python实现朴素的卷积操作

import numpy as npimport os# 朴素的卷积
def conv_naive(x, w):N,H,W,C &＃61; x.shapeKh, Kw, _C, Kc &＃61; w.shapeassert(C&＃61;&＃61;_C), (x.shape, w.shape)# stride is 1y&＃61; np.zeros([N, H-Kh &＃43;1, W-Kw&＃43;1, Kc])for i0 in range(N):for i1 in range(H - Kh &＃43; 1):for i2 in range(W - Kw &＃43; 1):for i3 in range(Kh):for i4 in range(Kw):for i5 in range(C):for i6 in range(Kc):if i1 - i3 < 0 or i2 - i4 < 0 or i1 - i3 >&＃61; H or i2 - i4 >&＃61; W: continuey[i0, i1, i2, i6] &＃43;&＃61; x[i0, i1 &＃43; i3, i2 &＃43; i4, i5] * w[i3, i4, i5, i6]return y# %matplotlib inline
import pylab as pl
import PIL.Image as Image
import sys
import subprocess
img_path&＃61;"cat.jpg"
if not os.path.isfile(img_path):cmd &＃61; f"""wget -O - &＃39;https://upload.wikimedia.org/wikipedia/commons/thumb/4/4f/Felis_silvestris_catus_lying_on_rice_straw.jpg/220px-Felis_silvestris_catus_lying_on_rice_straw.jpg&＃39; > {img_path}"""# subprocess.run(cmd)
im&＃61;Image.open(img_path)
im.show()
img &＃61; pl.imread(img_path)kernel &＃61; np.array([[-1, -1, -1],[0, 0, 0],[1, 1, 1],
])
x &＃61; img[np.newaxis,:,:,:1].astype("float32")
w &＃61; kernel[:,:,np.newaxis,np.newaxis].astype("float32")y &＃61; conv_naive(x, w)
print (x.shape, y.shape) # shape exists confusionimg &＃61; Image.fromarray(y[0,:,:,:], mode&＃61;&＃39;RGB&＃39;)
img.show()


输出&＃xff1a;
(1, 147, 220, 1) (1, 145, 218, 1)