python: 压缩图片.webp
pip install imageio
image = imageio.imread("1.jpg") imageio.imwrite("output_image.webp", image, "WEBP")
# 代码示例:使用Python的Keras库构建Autoencoder模型 from keras.models import Model from keras.layers import Input, Dense input_img = Input(shape=(784,)) encoded = Dense(128, activation='relu')(input_img) decoded = Dense(784, activation='sigmoid')(encoded) autoencoder = Model(input_img, decoded) autoencoder.compile(optimizer='adam', loss='binary_crossentropy')
rows, cols = (10, 10) # 创建一个真正的二维数组 F = [[0 for _ in range(cols)] for _ in range(rows)] n = int(input('请输入数字:')) y = 0 while y < rows: x = 0 while x < cols: for i in range(y, y + n): for j in range(x, x + n): if(i<=9 and j<=9): F[i][j] = 1 x += n * 2 # 用于每个隔一个相同的距离x 的坐标 y += n * 2 # 用于每个隔一个相同的距离y的坐标 #打印效果 for row in F: for col in row: print(col, end=" ") print()
rows, cols = (10, 10) # 创建一个真正的二维数组 F = [[0 for _ in range(cols)] for _ in range(rows)] n = int(input('请输入数字:')) y = 0 while y < rows: x = 0 while x < cols: for i in range(y, min(y + n, rows)): for j in range(x, min(x + n, cols)): F[i][j] = 1 x += n * 2 # 用于每个隔一个相同的距离x 的坐标 y += n * 2 # 用于每个隔一个相同的距离y的坐标 #打印效果 for row in F: for col in row: print(col, end=" ") print() letter_array = [ "JGJGDDAOYD", "IDGFHSPOSA", "FGDIOSAFSC", "INTERNETSO", "FJKCOSAFSM", "DJSGAPAHDP", "HAUSTRFBFU", "KDGFUCNSKT", "WSJDYCFXDE", "ODVFKXJVCR" ] word = input("请输入单词: ") word = word.upper() find = False if not letter_array or not word: print("输入的单词为空或字符串数组为空。") else: rows = len(letter_array) word_length = len(word) # 遍历所有行 for row in letter_array: # 在每一行中,从左到右滑动单词长度的窗口 for start_col in range(len(row) - word_length + 1): # 检查当前窗口的字符串是否与单词匹配 if row[start_col:start_col + word_length] == word: find = True # 如果在某一行的窗口中找到单词,则返回True break # 找到单词后立即退出循环 if find: break # 找到单词后立即退出循环 if find: print(f"单词 '{word}' 存在于字符串数组的行线上。") else: print(f"单词 '{word}' 不存在于字符串数组的任何行线上。") letter_array = [ "JGJGDDAOYD", "IDGFHSPOSA", "FGDIOSAFSC", "INTERNETSO", "FJKCOSAFSM", "DJSGAPAHDP", "HAUSTRFBFU", "KDGFUCNSKT", "WSJDYCFXDE", "ODVFKXJVCR" ] word = input("请输入单词: ") word = word.upper() rows = len(letter_array) cols = len(letter_array[0]) if rows > 0 else 0 word_length = len(word) find = False # 检查所有可能的起始位置 for i in range(rows): for j in range(cols): # 检查当前位置是否在数组的边界内,如果这个单词可以放在对角线上 if i + word_length <= rows and j + word_length <= cols: # 检查单词是否与对角线匹配 match = True for k in range(word_length): if letter_array[i + k][j + k] != word[k]: match = False break if match: find = True break # 找到匹配后立即停止搜索 if find: break # 找到匹配后立即停止搜索 if find: print(f"单词 '{word}' 存在于字符串数组的对角线上。") else: print(f"单词 '{word}' 不存在于字符串数组的任何对角线上。") letter_array = [ "JGJGDDAOYD", "IDGFHSPOSA", "FGDIOSAFSC", "INTERNETSO", "FJKCOSAFSM", "DJSGAPAHDP9", "HAUSTRFBFU", "KDGFUCNSKT", "WSJDYCFXDE", "ODVFKXJVCR" ] word = "CAR" word = input("please enter word:") word = word.upper() rows = len(letter_array) cols = len(letter_array[0]) if rows > 0 else 0 find=False # 所有可能的index起始位置 for i in range(rows): for j in range(cols): # 检查当前位置是否在数组的边界内 # ,如果这个单词可以放在index上 if i + len(word) <= rows and j + len(word) <= cols: # 检查单词是否与index匹配 match = True for k in range(len(word)): if letter_array[i + k][j + k] != word[k]: match = False break if match: find= True if find: print(f"The word '{word}' exists in the letter array as a diagonal.") else: print(f"The word '{word}' does not exist in the letter array as a diagonal.") letter_array = [ "JGJGDDAOYD", "IDGFHSPOSA", "FGDIOSAFSC", "INTERNETSO", "FJKCOSAFSM", "DJSGAPAHDP", "HAUSTRFBFU", "KDGFUCNSKT", "WSJDYCFXDE", "ODVFKXJVCR" ] word = "MPUTER" # 在一列部分的位置 word=input("输入要在列中查找的单词") # 转换为大写以便与letter_array中的字符进行比较 word = word.upper() find=False if not letter_array or not word: find= False cols = len(letter_array[0]) rows = len(letter_array) word_length = len(word) # 遍历所有列 for j in range(cols): # 在每一列中,从顶部到底部滑动单词长度的窗口 for start_row in range(rows - word_length + 1): # 检查当前窗口的字符串是否与单词匹配 match = True for i in range(word_length): if letter_array[start_row + i][j] != word[i]: match = False break if match: find= True # 如果在某一列的窗口中找到单词,则返回True if find: print(f"The word Part '{word}' exists in the letter array as a column.") else: print(f"The word Part '{word}' does not exist in the letter array as a column.")
rows, cols = (10, 10) F = [[0 for _ in range(cols)] for _ in range(rows)] n = int(input("please number:")) y = 0 while y < rows: x = 0 while x < cols: for i in range(y, y + n ): for j in range(x, x + n): if i <= 9 and j <= 9: F[i][j] = 1 x += n * 2 y += n * 2 # 打印效果 for row in F: for col in row: print(col, end=" ") print() rows, cols = (10, 10) # 创建一个真正的二维数组 F = [[0 for _ in range(cols)] for _ in range(rows)] n = int(input('请输入数字:')) y = 0 while y < rows: x = 0 while x < cols: for i in range(y, min(y + n,rows)): for j in range(x, min(x + n,cols)): F[i][j] = 1 x += n * 2 # 用于每个隔一个相同的距离x 的坐标 y += n * 2 # 用于每个隔一个相同的距离y的坐标 #打印效果 for row in F: for col in row: print(col, end=" ") print()
哲学管理(学)人生, 文学艺术生活, 自动(计算机学)物理(学)工作, 生物(学)化学逆境, 历史(学)测绘(学)时间, 经济(学)数学金钱(理财), 心理(学)医学情绪, 诗词美容情感, 美学建筑(学)家园, 解构建构(分析)整合学习, 智商情商(IQ、EQ)运筹(学)生存.---Geovin Du(涂聚文)