資源簡介

代碼片段和文件信息
from?sklearn?import?datasets
#導入交叉驗證庫
from?sklearn?import?cross_validation
#導入SVM分類算法庫
from?sklearn?import?svm
#導入圖表庫
import?cv2
import?numpy?as?np
from?tensorflow.examples.tutorials.mnist?import?input_data
from?sklearn.externals?import?joblib
drawing?=?False?#鼠標按下為真
mode?=?True?#如果為真,畫矩形,按m切換為曲線
ixiy=-1-1
mnist?=?input_data.read_data_sets(“MNIST“?one_hot=True)
#?X_train?=?mnist.train.images
#?X_test?=??mnist.test.images
number_train?=?len(mnist.train.images)
number_test?=?len(mnist.test.images)
X_train?=?mnist.train.images.reshape((number_train?784))
X_test?=??mnist.test.images.reshape((number_test?784))
#?print(X_train.shape)
y_train?=?np.zeros(number_train)
y_test?=?np.zeros(number_test)
#?print(mnist.test.labels[2])
for?i?in?range?(054999):
????for?j?in?range?(09):
????????if?mnist.train.labels[i][j]?==?1:
????????????y_train[i]?=?j
????????????j?=?0
????????????break
#?print(y_train[10])
for?i?in?range?(09999):
????for?j?in?range?(09):
????????if?mnist.test.labels[i][j]?==?1:
????????????y_test[i]?=?j
#?print(y_test)
#生成SVM分類模型
clf?=?svm.SVC(max_iter=?20000)
#使用訓練集對svm分類模型進行訓練
clf.fit(X_train?y_train)
joblib.dump(clf“model_2/SVM_MNIST.pkl“)
print(1)
score?=?clf.score(X_testy_test)
print(“準確率?:?“score)
#?def?draw(eventxyflagsparam):
#?????global?ixiydrawingmode
#
#?????if?event?==?cv2.EVENT_LBUTTONDOWN:
#?????????drawing?=?True
#?????????ixiy=xy
#
#
#?????elif?event?==?cv2.EVENT_MOUSEMOVE:
#?????????if?drawing?==?True:
#?????????????cv2.circle(img?(x?y)?5?(255?255?255)?-1)
#?????elif?event?==?cv2.EVENT_LBUTTONUP:
#?????????drawing?=?False
#?????????cv2.circle(img?(x?y)?5?(255?255?255)?-1)
#
#
#?img?=?np.zeros((1281281)np.uint8)
#
#?cv2.namedWindow(‘image‘)
#?cv2.setMouseCallback(‘image‘draw)
#
#?while(1):
#
#?????cv2.imshow(‘image‘img)
#?????resized_image?=?cv2.resize(img(2828))
#?????resized_image?=?cv2.normalize(resized_imageresized_image01cv2.NORM_MINMAXcv2.CV_32F)
#?????#?print(resized_image)
#?????#?print(resized_image.shape)
#?????resized_image?=?resized_image.reshape((1?784))
#?????#?cv2.imshow(“zero“resized_image)
#?????k?=?cv2.waitKey(1)?&?0xFF
#?????if?k?==?ord(‘m‘)?:
#?????????mode?=?not?mode
#?????elif?k?==?13:
#?????????predict?=?clf.predict(resized_image)
#?????????print(“predict?:?“?predict)
#?????elif?k?==?27:
#?????????break
#?cv2.destroyAllWindows()
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????2586??2018-01-11?13:07??MNIST.py
?????文件????????1596??2018-01-11?13:05??手寫3.py
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