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| import cv2
import matplotlib.pyplot as plt
import numpy as np
import os
def get_imgs(path:str):
img_files = os.listdir(path)
result = []
for file in img_files:
file = os.path.join(path,file)
img = cv2.imread(file)
img = cv2.resize(img,(150,150))
img = img.transpose(2,0,1)
result.append(img)
return np.array(result)
def conv(imgs,kernel):
out_channel,in_channel,kernel_h,kernel_w = kernel.shape
img_num,_,img_h,img_w = imgs.shape
c_w = img_w - kernel_w + 1
c_h = img_h - kernel_h + 1
A = kernel.reshape(out_channel,-1)
B = np.zeros((img_num,A.shape[1],c_w*c_h))
c = 0
for h in range(c_h):
for w in range(c_w):
d = imgs[:,:,h:h+kernel_h,w:w+kernel_w]
d = d.reshape(img_num,-1)
B[:,:,c] = d
c += 1
result = A @ B
result = result.reshape(img_num,out_channel,c_h,c_w)
return result
if __name__ =="__main__":
kernel = np.array([
[
[
[-1, -2, -3],
[-1, -2, -3],
[-1, -10, 1]
],
[
[0, 3, 3],
[-1, -2, -3],
[1, 1, 1]
],
[
[3, 3, 3],
[-1, -9, 0],
[-1, -2, -3]
]
],
[
[
[1, -1, 0],
[1, -1, 0],
[1, -1, 0]
],
[
[1, -1, 0],
[1, -1, 0],
[1, -1, 0]
],
[
[1, -1, 0],
[1, -1, 0],
[1, -1, 0]
]
],
])
imgs = get_imgs("img")
result = conv(imgs,kernel)
for j in i:
plt.imshow(j,cmap="gray")
plt.show()
|
