# coding:utf-8 import pandas as pd from src import App """写入文件""" # 写入excel df = pd.read_excel(App.resource_file("data/excel-comp-sheetdata.xlsx")) # 读取全部数据 all_data = pd.DataFrame(df) print(all_data.loc[14, 'name']) all_data.loc[14, 'name'] = 'McDermott PLCA' all_data.to_excel('C:\\Users\\Administrator\\Desktop\\1.xlsx', header=True, index=False)
canvas[:, :, :] = 255 new_image = Image.fromarray(canvas) draw = ImageDraw.Draw(new_image) # 创建绘制对象 font = ImageFont.truetype("consola.ttf", 10, encoding="unic") char_table = list("$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/|()1{}[]?-_+~<>i!lI;:,\"^`'. ") # font = ImageFont.truetype('simsun.ttc', 10) # char_table = list(u'新年快乐') # 开始绘制 pix_count = 0 table_len = len(char_table) for y in range(height): for x in range(width): if x % sample_step == 0 and y % sample_step == 0: draw.text((x * scale, y * scale), char_table[pix_count % table_len], pix[x, y], font) pix_count += 1 # 保存 if dst_img_file_path is not None: new_image.save(dst_img_file_path) print("used time : %d second, pix_count : %d" % ((int(time.time()) - start_time), pix_count)) print(pix_count) new_image.show() if __name__ == '__main__': image_file = App.resource_file("/img/wm.png") temp_file = App.temp_file("wm.png") happyNewYear(image_file, temp_file)
def load_dict(file): """英文字典/usr/share/dict""" englist_dic = [] with open(file, 'r', encoding='UTF-8') as ff: for line in ff.readlines(): englist_dic.append(line.strip()) return tuple(englist_dic) if __name__ == "__main__": """由于都是相对较小的文件因此直接进行统计""" endict = load_dict(App.resource_file("linux.words")) print("englis dic len:", len(endict)) count_dict = {} for dirpath, dirname, filenames in os.walk(u"C:\edocuments"): for filepath in filenames: f_n = os.path.join(dirpath, filepath) print("consume file =>", f_n) try: f_content = '' with open(f_n, 'r', encoding='UTF-8') as ff: for line in ff.readlines(): f_content += line # 文章字符串前期处理 f_content = trunNonalpha(f_content.lower())
ascii_char = list("$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/|()1{}[]?-_+~<>i!lI;:,\"^`'. ") def get_char(r, g, b, alpha=256): if alpha == 0: return ' ' length = len(ascii_char) gray = int(0.2126 * r + 0.7152 * g + 0.0722 * b) unit = (256.0 + 1) / length return ascii_char[int(gray / unit)] if __name__ == '__main__': image_file = App.resource_file("/opencv/green-spiral.jpg") im = Image.open(image_file) pix = im.load() ims = Image.new("RGB", (im.width,im.height), (255, 255, 255)) dr = ImageDraw.Draw(ims) font = ImageFont.truetype(os.path.join("fonts", "msyh.ttf"), 10) txt = "" for i in range(im.height): for j in range(im.width): char = get_char(*im.getpixel((j,i))) txt += char dr.text((j,i),char, pix[j, i], font) txt += '\n' with open("output.txt", 'w') as f:
# coding:UTF-8 import cv2 from src import App img_file = App.resource_file("/opencv/timg.jpg") im = cv2.imread(img_file, 0) sobx = cv2.CreateImage(cv2.GetSize(im), cv2.IPL_DEPTH_16S, 1) #Sobel with x-order=1 cv2.Sobel(im, sobx, 1, 0, 3) soby = cv2.CreateImage(cv2.GetSize(im), cv2.IPL_DEPTH_16S, 1) #Sobel withy-oder=1 cv2.Sobel(im, soby, 0, 1, 3) cv2.Abs(sobx, sobx) cv2.Abs(soby, soby) result = cv2.CloneImage(im) #Add the two results together. cv2.Add(sobx, soby, result) cv2.Threshold(result, result, 100, 255, cv2.CV_THRESH_BINARY_INV) cv2.ShowImage('Image', im) cv2.ShowImage('Result', result) cv2.WaitKey(0)
# coding:UTF-8 # python3.x """Imagge是pillow库中一个非常重要的模块,提供了大量用于图像处理的方法 """ from PIL import ImageGrab from src import App image_file = App.resource_file("/temp/test.jpg") # 获取屏幕指定区域的图像 im = ImageGrab.grab((0, 0, 100, 200)) im.show() # 或全屏截图 im = ImageGrab.grab() im.show()
# coding:UTF-8 import numpy as np from src import App """演示从文本中加载数据""" file_name = App.resource_file("/data/npl/affinity_dataset.txt") x = np.loadtxt(file_name) n_samples, n_features = x.shape print("This dataset has {0} samples and {1} features".format( n_samples, n_features)) # The names of the features, for your reference. features = ["bread", "milk", "cheese", "apples", "bananas"] # First, how many rows contain our premise: that a person is buying apples num_apple_purchases = 0 for sample in x: if sample[3] == 1: # This person bought Apples num_apple_purchases += 1 print("{0} people bought Apples".format(num_apple_purchases))