同步bin

.gitignore

@@ -4,4 +4,5 @@ Superstar_log.ldf
 .vs
 build.bat
 *.exe
-bin/*
+bin/logfile.txt
+.gitignore

bin/py/display_excel_sheets.py

@@ -0,0 +1,45 @@
+import pandas as pd
+import sqlite3
+
+# 读取Excel文件
+excel_file_path = '歌星.xlsx'  # 替换为你的Excel文件路径
+
+# 使用ExcelFile类获取工作表名称
+excel_file = pd.ExcelFile(excel_file_path, engine='openpyxl')
+sheet_names = excel_file.sheet_names
+
+# 选择你想要导入的工作表
+sheet_to_import = '工作表1'  # 替换为你实际的工作表名称
+df = pd.read_excel(excel_file_path, sheet_name=sheet_to_import, engine='openpyxl')
+
+# 打印前五行内容
+print(f"工作表: {sheet_to_import}")
+print(df.head(), "\n")
+
+# 连接到SQLite数据库（如果数据库不存在，会自动创建）
+conn = sqlite3.connect('KSongDatabase.db')
+cursor = conn.cursor()
+
+# 获取列名
+columns = df.columns.tolist()
+
+# 动态生成CREATE TABLE语句
+table_name = 'ArtistLibrary'
+create_table_sql = f'CREATE TABLE IF NOT EXISTS {table_name} ('
+create_table_sql += ', '.join([f'"{col}" TEXT' for col in columns])
+create_table_sql += ')'
+
+# 执行CREATE TABLE语句
+cursor.execute(create_table_sql)
+
+# 将DataFrame的数据写入SQLite表
+df.to_sql(table_name, conn, if_exists='append', index=False)
+
+# 验证数据是否插入成功
+print("数据插入后前五行内容:")
+query_result = pd.read_sql_query(f"SELECT * FROM {table_name} LIMIT 5", conn)
+print(query_result)
+
+# 提交事务并关闭连接
+conn.commit()
+conn.close()

bin/py/generate_config_ini.py

@@ -0,0 +1,58 @@
+from configparser import ConfigParser
+
+# Define the base paths for the normal, mouseDown, and mouseOver images
+normal_base_path = "themes\\superstar\\歌星\\拼音\\VOD_歌星查詢_拼音查詢(按鍵)-"
+mouse_down_base_path = "themes\\superstar\\歌星\\拼音\\VOD_歌星查詢_拼音查詢(按鍵)-"
+mouse_over_base_path = "themes\\superstar\\歌星\\拼音\\VOD_歌星查詢_拼音查詢(按鍵)-"
+
+# Create a ConfigParser object
+config = ConfigParser()
+config.optionxform = str  # Preserve case for option names
+
+# # Add the section for EnglishLetterButtonImages
+# config.add_section("EnglishLetterButtonImages")
+config.add_section("PinYinLetterButtonImages")
+
+# # Define the QWERTY layout sequence
+# qwerty_layout = "QWERTYUIOPASDFGHJKLZXCVBNM"
+
+# Add the image paths dynamically based on the QWERTY layout coordinates
+for i in range(26):
+    if i < 19:
+        normal_image_number = i + 3
+        mouse_down_image_number = i + 32
+        mouse_over_image_number = i + 3
+    else:
+        normal_image_number = i + 4
+        mouse_down_image_number = i + 33
+        mouse_over_image_number = i + 4
+    
+    normal_image = f"{normal_base_path}{normal_image_number:02}.png"
+    mouse_down_image = f"{mouse_down_base_path}{mouse_down_image_number:02}.png"
+    mouse_over_image = f"{mouse_over_base_path}{mouse_over_image_number:02}.png"
+    
+    # Add the image paths to the config
+    config.set("PinYinLetterButtonImages", f"button{i}_normal", normal_image)
+    config.set("PinYinLetterButtonImages", f"button{i}_mouseDown", mouse_down_image)
+    config.set("PinYinLetterButtonImages", f"button{i}_mouseOver", mouse_over_image)
+
+# Add the image paths dynamically for NumberButtonImages
+# for i in range(10):
+#     normal_image_number = i + 3
+#     mouse_down_image_number = i + 42
+#     mouse_over_image_number = i + 3
+    
+#     normal_image = f"{normal_base_path}{normal_image_number:02}.png"
+#     mouse_down_image = f"{mouse_down_base_path}{mouse_down_image_number:02}.png"
+#     mouse_over_image = f"{mouse_over_base_path}{mouse_over_image_number:02}.png"
+    
+#     # Add the image paths to the config
+#     config.set("NumberButtonImages", f"button{i}_normal", normal_image)
+#     config.set("NumberButtonImages", f"button{i}_mouseDown", mouse_down_image)
+#     config.set("NumberButtonImages", f"button{i}_mouseOver", mouse_over_image)
+
+# Write the config to file
+with open("config.ini", "a", encoding="utf-8") as configfile:
+    config.write(configfile)
+
+print("config.ini file has been updated successfully.")

bin/py/singer_pinyin_converter.py

@@ -0,0 +1,43 @@
+import sqlite3
+from pypinyin import lazy_pinyin, Style
+from tqdm import tqdm
+
+def chinese_to_initials(chinese_str):
+    pinyin_list = lazy_pinyin(chinese_str, style=Style.FIRST_LETTER)
+    initials = ''.join([char.upper() for char in pinyin_list])
+    return initials
+
+# 連接到 SQLite 資料庫
+conn = sqlite3.connect('KSongDatabase.db')
+cursor = conn.cursor()
+
+# 確保 SongLibrary 表中有 SingerA_pinyin 和 SingerB_pinyin 欄位
+# cursor.execute('''ALTER TABLE SongLibrary ADD COLUMN 歌星A拼音 TEXT''')
+# cursor.execute('''ALTER TABLE SongLibrary ADD COLUMN 歌星B拼音 TEXT''')
+
+# 讀取所有的歌手名稱
+cursor.execute("SELECT [歌曲編號], [歌星 A], [歌星 B] FROM SongLibrary")
+rows = cursor.fetchall()
+
+# 使用 tqdm 來顯示進度條
+for row in tqdm(rows, desc="Processing songs", unit="song"):
+    song_id, singer_a, singer_b = row
+    if singer_a:
+        singer_a_pinyin = chinese_to_initials(singer_a)
+    else:
+        singer_a_pinyin = None
+
+    if singer_b:
+        singer_b_pinyin = chinese_to_initials(singer_b)
+    else:
+        singer_b_pinyin = None
+
+    # 更新資料庫
+    cursor.execute(
+        "UPDATE SongLibrary SET 歌星A拼音 = ?, 歌星B拼音 = ? WHERE [歌曲編號] = ?",
+        (singer_a_pinyin, singer_b_pinyin, song_id)
+    )
+
+# 提交變更並關閉資料庫連接
+conn.commit()
+conn.close()

bin/themes/superstar/py/test.py

@@ -0,0 +1,33 @@
+import cv2
+import numpy as np
+
+# Load the image
+image_path = 'toggle_light.jpg'
+image = cv2.imread(image_path)
+
+# Convert to grayscale
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+# Set threshold for non-white color
+# Note: Adjust the threshold values based on your image's specific conditions
+upper_threshold = 220  # Anything below this will be considered as non-white
+
+# Create a mask for non-white regions (below the threshold value)
+mask = cv2.inRange(gray, 0, upper_threshold)
+
+# Find contours from the mask
+contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+# Draw contours or compute bounding boxes
+for contour in contours:
+    # Calculate the bounding rectangle for each non-white region
+    x, y, w, h = cv2.boundingRect(contour)
+    print(f"Bounding box coordinates: X: {x}, Y: {y}, Width: {w}, Height: {h}")
+
+    # Optional: Draw the bounding box on the original image
+    cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
+
+# Display the results
+cv2.imshow('Image with Bounding Boxes', image)
+cv2.waitKey(0)
+cv2.destroyAllWindows()

bin/themes/superstar/py/test2.py

@@ -0,0 +1,80 @@
+import cv2
+import numpy as np
+
+# 初始化坐标点
+roi_pts = []
+drawing = False # True if the mouse is pressed down
+
+# 鼠标回调函数
+def select_roi(event, x, y, flags, param):
+    global roi_pts, drawing
+    
+    # 当按下左键是记录起始位置坐标
+    if event == cv2.EVENT_LBUTTONDOWN:
+        drawing = True
+        roi_pts = [(x, y)]
+
+    # 当鼠标左键按下并移动是绘制图形
+    elif event == cv2.EVENT_MOUSEMOVE:
+        if drawing == True:
+            temp_image = param.copy()
+            cv2.rectangle(temp_image, roi_pts[0], (x, y), (0, 255, 0), 2)
+            cv2.imshow('image', temp_image)
+
+    # 当松开鼠标左键停止绘画
+    elif event == cv2.EVENT_LBUTTONUP:
+        drawing = False
+        roi_pts.append((x, y))
+        cv2.rectangle(param, roi_pts[0], (x, y), (0, 255, 0), 2)
+        cv2.imshow('image', param)
+
+# 读取图像
+image = cv2.imread('555024.jpg')
+image_copy = image.copy()
+cv2.namedWindow('image')
+cv2.setMouseCallback('image', select_roi, image)
+
+# Keep looping until the 'q' key is pressed
+while True:
+    cv2.imshow('image', image)
+    key = cv2.waitKey(1) & 0xFF
+    
+    # 按下'r'重置选择区域
+    if key == ord('r'):
+        image = image_copy.copy()
+        roi_pts = []
+
+    # 按下'q'退出循环
+    elif key == ord('q'):
+        break
+
+# 关闭所有打开的窗口
+cv2.destroyAllWindows()
+
+# 如果选择了区域，那么进行黄色检测
+if len(roi_pts) == 2:
+    roi = image_copy[roi_pts[0][1]:roi_pts[1][1], roi_pts[0][0]:roi_pts[1][0]]
+    hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
+    lower_yellow = np.array([20, 100, 100])
+    upper_yellow = np.array([30, 255, 255])
+    mask = cv2.inRange(hsv_roi, lower_yellow, upper_yellow)
+    
+    # 在掩码上找出轮廓
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    # 如果有轮廓则找出最大的轮廓
+    if contours:
+        max_contour = max(contours, key=cv2.contourArea)
+        x, y, w, h = cv2.boundingRect(max_contour)
+        cv2.rectangle(roi, (x, y), (x+w, y+h), (0, 255, 0), 2)
+        print(f"Yellow area at X: {x}, Y: {y}, W: {w}, H: {h}")
+        
+        # 将边界框位置映射回原始图像
+        x += roi_pts[0][0]
+        y += roi_pts[0][1]
+        cv2.rectangle(image_copy, (x, y), (x+w, y+h), (0, 255, 0), 2)
+        print(f"Yellow area at X: {x}, Y: {y}, W: {w}, H: {h}")
+    
+    cv2.imshow('Detected Yellow Area in ROI', image_copy)
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()

bin/themes/superstar/py/test3.py

@@ -0,0 +1,55 @@
+import cv2
+import numpy as np
+import os
+
+# 使用絕對路徑
+image_path = 'image.jpg'
+# if not os.path.exists(image_path):
+#     print("File does not exist:", image_path)
+# else:
+#     print("File exists, attempting to load...")
+image = cv2.imread(image_path)
+
+if image is None:
+    print("But failed to load.")
+else:
+    print("Image loaded successfully, processing...")
+
+# Convert to HSV color space
+hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+
+# Define the range for yellow color in HSV
+# Adjust these ranges based on your specific yellow color and lighting conditions
+lower_yellow = np.array([20, 100, 100])
+upper_yellow = np.array([30, 255, 255])
+lower_pink = np.array([140, 100, 100])
+upper_pink = np.array([170, 255, 255])
+lower_purple = np.array([129, 50, 50])  # Lower bound of purple
+upper_purple = np.array([158, 255, 255])  # Upper bound of purple
+lower_blue = np.array([110, 50, 50])  # Lower bound of blue
+upper_blue = np.array([130, 255, 255])  # Upper bound of blue
+lower_blue_violet = np.array([120, 50, 50])  # Lower bound of blue-violet
+upper_blue_violet = np.array([160, 255, 255])  # Upper bound of blue-violet
+lower_red2 = np.array([170, 100, 100])
+upper_red2 = np.array([180, 255, 255])
+
+# Create a mask for yellow color
+mask = cv2.inRange(hsv, lower_pink, upper_pink)
+
+# Find contours on the mask
+contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+# Draw all contours
+for contour in contours:
+    x, y, w, h = cv2.boundingRect(contour)
+    cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
+    coordinates_text = f"X: {x}, Y: {y}, W: {w}, H: {h}"
+    # if w > 100:
+    print(coordinates_text)
+    # Display coordinates on the image
+    cv2.putText(image, coordinates_text, (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)
+
+# Show the image with all bounding boxes drawn
+cv2.imshow('Image with yellow contours', image)
+cv2.waitKey(0)
+cv2.destroyAllWindows()

bin/themes/superstar/py/test4.py

@@ -0,0 +1,40 @@
+import cv2
+import numpy as np
+
+def detect_light_areas(image_path):
+    # 讀取圖片
+    image = cv2.imread(image_path)
+    if image is None:
+        print("Failed to load image.")
+        return
+    
+    # 將圖片從 BGR 轉換到 HSV 色彩空間
+    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+    
+    # 設定 HSV 閾值範圍來選取淺色區域
+    lower_hsv = np.array([0, 0, 70])  # 較低的 HSV 閾值
+    upper_hsv = np.array([180, 50, 255])  # 較高的 HSV 閾值
+    
+    # 創建遮罩
+    mask = cv2.inRange(hsv, lower_hsv, upper_hsv)
+    
+    # 找到遮罩上的輪廓
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    
+    # 在原始圖片上畫框
+    for contour in contours:
+        x, y, w, h = cv2.boundingRect(contour)
+        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)  # 綠色方框，2像素寬
+        text = f"X:{x} Y:{y} W:{w} H:{h}"
+        if w < 40 or h < 40:
+            continue
+        cv2.putText(image, text, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)  # 白色文字
+    
+    # 顯示原圖和結果
+    cv2.imshow('Original', image)
+    # cv2.imshow('Light Areas Detected', mask)  # 顯示遮罩
+    cv2.waitKey(0)
+    cv2.destroyAllWindows()
+
+# 使用上面的函數
+detect_light_areas('555011.jpg')  # 請更換為實際的圖片路徑

bin/themes/superstar/py/test5.py

@@ -0,0 +1,30 @@
+import cv2
+import numpy as np
+
+# Load the image
+image_path = '555020.jpg'  # replace with your image path
+image = cv2.imread(image_path)
+
+# Convert to grayscale
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+# Apply thresholding to get binary image
+_, binary = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)
+
+# Find contours of the white regions
+contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+# Draw contours on the original image (optional, for visualization)
+for contour in contours:
+    cv2.drawContours(image, [contour], -1, (0, 255, 0), 2)
+
+# Print positions of the white regions
+for i, contour in enumerate(contours):
+    x, y, w, h = cv2.boundingRect(contour)
+    if w > 100:
+        print(f"White region {i+1}: x={x}, y={y}, width={w}, height={h}")
+
+# Show the image with contours (optional, for visualization)
+cv2.imshow('White regions', image)
+cv2.waitKey(0)
+cv2.destroyAllWindows()

bin/themes/superstar/py/test6.py

@@ -0,0 +1,25 @@
+from PIL import Image
+
+def change_image_dpi(input_path, output_path, new_dpi):
+    # 打开图像
+    image = Image.open(input_path)
+    
+    # 获取当前的dpi值（如果有）
+    dpi = image.info.get('dpi', (72, 72))
+    print(f"当前DPI: {dpi}")
+    
+    # 保存图像并设置新的dpi值
+    image.save(output_path, dpi=(new_dpi, new_dpi))
+    print(f"DPI已更改为: {new_dpi}")
+
+# 输入图像路径
+input_image_path = "image.jpg"
+
+# 输出图像路径
+output_image_path = "image.jpg"
+
+# 目标DPI
+new_dpi = 96
+
+# 调用函数
+change_image_dpi(input_image_path, output_image_path, new_dpi)