Python tensorflow计算tf.nn.conv2d
我在Excel中手动计算了3x3图像和两个2x2过滤器之间的卷积: 我想使用tensorflowPython tensorflow计算tf.nn.conv2d,python,tensorflow,convolution,Python,Tensorflow,Convolution,我在Excel中手动计算了3x3图像和两个2x2过滤器之间的卷积: 我想使用tensorflowtf.nn.conv2d: x_raw = np.array([ [2,5,3], [3,4,2], [4,1,1] ]) f_raw = np.array( [[ [2,1], [3,4] ],[ [4,1], [1,2] ]]) f = tf.constant(f_raw, dtype=tf.float32) x = tf.con
tf.nn.conv2d:
x_raw = np.array([
[2,5,3],
[3,4,2],
[4,1,1]
])
f_raw = np.array(
[[
[2,1],
[3,4]
],[
[4,1],
[1,2]
]])
f = tf.constant(f_raw, dtype=tf.float32)
x = tf.constant(x_raw, dtype=tf.float32)
filter = tf.reshape(f, [2, 2, 1, 2])
image = tf.reshape(x, [1, 3, 3, 1])
tf.nn.conv2d(image, filter, [1, 1, 1, 1], "VALID").eval()
但是tensorflow的输出是关闭的:
数组([[35,33.],[37,25.],[[35,25.],[19,15.]],dtype=float32)
我做错了什么?要获得与excel示例相同的结果,您需要进行以下更改:
x_raw = np.array([
[2,5,3],
[3,4,2],
[4,1,1]
])
#created two seperate weights
weight1 = np.array(
[[
[2,1],
[3,4]
]])
weight2 = np.array(
[[
[4,1],
[1,2]
]]
)
weight1 = tf.constant(weight1, dtype=tf.float32)
weight2 = tf.constant(weight2, dtype=tf.float32)
x = tf.constant(x_raw, dtype=tf.float32)
#change out_channels to 1
filter1 = tf.reshape(weight1, [2, 2, 1, 1])
filter2 = tf.reshape(weight2, [2, 2, 1, 1])
image = tf.reshape(x, [1, 3, 3, 1])
with tf.Session() as sess:
print(tf.nn.conv2d(image, filter1, [1, 1, 1, 1], "VALID").eval())
print(tf.nn.conv2d(image, filter2, [1, 1, 1, 1], "VALID").eval())
谢谢你,先生。但在我的例子中它在做什么呢?