Update borealis_overlay.py
This commit is contained in:
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943967be60
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@ -1,21 +1,92 @@
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#!/usr/bin/env python3
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"""
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Project Borealis (Fixed Progress Bar)
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=====================================
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• Uses Tesseract OCR only, storing up to 7 data points.
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• Rollover logic (reset if new < old).
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• Skips duplicates.
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• Shows a Rich table of historical data (2+ points).
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• Then displays a Rich progress bar for the current EXP, plus predicted time to level
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in hours/min/seconds if over 60 minutes.
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Key fix: we use "with Progress(...) as progress:" *without* transient,
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so the bar remains in the console after the update.
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"""
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import sys
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import os
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import time
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import re
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import pytesseract
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import easyocr
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import numpy as np
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from PyQt5.QtWidgets import QApplication, QWidget, QLabel, QCheckBox, QTextEdit, QComboBox, QVBoxLayout
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from PyQt5.QtWidgets import QApplication, QWidget
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from PyQt5.QtCore import Qt, QRect, QPoint, QTimer
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from PyQt5.QtGui import QPainter, QPen, QColor, QFont
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from PIL import Image, ImageGrab, ImageEnhance, ImageFilter # For screen capture and image processing
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from PIL import Image, ImageGrab, ImageEnhance, ImageFilter
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HANDLE_SIZE = 10 # Size of the resize handle squares
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LABEL_HEIGHT = 20 # Height of the label area above the rectangle
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DEFAULT_WIDTH = 150 # Default width for the regions
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DEFAULT_HEIGHT = 50 # Default height for the regions
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DEFAULT_SPACING = 20 # Default horizontal spacing between regions
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from rich.console import Console
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from rich.table import Table
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from rich.progress import Progress, BarColumn, TextColumn
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# Set the path for tesseract manually
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# ---------------- [ Global Config ] ----------------
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pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"
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OCR_ENGINE = "Tesseract" # Hard-coded since we removed EasyOCR
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POLLING_RATE_MS = 1000
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MAX_DATA_POINTS = 7
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GREEN_HEADER_STYLE = "bold green"
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HANDLE_SIZE = 10
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LABEL_HEIGHT = 20
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DEFAULT_WIDTH = 150
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DEFAULT_HEIGHT = 50
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def sanitize_experience_string(raw_text):
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"""Extract a float from raw OCR text, removing extraneous symbols."""
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text_no_percent = raw_text.replace('%', '')
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text_no_spaces = text_no_percent.replace(' ', '')
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cleaned = re.sub(r'[^0-9\.]', '', text_no_spaces)
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match = re.search(r'\d+(?:\.\d+)?', cleaned)
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if not match:
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return None
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val = float(match.group(0))
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return round(val, 4)
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def format_experience_value(value):
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"""Format float to 'XX.XXXX' with leading zeros if needed."""
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if value < 0:
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value = 0
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elif value > 100:
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value = 100
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float_4 = round(value, 4)
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raw_str = f"{float_4:.4f}"
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int_part, dec_part = raw_str.split('.')
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if int_part == "100":
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pass
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elif len(int_part) == 1 and int_part != "0":
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int_part = "0" + int_part
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elif int_part == "0":
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int_part = "00"
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return f"{int_part}.{dec_part}"
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def format_duration(seconds):
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"""
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Convert total seconds into hours / min / sec:
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- If hours > 0 => "Xh Ym Zs"
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- Otherwise => "Xm Ys"
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"""
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seconds = int(seconds)
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hours = seconds // 3600
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leftover = seconds % 3600
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mins = leftover // 60
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secs = leftover % 60
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if hours > 0:
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return f"{hours}h {mins}m {secs}s"
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else:
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return f"{mins}m {secs}s"
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class Region:
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def __init__(self, x, y, label="Region", color=QColor(0, 0, 255)):
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@ -25,81 +96,68 @@ class Region:
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self.h = DEFAULT_HEIGHT
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self.label = label
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self.color = color
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self.visible = True # Track the visibility of the region
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self.data = "" # Store OCR data for this region
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self.visible = True
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self.data = ""
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def rect(self):
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return QRect(self.x, self.y, self.w, self.h)
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def label_rect(self):
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"""The rectangle representing the label area."""
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return QRect(self.x, self.y - LABEL_HEIGHT, self.w, LABEL_HEIGHT)
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def resize_handles(self):
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"""Calculate the positions of the resize handles."""
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return [
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QRect(self.x - HANDLE_SIZE // 2, self.y - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE), # Top-left
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QRect(self.x + self.w - HANDLE_SIZE // 2, self.y - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE), # Top-right
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QRect(self.x - HANDLE_SIZE // 2, self.y + self.h - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE), # Bottom-left
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QRect(self.x + self.w - HANDLE_SIZE // 2, self.y + self.h - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE), # Bottom-right
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QRect(self.x - HANDLE_SIZE // 2, self.y - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE),
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QRect(self.x + self.w - HANDLE_SIZE // 2, self.y - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE),
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QRect(self.x - HANDLE_SIZE // 2, self.y + self.h - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE),
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QRect(self.x + self.w - HANDLE_SIZE // 2, self.y + self.h - HANDLE_SIZE // 2, HANDLE_SIZE, HANDLE_SIZE),
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]
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class OverlayCanvas(QWidget):
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"""
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A canvas to draw, resize, and interact with rectangular regions.
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"""
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def __init__(self, regions, parent=None):
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super().__init__(parent)
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self.regions = regions
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self.edit_mode = False
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self.edit_mode = True
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self.selected_region = None
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self.selected_handle = None # Track which handle is being dragged
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self.selected_handle = None
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self.drag_offset = QPoint()
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def paintEvent(self, event):
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painter = QPainter(self)
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painter.setRenderHint(QPainter.Antialiasing)
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for region in self.regions:
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if region.visible: # Only draw visible regions
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# Draw the rectangle
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if region.visible:
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pen = QPen(region.color)
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pen.setWidth(3)
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painter.setPen(pen)
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painter.drawRect(region.x, region.y, region.w, region.h)
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# Draw the label above the rectangle, aligned with the left edge of the region
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painter.setFont(QFont("Arial", 12, QFont.Bold))
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painter.setPen(region.color)
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painter.drawText(region.x, region.y - 5, region.label) # Aligned to the left of the region
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painter.drawText(region.x, region.y - 5, region.label)
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# Draw resize handles if in edit mode
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if self.edit_mode:
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for handle in region.resize_handles():
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painter.fillRect(handle, region.color)
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def mousePressEvent(self, event):
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if not self.edit_mode:
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return # Ignore clicks if not in edit mode
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return
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if event.button() == Qt.LeftButton:
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for region in reversed(self.regions): # Check regions from topmost to bottommost
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# Check if a resize handle is clicked
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for region in reversed(self.regions):
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# Check handles
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for i, handle in enumerate(region.resize_handles()):
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if handle.contains(event.pos()):
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self.selected_region = region
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self.selected_handle = i
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return
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# Check if the label area is clicked (for dragging)
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# Check label or rect
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if region.label_rect().contains(event.pos()):
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self.selected_region = region
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self.selected_handle = None # No resize handle, just dragging the rectangle
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self.selected_handle = None
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self.drag_offset = event.pos() - QPoint(region.x, region.y)
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return
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# Check if the main rectangle is clicked (fallback for dragging)
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if region.rect().contains(event.pos()):
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self.selected_region = region
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self.selected_handle = None
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@ -111,274 +169,209 @@ class OverlayCanvas(QWidget):
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return
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if self.selected_handle is None:
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# Dragging the entire rectangle
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# Drag rectangle
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self.selected_region.x = event.x() - self.drag_offset.x()
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self.selected_region.y = event.y() - self.drag_offset.y()
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else:
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# Resizing the rectangle
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# Resize
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sr = self.selected_region
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if self.selected_handle == 0: # Top-left
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self.selected_region.w += self.selected_region.x - event.x()
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self.selected_region.h += self.selected_region.y - event.y()
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self.selected_region.x = event.x()
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self.selected_region.y = event.y()
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sr.w += sr.x - event.x()
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sr.h += sr.y - event.y()
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sr.x = event.x()
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sr.y = event.y()
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elif self.selected_handle == 1: # Top-right
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self.selected_region.w = event.x() - self.selected_region.x
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self.selected_region.h += self.selected_region.y - event.y()
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self.selected_region.y = event.y()
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sr.w = event.x() - sr.x
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sr.h += sr.y - event.y()
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sr.y = event.y()
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elif self.selected_handle == 2: # Bottom-left
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self.selected_region.w += self.selected_region.x - event.x()
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self.selected_region.h = event.y() - self.selected_region.y
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self.selected_region.x = event.x()
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sr.w += sr.x - event.x()
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sr.h = event.y() - sr.y
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sr.x = event.x()
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elif self.selected_handle == 3: # Bottom-right
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self.selected_region.w = event.x() - self.selected_region.x
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self.selected_region.h = event.y() - self.selected_region.y
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sr.w = event.x() - sr.x
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sr.h = event.y() - sr.y
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# Prevent negative width/height
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self.selected_region.w = max(self.selected_region.w, 10)
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self.selected_region.h = max(self.selected_region.h, 10)
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self.update() # Trigger a repaint
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sr.w = max(sr.w, 10)
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sr.h = max(sr.h, 10)
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self.update()
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def mouseReleaseEvent(self, event):
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if not self.edit_mode:
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return
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if event.button() == Qt.LeftButton:
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self.selected_region = None
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self.selected_handle = None # Deselect handle
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self.selected_handle = None
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class BorealisOverlay(QWidget):
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"""
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Project Borealis with Tesseract + Rich table + Rich progress bar,
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properly displayed with "with Progress(...) as progress".
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"""
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def __init__(self):
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super().__init__()
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# Set window properties to cover the full screen
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# Fullscreen overlay
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screen_geometry = QApplication.primaryScreen().geometry()
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self.setGeometry(screen_geometry)
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self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
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self.setAttribute(Qt.WA_TranslucentBackground, True) # Transparent background
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self.setAttribute(Qt.WA_TranslucentBackground, True)
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# Create regions to draw and interact with, all regions have the same size and are moved higher up
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self.regions = [
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Region(250, 50, label="Experience"), # Moved slightly to the right
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Region(450, 50, label="Region 02"), # Moved slightly to the right
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Region(650, 50, label="Region 03") # Moved slightly to the right
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Region(250, 50, label="Experience"),
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]
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# Create canvas and attach to window
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self.canvas = OverlayCanvas(self.regions, self)
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self.canvas.setGeometry(self.rect()) # Match the canvas size to the full window
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self.canvas.setGeometry(self.rect())
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# Add title, Edit Mode UI, and buttons (Overlay Visibility checkbox)
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self.init_ui()
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# Tesseract
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self.engine = pytesseract
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# Timer for polling OCR data
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self.points = []
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self.timer = QTimer(self)
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self.timer.timeout.connect(self.collect_ocr_data)
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self.timer.start(1000) # Poll every second (default)
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self.reader = None # Default OCR reader (None until an engine is selected)
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def init_ui(self):
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"""Initialize UI components."""
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# Title label
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self.title_label = QLabel("Borealis Overlay", self)
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self.title_label.setStyleSheet("QLabel { color: white; font-size: 20px; font-weight: bold; }") # Adjusted title size
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self.title_label.move(10, 5)
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# OCR Engine label and selection dropdown
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self.engine_label = QLabel("OCR Engine:", self)
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self.engine_label.setStyleSheet("QLabel { color: white; font-size: 14px; }")
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self.engine_label.move(10, 60) # Moved OCR Engine label slightly higher
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self.engine_dropdown = QComboBox(self)
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self.engine_dropdown.setStyleSheet("""
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QComboBox {
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color: white;
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background-color: #2b2b2b;
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border: 1px solid #3c3f41;
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font-size: 14px;
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}
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QComboBox QAbstractItemView {
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color: white;
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background-color: #2b2b2b;
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}
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""")
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self.engine_dropdown.addItem("Select OCR Engine") # Placeholder option
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self.engine_dropdown.addItem("Tesseract") # Only Tesseract for now
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self.engine_dropdown.addItem("EasyOCR") # Adding EasyOCR option
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self.engine_dropdown.move(100, 90) # Dropdown moved slightly up and aligned with label
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self.engine_dropdown.currentIndexChanged.connect(self.on_engine_selected)
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# Polling rate dropdown
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self.polling_rate_label = QLabel("Polling Rate:", self)
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self.polling_rate_label.setStyleSheet("QLabel { color: white; font-size: 14px; }")
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self.polling_rate_label.move(10, 120)
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self.polling_rate_dropdown = QComboBox(self)
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self.polling_rate_dropdown.setStyleSheet("""
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QComboBox {
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color: white;
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background-color: #2b2b2b;
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border: 1px solid #3c3f41;
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font-size: 14px;
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}
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QComboBox QAbstractItemView {
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color: white;
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background-color: #2b2b2b;
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}
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""")
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self.polling_rate_dropdown.addItem("0.1 Seconds")
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self.polling_rate_dropdown.addItem("0.5 Seconds")
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self.polling_rate_dropdown.addItem("1 Second")
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self.polling_rate_dropdown.addItem("2 Seconds")
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self.polling_rate_dropdown.addItem("5 Seconds")
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self.polling_rate_dropdown.move(100, 150) # Dropdown moved slightly up
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self.polling_rate_dropdown.currentIndexChanged.connect(self.on_polling_rate_selected)
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# Options label
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self.options_label = QLabel("Options", self)
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self.options_label.setStyleSheet("QLabel { color: white; font-size: 16px; font-weight: bold; }")
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self.options_label.move(10, 180) # Positioned above checkboxes
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# Edit mode checkbox
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self.mode_toggle = QCheckBox("Edit Mode", self)
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self.mode_toggle.setStyleSheet("QCheckBox { color: white; }")
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self.mode_toggle.move(10, 210)
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self.mode_toggle.stateChanged.connect(self.toggle_edit_mode)
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# Overlay Visibility checkbox
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self.visibility_checkbox = QCheckBox("Overlay Visibility", self)
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self.visibility_checkbox.setStyleSheet("QCheckBox { color: white; }")
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self.visibility_checkbox.move(10, 240) # Positioned below Edit Mode
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self.visibility_checkbox.setChecked(True) # Default to visible
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self.visibility_checkbox.stateChanged.connect(self.toggle_overlay_visibility)
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# Collect Data checkbox for OCR functionality (disabled initially)
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self.collect_data_checkbox = QCheckBox("Collect Data", self)
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self.collect_data_checkbox.setStyleSheet("QCheckBox { color: white; }")
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self.collect_data_checkbox.move(10, 270) # Positioned below Overlay Visibility
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self.collect_data_checkbox.setEnabled(False) # Initially disabled
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self.collect_data_checkbox.stateChanged.connect(self.toggle_ocr)
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# Data Collection Output label
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self.output_label = QLabel("Data Collection Output:", self)
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self.output_label.setStyleSheet("QLabel { color: white; font-size: 14px; font-weight: bold; }")
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self.output_label.move(10, 330) # Moved down by 50px
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# Text area for OCR data display (with transparent background)
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self.ocr_display = QTextEdit(self)
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self.ocr_display.setStyleSheet("QTextEdit { color: white; background-color: transparent; font-size: 14px; }")
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self.ocr_display.setReadOnly(True)
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self.ocr_display.setGeometry(10, 360, 300, 400)
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def on_engine_selected(self):
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"""Enable the Collect Data checkbox when an OCR engine is selected."""
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selected_engine = self.engine_dropdown.currentText()
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if selected_engine == "Tesseract":
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self.reader = pytesseract
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elif selected_engine == "EasyOCR":
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self.reader = easyocr.Reader(['en']) # Initialize EasyOCR reader for English language
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elif selected_engine == "Select OCR Engine":
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self.reader = None
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if self.reader:
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self.collect_data_checkbox.setEnabled(True)
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else:
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self.collect_data_checkbox.setEnabled(False)
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def on_polling_rate_selected(self):
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"""Update the polling rate based on dropdown selection."""
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polling_rate = self.polling_rate_dropdown.currentText()
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if polling_rate == "0.1 Seconds":
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self.timer.setInterval(100)
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elif polling_rate == "0.5 Seconds":
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self.timer.setInterval(500)
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elif polling_rate == "1 Second":
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self.timer.setInterval(1000)
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elif polling_rate == "2 Seconds":
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self.timer.setInterval(2000)
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elif polling_rate == "5 Seconds":
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self.timer.setInterval(5000)
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def toggle_edit_mode(self, state):
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"""Enable or disable edit mode for dragging and resizing rectangles."""
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editing = (state == 2)
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||||
self.canvas.edit_mode = editing # Pass the state to the canvas
|
||||
|
||||
def toggle_overlay_visibility(self):
|
||||
"""Toggle the visibility of the regions."""
|
||||
visible = self.visibility_checkbox.isChecked()
|
||||
for region in self.regions:
|
||||
region.visible = visible # Toggle visibility based on checkbox
|
||||
self.update() # Trigger a repaint
|
||||
|
||||
def toggle_ocr(self, state):
|
||||
"""Enable or disable OCR collection."""
|
||||
if state == Qt.Checked:
|
||||
self.collect_ocr_data()
|
||||
else:
|
||||
self.clear_ocr_data()
|
||||
self.timer.start(POLLING_RATE_MS)
|
||||
|
||||
def collect_ocr_data(self):
|
||||
"""Collect OCR data from each visible region."""
|
||||
if self.collect_data_checkbox.isChecked() and self.reader: # Only collect data if checkbox is checked
|
||||
if not self.engine:
|
||||
return
|
||||
|
||||
for region in self.regions:
|
||||
if region.visible:
|
||||
# Capture the image of the region
|
||||
screenshot = ImageGrab.grab(bbox=(region.x, region.y, region.x + region.w, region.y + region.h))
|
||||
|
||||
# Preprocess the image (Convert to grayscale and apply threshold)
|
||||
screenshot = ImageGrab.grab(
|
||||
bbox=(region.x, region.y, region.x + region.w, region.y + region.h)
|
||||
)
|
||||
processed_image = self.preprocess_image(screenshot)
|
||||
|
||||
# Convert the processed image to a numpy array for EasyOCR
|
||||
numpy_image = np.array(processed_image)
|
||||
|
||||
# Perform OCR on the preprocessed numpy image
|
||||
if self.reader == pytesseract:
|
||||
text = pytesseract.image_to_string(processed_image, config='--psm 6 --oem 1')
|
||||
else:
|
||||
# Get text from EasyOCR
|
||||
results = self.reader.readtext(numpy_image)
|
||||
|
||||
if results:
|
||||
text = results[0][1] # If OCR detects text, use it
|
||||
else:
|
||||
text = "No text detected" # Fallback if no text is detected
|
||||
|
||||
region.data = text.strip()
|
||||
|
||||
self.display_ocr_data()
|
||||
if region.label.lower() == "experience":
|
||||
val = sanitize_experience_string(region.data)
|
||||
if val is not None:
|
||||
self.update_points(val)
|
||||
region.data = format_experience_value(val) + "%"
|
||||
else:
|
||||
region.data = "N/A"
|
||||
|
||||
self.display_ocr_data_in_terminal()
|
||||
|
||||
def preprocess_image(self, image):
|
||||
"""Preprocess the image to enhance text recognition."""
|
||||
# Convert image to grayscale
|
||||
gray_image = image.convert("L")
|
||||
gray = image.convert("L")
|
||||
scaled = gray.resize(
|
||||
(gray.width * 3, gray.height * 3),
|
||||
resample=Image.Resampling.LANCZOS
|
||||
)
|
||||
thresh = scaled.point(lambda p: p > 200 and 255)
|
||||
return thresh.filter(ImageFilter.MedianFilter(3))
|
||||
|
||||
# Apply threshold to make the image binary (black and white)
|
||||
threshold_image = gray_image.point(lambda p: p > 200 and 255)
|
||||
def update_points(self, new_val):
|
||||
now = time.time()
|
||||
if self.points:
|
||||
_, last_v = self.points[-1]
|
||||
if abs(new_val - last_v) < 1e-6:
|
||||
return
|
||||
if new_val < last_v:
|
||||
self.points.clear()
|
||||
self.points.append((now, new_val))
|
||||
if len(self.points) > MAX_DATA_POINTS:
|
||||
self.points.pop(0)
|
||||
|
||||
# Apply noise reduction (filter)
|
||||
processed_image = threshold_image.filter(ImageFilter.MedianFilter(3))
|
||||
return processed_image
|
||||
def compute_time_to_100(self):
|
||||
"""Return integer seconds until 100% or None if not feasible."""
|
||||
n = len(self.points)
|
||||
if n < 2:
|
||||
return None
|
||||
first_t, first_v = self.points[0]
|
||||
last_t, last_v = self.points[-1]
|
||||
diff_v = last_v - first_v
|
||||
if diff_v <= 0:
|
||||
return None
|
||||
|
||||
def clear_ocr_data(self):
|
||||
"""Clear the displayed OCR data."""
|
||||
self.ocr_display.clear()
|
||||
steps = n - 1
|
||||
total_time = last_t - first_t
|
||||
if total_time <= 0:
|
||||
return None
|
||||
|
||||
def display_ocr_data(self):
|
||||
"""Display OCR data in the text area on the left-hand side."""
|
||||
ocr_text = ""
|
||||
for region in self.regions:
|
||||
ocr_text += f"{region.label} Output:\n{region.data}\n\n" # Updated headers with "Output"
|
||||
self.ocr_display.setText(ocr_text)
|
||||
avg_change = diff_v / steps
|
||||
remain = 100.0 - last_v
|
||||
if remain <= 0:
|
||||
return None
|
||||
|
||||
avg_time = total_time / steps
|
||||
rate_per_s = avg_change / avg_time if avg_time > 0 else 0
|
||||
if rate_per_s <= 0:
|
||||
return None
|
||||
|
||||
return int(remain / rate_per_s)
|
||||
|
||||
def display_ocr_data_in_terminal(self):
|
||||
console = Console()
|
||||
os.system('cls' if os.name == 'nt' else 'clear')
|
||||
|
||||
console.print("[bold white]Project Borealis[/bold white]")
|
||||
console.print("[dim]Flyff Information Overlay[/dim]\n")
|
||||
|
||||
console.print(f"[bold]OCR Engine[/bold]: {OCR_ENGINE}")
|
||||
console.print(f"[bold]Data Polling Rate[/bold]: {POLLING_RATE_MS / 1000}s\n")
|
||||
|
||||
# Build the historical table
|
||||
table = Table(show_header=True, header_style=GREEN_HEADER_STYLE, style=None)
|
||||
table.add_column("Historical EXP", justify="center", style="green")
|
||||
table.add_column("Time Since Last Kill", justify="center", style="green")
|
||||
table.add_column("Average EXP Per Kill", justify="center", style="green")
|
||||
table.add_column("Average Time Between Kills", justify="center", style="green")
|
||||
|
||||
n = len(self.points)
|
||||
if n == 1:
|
||||
t0, v0 = self.points[0]
|
||||
exp_str = f"[green]{format_experience_value(v0)}%[/green]"
|
||||
table.add_row(exp_str, "N/A", "N/A", "N/A")
|
||||
else:
|
||||
for i in range(1, n):
|
||||
t_cur, v_cur = self.points[i]
|
||||
t_prev, v_prev = self.points[i - 1]
|
||||
|
||||
exp_str = f"[green]{format_experience_value(v_cur)}%[/green]"
|
||||
delta_t = t_cur - t_prev
|
||||
t_since_str = f"{delta_t:.1f}s"
|
||||
|
||||
diff_v = v_cur - self.points[0][1]
|
||||
steps = i
|
||||
avg_exp_str = f"{diff_v/steps:.4f}%"
|
||||
|
||||
total_time = t_cur - self.points[0][0]
|
||||
avg_kill_time = total_time / steps
|
||||
avg_time_str = f"{avg_kill_time:.1f}s"
|
||||
|
||||
table.add_row(exp_str, t_since_str, avg_exp_str, avg_time_str)
|
||||
|
||||
console.print(table)
|
||||
console.print()
|
||||
|
||||
# Prepare the progress bar
|
||||
current_exp = self.points[-1][1] if self.points else 0.0
|
||||
secs_left = self.compute_time_to_100()
|
||||
time_str = format_duration(secs_left) if secs_left is not None else "???"
|
||||
|
||||
# We'll display a single progress bar line in a context manager
|
||||
# Setting transient=False ensures it remains in the console
|
||||
with Progress(
|
||||
TextColumn("[bold white]Predicted Time to Level:[/bold white] "),
|
||||
BarColumn(bar_width=30),
|
||||
TextColumn(" [green]{task.percentage:>5.2f}%[/green] "),
|
||||
TextColumn(f"[orange]{time_str}[/orange] until 100%", justify="right"),
|
||||
console=console,
|
||||
transient=False,
|
||||
) as progress:
|
||||
task_id = progress.add_task("", total=100, completed=current_exp)
|
||||
# Force a manual refresh so the bar appears immediately
|
||||
progress.refresh()
|
||||
|
||||
def main():
|
||||
app = QApplication(sys.argv)
|
||||
window = BorealisOverlay()
|
||||
window.setWindowTitle("Borealis Overlay") # Set application window title
|
||||
window.show() # Explicitly show the window
|
||||
window.setWindowTitle("Project Borealis Overlay (Fixed Progress Bar)")
|
||||
window.show()
|
||||
sys.exit(app.exec_())
|
||||
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user