MCPcopy Index your code
hub / github.com/lawlite19/MachineLearning_Python / display_imageData

Function display_imageData

PCA/PCA.py:115–138  ·  view source on GitHub ↗
(imgData)

Source from the content-addressed store, hash-verified

113
114# 显示图片
115def display_imageData(imgData):
116 sum = 0
117 '''
118 显示100个数(若是一个一个绘制将会非常慢,可以将要画的图片整理好,放到一个矩阵中,显示这个矩阵即可)
119 - 初始化一个二维数组
120 - 将每行的数据调整成图像的矩阵,放进二维数组
121 - 显示即可
122 '''
123 m,n = imgData.shape
124 width = np.int32(np.round(np.sqrt(n)))
125 height = np.int32(n/width);
126 rows_count = np.int32(np.floor(np.sqrt(m)))
127 cols_count = np.int32(np.ceil(m/rows_count))
128 pad = 1
129 display_array = -np.ones((pad+rows_count*(height+pad),pad+cols_count*(width+pad)))
130 for i in range(rows_count):
131 for j in range(cols_count):
132 max_val = np.max(np.abs(imgData[sum,:]))
133 display_array[pad+i*(height+pad):pad+i*(height+pad)+height,pad+j*(width+pad):pad+j*(width+pad)+width] = imgData[sum,:].reshape(height,width,order="F")/max_val # order=F指定以列优先,在matlab中是这样的,python中需要指定,默认以行
134 sum += 1
135
136 plt.imshow(display_array,cmap='gray') #显示灰度图像
137 plt.axis('off')
138 plt.show()
139
140if __name__ == "__main__":
141 PCA_2D()

Callers 1

PCA_faceImageFunction · 0.70

Calls

no outgoing calls

Tested by

no test coverage detected