: Pose")
if self.task == 'Segment':
self.show_status("Current page: image or video detection page, Mode: Segment")
if self.task == 'Track':
self.show_status("Current page: image or video detection page, Mode: Track")
# Terminate cam thread to save resources
if self.yolo_thread_cam.isRunning():
self.yolo_thread_cam.quit()
self.cam_stop()
if self.PageIndex != 0:
self.PageIndex = 0
self.content.setCurrentIndex(0)
self.settings_button.clicked.connect(lambda: UIFuncitons.settingBox(self, True)) # Top right settings button
# Set the configuration file path
config_file = 'config/fold.json'
# Read the configuration file content
config = json.load(open(config_file, 'r', encoding='utf-8'))
# Get the last opened folder path
open_fold = config['open_fold']
# Use the current working directory if the last opened folder does not exist
if not os.path.exists(open_fold):
open_fold = os.getcwd()
# Allow the user to select a picture or video file through a file dialog
if self.task == 'Track':
name, _ = QFileDialog.getOpenFileName(self, 'Video', open_fold, "Pic File(*.mp4 *.mkv *.avi *.flv)")
else:
name, _ = QFileDialog.getOpenFileName(self, 'Video/image', open_fold, "Pic File(*.mp4 *.mkv *.avi *.flv *.jpg *.png *.heic)")
# If the user selects a file
if name:
# Set the selected file path as the source for yolo_predict
self.yolo_predict.source = name
# Display the file load status
self.show_status('Load file: {}'.format(os.path.basename(name)))
# Update the last opened folder path in the configuration file
config['open_fold'] = os.path.dirname(name)
# Write the updated configuration file back to the file
config_json = json.dumps(config, ensure_ascii=False, indent=2)
with open(config_file, 'w', encoding='utf-8') as f:
f.write(config_json)
# Stop detection
self.stop()
# Display original image and detection result in main window
@staticmethod
def show_image(img_src, label, flag):
try:
if flag == "path":
img_src = cv2.imdecode(np.fromfile(img_src, dtype=np.uint8), -1)
# Get the height, width, and number of channels of the original image
ih, iw, _ = img_src.shape
# Get the width and height of the label
w = label.geometry().width()
h = label.geometry().height()
# Maintain the original data ratio
if iw / w > ih / h:
scal = w / iw
nw = w
nh = int(scal * ih)
img_src_ = cv2.resize(img_src, (nw, nh))
else:
scal = h / ih
nw = int(scal * iw)
nh = h
img_src_ = cv2.resize(img_src, (nw, nh))
# Convert the image to RGB format
frame = cv2.cvtColor(img_src_, cv2.COLOR_BGR2RGB)
# Convert the image data to a QPixmap object
img = QImage(frame.data, frame.shape[1], frame.shape[0], frame.shape[2] * frame.shape[1],
QImage.Format_RGB888)
# Display the image on the label
label.setPixmap(QPixmap.fromImage(img))
except Exception as e:
# Handle exceptions and print error messages
print(repr(e))
# Control start/pause of detection
def run_or_continue(self):
# Check if the source of YOLO prediction is empty
if self.yolo_predict.source == '':
self.show_status('Before starting detection, please select an image or video source...')
self.run_button.setChecked(False)
else:
# Set the stop flag of YOLO prediction to False
self.yolo_predict.stop_dtc = False
# If the start button is checked
if self.run_button.isChecked():
self.run_button.setChecked(True) # Activate button
self.save_txt_button.setEnabled(False) # Disable saving after detection starts
self.save_res_button.setEnabled(False)
self.show_status('Detecting...')
self.yolo_predict.continue_dtc = True # Control YOLO pause
if not self.yolo_thread.isRunning():
self.yolo_thread.start()
self.main2yolo_begin_sgl.emit()
# If the start button is not checked, it means pause detection
else:
self.yolo_predict.continue_dtc = False
self.show_status("Detection paused...")
self.run_button.setChecked(False) # Stop button
# Save test result button -- image/video
def is_save_res(self):
if self.save_res_button.checkState() == Qt.CheckState.Unchecked:
# Show message, indicating that image results will not be saved
self.show_status('NOTE: Image results will not be saved')
# Set the flag for saving results in the YOLO instance to False
self.yolo_predict.save_res = False
elif self.save_res_button.checkState() == Qt.CheckState.Checked:
# Show message, indicating that image results will be saved
self.show_status('NOTE: Image results will be saved')
# Set the flag for saving results in the YOLO instance to True
self.yolo_predict.save_res = True
# Save test result button -- label (txt)
def is_save_txt(self):
if self.save_txt_button.checkState() == Qt.CheckState.Unchecked:
# Show message, indicating that label results will not be saved
self.show_status('NOTE: Label results will not be saved')
# Set the flag for saving labels in the YOLO instance to False
self.yolo_predict.save_txt = False
elif self.save_txt_button.checkState() == Qt.CheckState.Checked:
# Show message, indicating that label results will be saved
self.show_status('NOTE: Label results will be saved')
# Set the flag for saving labels in the YOLO instance to True
self.yolo_predict.save_txt = True
# Terminate button and related state handling
def stop(self):
# If the YOLO thread is running, terminate the thread
if self.yolo_thread.isRunning():
self.yolo_thread.quit() # Terminate thread
# Set the termination flag of the YOLO instance to True
self.yolo_predict.stop_dtc = True
# Restore the status of the start button
self.run_button.setChecked(False)
self.save_res_button.setEnabled(True)
self.save_txt_button.setEnabled(True)
# Clear the image in the prediction result display area
self.pre_video.clear()
# Clear the image in the detection result display area
self.res_video.clear()
# Set the value of the progress bar to 0
self.progress_bar.setValue(0)
# Reset the class number, target number, and fps labels
self.Class_num.setText('--')
self.Target_num.setText('--')
self.fps_label.setText('--')
# Change detection parameters
def change_val(self, x, flag):
if flag == 'iou_spinbox':
# If the value of the iou_spinbox changes, change the value of the iou_slider
self.iou_slider.setValue(int(x * 100))
elif flag == 'iou_slider':
# If the value of the iou_slider changes, change the value of the iou_spinbox
self.iou_spinbox.setValue(x / 100)
# Show message, indicating IOU threshold change
self.show_status('IOU Threshold: %s' % str(x / 100))
# Set the IOU threshold of the YOLO instance
self.yolo_predict.iou_thres = x / 100
elif flag == 'conf_spinbox':
# If the value of the conf_spinbox changes, change the value of the conf_slider
self.conf_slider.setValue(int(x * 100))
elif flag == 'conf_slider':
# If the value of the conf_slider changes, change the value of the conf_spinbox
self.conf_spinbox.setValue(x / 100)
# Show message, indicating Confidence threshold change
self.show_status('Conf Threshold: %s' % str(x / 100))
# Set the Confidence threshold of the YOLO instance
self.yolo_predict.conf_thres = x / 100
elif flag == 'speed_spinbox':
# If the value of the speed_spinbox changes, change the value of the speed_slider
self.speed_slider.setValue(x)
elif flag == 'speed_slider':
# If the value of the speed_slider changes, change the value of the speed_spinbox
self.speed_spinbox.setValue(x)
# Show message, indicating delay time change
self.show_status('Delay: %s ms' % str(x))
# Set the delay time threshold of the YOLO instance
self.yolo_predict.speed_thres = x # milliseconds
# Change model
def change_model(self, x):
# Get the currently selected model name
self.select_model = self.model_box.currentText()
# Set the new model name of the YOLO instance
if self.task == 'Classify':
self.yolo_predict.new_model_name = "./models/classify/%s" % self.select_model
elif self.task == 'Detect':
self.yolo_predict.new_model_name = "./models/detect/%s" % self.select_model
elif self.task == 'Pose':
self.yolo_predict.new_model_name = "./models/pose/%s" % self.select_model
elif self.task == 'Segment':
self.yolo_predict.new_model_name = "./models/segment/%s" % self.select_model
elif self.task == 'Track':
self.yolo_predict.new_model_name = "./models/track/%s" % self.select_model
# Show message, indicating model has been changed
self.show_status('Change Model: %s' % self.select_model)
# Display the new model name on the interface
self.Model_name.setText(self.select_model)
####################################image or video####################################
####################################camera####################################
def cam_button(self):
self.yolo_predict_cam.source = 0
self.show_status('Current page: Webcam detection page')
# Terminate image or video thread to save resources
if self.yolo_thread.isRunning() or self.yolo_thread_cam.isRunning():
self.yolo_thread.quit()
self.yolo_thread_cam.quit()
self.stop()
self.cam_stop()
if self.PageIndex != 2:
self.PageIndex = 2
self.content.setCurrentIndex(2)
self.settings_button.clicked.connect(lambda: UIFuncitons.cam_settingBox(self, True)) # Top right settings button
# Control cam start/pause detection
def cam_run_or_continue(self):
if self.yolo_predict_cam.source == '':
self.show_status('Camera not detected')
self.run_button_cam.setChecked(False)
else:
# Set the stop flag for YOLO prediction to False
self.yolo_predict_cam.stop_dtc = False
# If the start button is checked
if self.run_button_cam.isChecked():
self.run_button_cam.setChecked(True) # Start button
self.save_txt_button_cam.setEnabled(False) # Disable save after detection starts
self.save_res_button_cam.setEnabled(False)
self.show_status('Detection in progress...')
self.yolo_predict_cam.continue_dtc = True # Control whether YOLO is paused
if not self.yolo_thread_cam.isRunning():
self.yolo_thread_cam.start()
self.main2yolo_begin_sgl.emit()
# If the start button is not checked, it means pause detection
else:
self.yolo_predict_cam.continue_dtc = False
self.show_status("Detection paused...")
self.run_button_cam.setChecked(False) # Stop button
# Display original image and detection results in the main cam window
@staticmethod
def cam_show_image(img_src, label, instance=None):
try:
# Get the height, width, and channels of the original image
ih, iw, _ = img_src.shape
# Get the width and height of the label
w = label.geometry().width()
h = label.geometry().height()
# Maintain the original data ratio
if iw / w > ih / h:
scal = w / iw
nw = w
nh = int(scal * ih)
img_src_ = cv2.resize(img_src, (nw, nh))
else:
scal = h / ih
nw = int(scal * iw)
nh = h
img_src_ = cv2.resize(img_src, (nw, nh))
# Convert the image to RGB format
frame = cv2.cvtColor(img_src_, cv2.COLOR_BGR2RGB)
# Convert the image data to a QPixmap object
img = QImage(frame.data, frame.shape[1], frame.shape[0], frame.shape[2] * frame.shape[1],
QImage.Format_RGB888)
# Display the image on the label
label.setPixmap(QPixmap.fromImage(img))
except Exception as e:
# Handle exceptions, print error messages
traceback.print_exc()
print(f"Error: {e}")
if instance is not None:
instance.show_status('%s' % e)
# Change detection parameters
def cam_change_val(self, c, flag):
if flag == 'iou_spinbox_cam':
# If the value of iou_spinbox changes, change the value of iou_slider
self.iou_slider_cam.setValue(int(c * 100))
elif flag == 'iou_slider_cam':
# If the value of iou_slider changes, change the value of iou_spinbox
self.iou_spinbox_cam.setValue(c / 100)
# Display message indicating IOU threshold change
self.show_status('IOU Threshold: %s' % str(c / 100))
# Set the IOU threshold for the YOLO instance
self.yolo_predict_cam.iou_thres = c / 100
elif flag == 'conf_spinbox_cam':
# If the value of conf_spinbox changes, change the value of conf_slider
self.conf_slider_cam.setValue(int(c * 100))
elif flag == 'conf_slider_cam':
# If the value of conf_slider changes, change the value of conf_spinbox
self.conf_spinbox_cam.setValue(c / 100)
# Display message indicating confidence threshold change
self.show_status('Conf Threshold: %s' % str(c / 100))
# Set the confidence threshold for the YOLO instance
self.yolo_predict_cam.conf_thres = c / 100
elif flag == 'speed_spinbox_cam':
# If the value of speed_spinbox changes, change the value of speed_slider
self.speed_slider_cam.setValue(c)
elif flag == 'speed_slider_cam':
# If the value of speed_slider changes, change the value of speed_spinbox
self.speed_spinbox_cam.setValue(c)
# Display message indicating delay time change
self.show_status('Delay: %s ms' % str(c))
# Set the delay time threshold for the YOLO instance
self.yolo_predict_cam.speed_thres = c # milliseconds
# Change model
def cam_change_model(self, c):
# Get the currently selected model name
self.select_model_cam = self.model_box_cam.currentText()
# Set the new model name for the YOLO instance
if self.task == 'Classify':
self.yolo_predict_cam.new_model_name = "./models/classify/%s" % self.select_model_cam
elif self.task == 'Detect':
self.yolo_predict_cam.new_model_name = "./models/detect/%s" % self.select_model_cam
elif self.task == 'Pose':
self.yolo_predict_cam.new_model_name = "./models/pose/%s" % self.select_model_cam
elif self.task == 'Segment':
self.yolo_predict_cam.new_model_name = "./models/segment/%s" % self.select_model_cam
elif self.task == 'Track':
self.yolo_predict_cam.new_model_name = "./models/track/%s" % self.select_model_cam
# Display message indicating the model has changed
self.show_status('Change Model：%s' % self.select_model_cam)
# Display the new model name on the interface
self.Model_name_cam.setText(self.select_model_cam)
# Save test result button -- image/video
def cam_is_save_res(self):
if self.save_res_button_cam.checkState() == Qt.CheckState.Unchecked:
# Display message, indicating that webcam results will not be saved
self.show_status('NOTE: Webcam results will not be saved')
# Set the flag for saving results in the YOLO instance to False
self.yolo_thread_cam.save_res = False
elif self.save_res_button_cam.checkState() == Qt.CheckState.Checked:
# Display message, indicating that webcam results will be saved
self.show_status('NOTE: Webcam results will be saved')
# Set the flag for saving results in the YOLO instance to True
self.yolo_thread_cam.save_res = True
# Save test result button -- label (txt)
def cam_is_save_txt(self):
if self.save_txt_button_cam.checkState() == Qt.CheckState.Unchecked:
# Display message, indicating that label results will not be saved
self.show_status('NOTE: Label results will not be saved')
# Set the flag for saving labels in the YOLO instance to False
self.yolo_thread_cam.save_txt_cam = False
elif self.save_txt_button_cam.checkState() == Qt.CheckState.Checked:
# Display message, indicating that label results will be saved
self.show_status('NOTE: Label results will be saved')
# Set the flag for saving labels in the YOLO instance to True
self.yolo_thread_cam.save_txt_cam = True
# Stop cam button and related state processing
def cam_stop(self):
# If the YOLO thread is running, terminate the thread
if self.yolo_thread_cam.isRunning():
self.yolo_thread_cam.quit() # Terminate thread
# Set the termination flag in the YOLO instance to True
self.yolo_predict_cam.stop_dtc = True
# Restore the status of the run button
self.run_button_cam.setChecked(False)
# Enable save button permissions
if self.task == 'Classify':
self.save_res_button_cam.setEnabled(False)
self.save_txt_button_cam.setEnabled(False)
else:
self.save_res_button_cam.setEnabled(True)
self.save_txt_button_cam.setEnabled(True)
# Clear the predicted result display area image
self.pre_cam.clear()
# Clear the detection result display area image
self.res_cam.clear()
# Reset the progress bar value
# self.progress_bar.setValue(0)
# Reset the class number, target number, and fps labels
self.Class_num_cam.setText('--')
self.Target_num_cam.setText('--')
self.fps_label_cam.setText('--')
####################################camera####################################
####################################rtsp####################################
# RTSP input address
def rtsp_button(self):
# Terminate image or video thread to save resources
if self.yolo_thread.isRunning() or self.yolo_thread_cam.isRunning():
self.yolo_thread.quit() # Terminate thread
self.yolo_thread_cam.quit()
self.stop()
self.cam_stop()
self.content.setCurrentIndex(2)
self.show_status('Current page: RTSP detection page')
self.rtsp_window = Window()
config_file = 'config/ip.json'
if not os.path.exists(config_file):
ip = "rtsp://admin:[email protected]:555"
new_config = {"ip": ip}
new_json = json.dumps(new_config, ensure_ascii=False, indent=2)
with open(config_file, 'w', encoding='utf-8') as f:
f.write(new_json)
else:
config = json.load(open(config_file, 'r', encoding='utf-8'))
ip = config['ip']
self.rtsp_window.rtspEdit.setText(ip)
self.rtsp_window.show()
self.rtsp_window.rtspButton.clicked.connect(lambda: self.load_rtsp(self.rtsp_window.rtspEdit.text()))
self.settings_button.clicked.connect(lambda: UIFuncitons.cam_settingBox(self, True)) # Top right settings button
# Load network source
def load_rtsp(self, ip):
try:
self.stop()
MessageBox(
self.close_button, title='NOTE', text='Loading RTSP...', time=1000, auto=True).exec()
self.yolo_predict_cam.source = ip
new_config = {"ip": ip}
new_json = json.dumps(new_config, ensure_ascii=False, indent=2)
with open('config/ip.json', 'w', encoding='utf-8') as f:
f.write(new_json)
self.show_status('Loaded RTSP: {}'.format(ip))
self.rtsp_window.close()
except Exception as e:
self.show_status('%s' % e)
####################################rtsp####################################
####################################common####################################
# Display information in the bottom status bar
def show_status(self, msg):
self.status_bar.setText(msg)
def handle_page_0():
if msg == 'Detection completed!':
self.save_res_button.setEnabled(True)
self.save_txt_button.setEnabled(True)
self.run_button.setChecked(False)
if self.yolo_thread.isRunning():
self.yolo_thread.quit()
elif msg == 'Detection terminated!':
self.save_res_button.setEnabled(True)
self.save_txt_button.setEnabled(True)
self.run_button.setChecked(False)
self.progress_bar.setValue(0)
if self.yolo_thread.isRunning():
self.yolo_thread.quit()
self.pre_video.clear()
self.res_video.clear()
self.Class_num.setText('--')
self.Target_num.setText('--')
self.fps_label.setText('--')
def handle_page_2():
if msg == 'Detection terminated!':
self.save_res_button_cam.setEnabled(True)
self.save_txt_button_cam.setEnabled(True)
self.run_button_cam.setChecked(False)
self.progress_bar_cam.setValue(0)
if self.yolo_thread_cam.isRunning():
self.yolo_thread_cam.quit()
self.pre_cam.clear()
self.res_cam.clear()
self.Class_num_cam.setText('--')
self.Target_num_cam.setText('--')
self.fps_label_cam.setText('--')
if self.PageIndex == 0:
handle_page_0()
elif self.PageIndex == 2:
handle_page_2()
# Monitor model file changes in a loop
def ModelBoxRefre(self):
# Get all model files in the model folder
if self.task == 'Classify':
pt_list = os.listdir('./models/classify')
pt_list = [file for file in pt_list if file.endswith(('.pt', 'onnx', 'engine'))]
pt_list.sort(key=lambda x: os.path.getsize('./models/classify/' + x))
# If the model file list changes, update the model dropdown content
if pt_list != self.pt_list:
self.pt_list = pt_list
self.model_box.clear()
self.model_box.addItems(self.pt_list)
self.pt_list_cam = pt_list
self.model_box_cam.clear()
self.model_box_cam.addItems(self.pt_list_cam)
# Repeat the same process for other tasks ('Detect', 'Pose', 'Segment', 'Track')
# Get the mouse position (for dragging the window by holding the title bar)
def mousePressEvent(self, event):
p = event.globalPosition()
globalPos = p.toPoint()
self.dragPos = globalPos
# Optimize adjustments when resizing the window (for resizing by dragging the bottom right corner)
def resizeEvent(self, event):
# Update the resize grip
UIFuncitons.resize_grips(self)
# Configuration initialization
def load_config(self):
config_file = 'config/setting.json'
# If the configuration file does not exist, create it and write default settings
if not os.path.exists(config_file):
iou = 0.26
conf = 0.33
rate = 10
save_res = 0
save_txt = 0
save_res_cam = 0
save_txt_cam = 0
new_config = {"iou": iou,
"conf": conf,
"rate": rate,
"save_res": save_res,