Merge pull request '修改了doc中用户界面设计部分' (#27) from hexuesong into develop

txl/huidu_shuai.py

@@ -0,0 +1,45 @@
+import  PIL.Image
+import numpy
+import os
+import shutil
+def sum_right(path):
+    img = PIL.Image.open(path)
+    array = numpy.array(img)
+    num = array.sum(axis=0)
+    print(type(num))
+    res_left = 0
+    res_right = 0
+    for i in range(256,512):
+        res_right += num[i]
+    print(res_right)
+
+if __name__ == '__main__':
+    dir2 = r"C:\Users\xinluo\PycharmProjects\pythonProject\Camera Roll"
+    dir1 = r"C:\Users\xinluo\PycharmProjects\pythonProject\Saved Pictures"
+    names = os.listdir(dir1)
+    n = len(names)
+    print("文件数量",n)
+    res = 0
+    average_5 = 25565356
+    average_25 = 26409377
+    average_5_right = 10006019
+    average_tmp = (average_25+average_5)//2
+    count = 0
+    show(os.path.join(dir1, "uni4F6C.png"))
+    for i in range(n):
+        #取图片
+        img = PIL.Image.open(os.path.join(dir1,names[i]))
+        file = os.path.join(dir1,names[i])
+        rmfile = os.path.join(dir2,names[i])
+        array = numpy.array(img)
+        num = array.sum(axis=0)
+        res_right = 0
+        for i in range(256, 512):
+            res_right += num[i]
+        average_5_right += res_right/n
+        if (res_right > average_5_right).all():
+             shutil.copyfile(file, rmfile)
+             os.remove(file)
+             count += 1
+    print(average_5_right)
+    print(count)

txl/qingxi_shuai.py

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+# -*- coding: UTF-8 -*-
+
+import argparse
+import cv2
+import os
+
+# 使用方法：命令行cd到脚本所在文件夹，python picture.py -i "图片路径"
+#便历图片，合格则保存，不合格则删除
+
+
+def variance_of_laplacian(image):
+    # 使用拉普拉斯算子提取图像边缘信息，计算边缘的平均方差
+    return cv2.Laplacian(image, cv2.CV_64F).var()
+def read_path(file_pathname):
+    #遍历该目录下的所有图片文件
+    for filename in os.listdir(file_pathname):
+        print(filename)
+        image = cv2.imread(file_pathname+'/'+filename)
+        # 取图片的灰度通道
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        fm = variance_of_laplacian(gray)
+
+        # 如果得分比阈值低，认为是模糊
+        if fm < 100.0:
+            os.remove(file_pathname+'/'+filename)
+#read_path(r"C:\Users\xinluo\PycharmProjects\pythonProject\Saved Pictures")
+#print(os.getcwd())

txl/video_to_photo.py

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+import cv2
+import argparse
+import os
+
+
+def parse_args():
+    """
+    Parse input arguments
+    """
+    parser = argparse.ArgumentParser(description='Process pic')
+    parser.add_argument('--input', help='video to process', dest='input', default=None, type=str)
+    parser.add_argument('--output', help='pic to store', dest='output', default=None, type=str)
+    # default为间隔多少帧截取一张图片
+    parser.add_argument('--skip_frame', dest='skip_frame', help='skip number of video', default=10, type=int)
+    # input为输入视频的路径 ，output为输出存放图片的路径
+    args = parser.parse_args(['--input', r'C:\Users\xinluo\PycharmProjects\pythonProject\1234.mp4', '--output', r'C:\Users\xinluo\PycharmProjects\pythonProject\Saved Pictures'])
+    return args
+
+
+def process_video(i_video, o_video, num):
+    cap = cv2.VideoCapture(i_video)
+    num_frame = cap.get(cv2.CAP_PROP_FRAME_COUNT)
+    expand_name = '.jpg'
+    if not cap.isOpened():
+        print("Please check the path.")
+    cnt = 0
+    count = 0
+    while 1:
+        ret, frame = cap.read()
+        cnt += 1
+        #  how
+        # many
+        # frame
+        # to
+        # cut
+        if cnt % num == 0:
+            count += 1
+            cv2.imwrite(os.path.join(o_video, str(count) + expand_name), frame)
+
+        if not ret:
+            break
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    if not os.path.exists(args.output):
+        os.makedirs(args.output)
+    print('Called with args:')
+    print(args)
+    process_video(args.input, args.output, args.skip_frame)

txl/xiangsu_shuai.py

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+import os
+from PIL import Image, ImageFile
+
+# ImageFile.LOAD_TRUNCATED_IMAGES = True    #如果图片太大报错可以使用这个
+
+
+
+def pixel():
+    b = 0
+    dir = r'C:\Users\xinluo\PycharmProjects\pythonProject\Camera Roll'  # 需要处理的图片目录
+    files = os.listdir(dir)  # 得到需要处理的所有图片
+    files.sort()  # 对图片进行排序
+    for each_bmp in files:  # 遍历图片，进行筛选
+
+        each_bmp_root = os.path.join(dir, each_bmp)  # 得到每个图片路径
+        image = Image.open(each_bmp_root)  # 打开每个图片
+        img = image.convert('RGB')  # 转化成RGB，其实图片大多都是RGB，即使灰度图也不一定转RGB，看需求
+        width = img.size[0]  # 获取图像的宽和长
+        height = img.size[1]
+
+        if (width < 650) or (height < 650):  # 判断图形尺寸有一条边小于600像素的直接删除
+            os.remove(each_bmp_root)