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李雪洋
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‎neural-networks-and-deep-learning/src/mytest/data.pkl‎

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‎neural-networks-and-deep-learning/src/mytest/network.py‎

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@@ -162,6 +162,7 @@ def sigmoid(z):
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return 1.0 / (1.0 + np.exp(-z))
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#计算S函数的导数
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def sigmoid_prime(z):
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"""Derivative of the sigmoid function."""
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return sigmoid(z) * (1 - sigmoid(z))

‎neural-networks-and-deep-learning/src/mytest/test.py‎

Lines changed: 24 additions & 22 deletions
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@@ -55,28 +55,30 @@ def feedforward(a):
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return a
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# card = [4, 1, 3, 0, 2, 6, 1, 9, 9, 2, 1, 2, 2, 7, 5, 7, 1, 3]
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# n = 0
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# pkllist = []
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# for i in range(1, 37):
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# srcImg = cv2.imread(f'./tmp/{i}.bmp', 0)
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# gray = cv2.equalizeHist(srcImg)
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# cv2.imshow('equalizeHist', gray)
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# cv2.waitKey(0)
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#
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# array = np.array(gray) # array is a numpy array
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# ary = []
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# for x in array:
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# for y in x:
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# aa = [float(Decimal((255 - y) / 255).quantize(Decimal('0.00000000')))]
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# ary.append(aa)
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# if n == len(card):
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# n = 0
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# print(card[n])
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# pkllist.append((ary, card[n]))
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# n += 1
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# fw = open('./data.pkl', 'wb+')
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# pickle.dump(pkllist, fw)
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card = [4, 1, 3, 0, 2, 6, 1, 9, 9, 2, 1, 2, 2, 7, 5, 7, 1, 3]
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n = 0
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pkllist = []
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for i in range(1, 37):
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srcImg = cv2.imread(f'./tmp/{i}.bmp', 0)
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gray = cv2.equalizeHist(srcImg)
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cv2.imshow('equalizeHist', gray)
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cv2.waitKey(0)
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array = np.array(gray) # array is a numpy array
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print(array)
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cv2.waitKey(0)
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ary = []
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for x in array:
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for y in x:
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aa = [float(Decimal((255 - y) / 255).quantize(Decimal('0.00000000')))]
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ary.append(aa)
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if n == len(card):
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n = 0
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print(card[n])
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pkllist.append((ary, card[n]))
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n += 1
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fw = open('./data.pkl', 'wb+')
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pickle.dump(pkllist, fw)
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data = pickle.load(open('./data.pkl', 'rb'))
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for x, y in data:

‎neural-networks-and-deep-learning/src/test.py‎

Lines changed: 7 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -10,5 +10,10 @@
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import mnist_loader
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training_data, validation_data, test_data = mnist_loader.load_data_wrapper()
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net = network.Network([784, 30, 10])
14-
net.SGD(training_data, 30, 10, 3.0, test_data=test_data)
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# net = network.Network([784, 30, 10])
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# net.SGD(training_data, 30, 10, 3.0, test_data=test_data)
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for x, y in training_data:
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print(x)
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print('---------------')
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print(y)
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break

‎opencv/cbss/01.py‎

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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# @Time : 2017/11/8 0008 下午 19:18
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# @Author : 李雪洋
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# @File : 01.py
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# @Software: PyCharm
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import cv2
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import numpy as np
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import os
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img_save_path = 'E:\\pythonDemo\\opencv\\cbss\\spit\\'
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# 按照指定图像大小调整尺寸
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def resize_image(image, height, width):
17+
top, bottom, left, right = (0, 0, 0, 0)
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# 获取图像尺寸
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h, w = image.shape
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# 对于长宽不相等的图片，找到最长的一边
23+
longest_edge = max(h, w)
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# 计算短边需要增加多上像素宽度使其与长边等长
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if h < longest_edge:
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dh = longest_edge - h
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top = dh // 2
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bottom = dh - top
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elif w < longest_edge:
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dw = longest_edge - w
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left = dw // 2
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right = dw - left
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else:
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pass
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# RGB颜色
38+
BLACK = [0, 0, 0]
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# 给图像增加边界，是图片长、宽等长，cv2.BORDER_CONSTANT指定边界颜色由value指定
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constant = cv2.copyMakeBorder(image, top, bottom, left, right, cv2.BORDER_CONSTANT, value=BLACK)
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# 调整图像大小并返回
44+
return cv2.resize(constant, (height, width))
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def saveSpitImg(boxList, dst):
48+
for box in boxList:
49+
img_org2 = dst.copy()
50+
img_plate = img_org2[box[2]:box[3], box[0]:box[1]]
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# img_plate = cv2.resize(img_plate, (30, 30), interpolation=cv2.INTER_CUBIC)
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img_plate = resize_image(img_plate, 30, 30)
53+
l = os.listdir(img_save_path)
54+
size = len(l)
55+
size += 1
56+
cv2.imwrite(img_save_path + str(size) + '.bmp', img_plate)
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58+
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for i in range(1, 5001):
60+
print(i)
61+
srcImg = cv2.imread(f"E:\\pythonDemo\\opencv\\cbss\\img\\{i}.bmp")
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h, w, _ = srcImg.shape
63+
dstImg = cv2.resize(srcImg, (w * 10, h * 10), interpolation=cv2.INTER_CUBIC)
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# cv2.imshow('dstImg', dstImg)
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# cv2.waitKey(0)
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gray = cv2.cvtColor(dstImg, cv2.COLOR_BGR2GRAY)
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ret1, th1 = cv2.threshold(gray, 82, 255, cv2.THRESH_BINARY_INV)
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# cv2.imshow('th1', th1)
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# cv2.waitKey(0)
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kernel = np.ones((11, 11), np.uint8)
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dilation = cv2.dilate(th1, kernel, iterations=1)
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# cv2.imshow('dilation', dilation)
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# cv2.waitKey(0)
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kernel = np.ones((11, 11), np.uint8)
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dilation2 = cv2.dilate(dilation, kernel, iterations=1)
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# cv2.imshow('dilation2', dilation2)
83+
# cv2.waitKey(0)
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(_, contours, _) = cv2.findContours(dilation2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
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boxList = []
88+
for j in contours:
89+
# 计算该轮廓的面积
90+
area = cv2.contourArea(j)
91+
#
92+
# 面积小的都筛选掉
93+
if area < 1300:
94+
continue
95+
96+
x, y, width, height = cv2.boundingRect(j)
97+
box = [x, y, width, height]
98+
box = [box[0], box[0] + box[2], box[1], box[1] + box[3]]
99+
boxList.append(box)
100+
# cv2.rectangle(dstImg, (box[0], box[2]), (box[1], box[3]), (0, 255, 0), 1)
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saveSpitImg(boxList, th1)

‎opencv/cbss/download.py‎

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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# @Time : 2017/11/8 0008 下午 19:18
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# @Author : 李雪洋
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# @File : download.py
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# @Software: PyCharm
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# https://hq.cbss.10010.com/image?mode=validate&width=60&height=20&random=0.5718313927110062
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import requests
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def download(n):
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url = 'http://hq.cbss.10010.com/image?mode=validate&width=60&height=20&random=0.5718313927110062'
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res = requests.get(url, stream=True)
16+
with open('E:\\pythonDemo\\opencv\\cbss\\img\\' + str(n) + '.bmp', 'wb') as f:
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for chunk in res.iter_content(chunk_size=1024):
18+
if chunk: # filter out keep-alive new chunks
19+
f.write(chunk)
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f.flush()
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f.close()
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print(n)
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for i in range(1, 5001):
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download(i)

‎opencv/cbss/makePkl.py‎

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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# @Time : 2017/11/9 0009 下午 15:15
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# @Author : 李雪洋
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# @File : makePkl.py
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# @Software: PyCharm
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import pickle
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from decimal import Decimal
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import cv2
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import numpy as np
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import os
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dir_name = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z']
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base_path = 'E:\\pythonDemo\\opencv\\cbss\\trainDemo\\'
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pkllist = []
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for dirName in dir_name:
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rootdir = base_path + dirName
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fileList = os.listdir(rootdir) # 列出文件夹下所有的目录与文件
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24+
realNp = np.zeros((len(dir_name), 1))
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for n in range(len(dir_name)):
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if dir_name[n] == dirName:
27+
realNp[n] = 1
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else:
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realNp[n] = 0
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for i in range(0, len(fileList)):
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path = os.path.join(rootdir, fileList[i])
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if os.path.isfile(path):
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#print(path)
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img = cv2.imread(path, 0)
36+
# cv2.imshow('img', img)
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# cv2.waitKey(0)
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array = np.array(img) # array is a numpy array
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print(array)
40+
ary = np.zeros((900, 1))
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num = 0
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for x in array:
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for y in x:
44+
ary[num] = [float(Decimal(y / 255).quantize(Decimal('0.00000000')))]
45+
num += 1
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pkllist.append((ary, realNp))
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48+
fw = open('./data.pkl', 'wb+')
49+
pickle.dump(pkllist, fw)

‎opencv/cbss/readPkl.py‎

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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# @Time : 2017/11/9 0009 下午 16:49
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# @Author : 李雪洋
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# @File : readPkl.py
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# @Software: PyCharm
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import pickle
9+
from numpy import *
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11+
data = pickle.load(open('./data.pkl', 'rb'))
12+
print(len(data))

‎opencv/cbss/trainDemo/A/147.bmp‎

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‎opencv/cbss/trainDemo/A/159.bmp‎

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