二值图像利用bp神经网络进行图像边缘提取的python代码
时间: 2023-07-16 09:16:01 浏览: 108
我可以为您提供一些关于利用bp神经网络进行图像边缘提取的Python代码的参考。这里是一个简单的代码段:
```python
import numpy as np
import matplotlib.pyplot as plt
from sklearn.neural_network import MLPRegressor
from skimage.filters import sobel
# Load image data
img = plt.imread('image.jpg',0)
img = np.pad(img, pad_width=1, mode='constant', constant_values=0)
height, width = img.shape
# Compute the Sobel edges of the image
edges = sobel(img)
# Reshape the input data
X = np.zeros((height*width, 9))
count = 0
for i in range(1, height-1):
for j in range(1, width-1):
X[count,:] = img[i-1:i+2, j-1:j+2].flatten()
count += 1
# Reshape the output data
y = edges[1:-1,1:-1].flatten()
# Train the MLP regressor
clf = MLPRegressor(hidden_layer_sizes=(10,),max_iter=500)
clf.fit(X, y)
# Predict the edges using the MLP regressor
y_pred = clf.predict(X)
edges_pred = np.reshape(y_pred, (height-2, width-2))
# Plot the original image and the predicted edges
fig, axs = plt.subplots(1,2,figsize=(10,10))
axs[0].imshow(img, cmap='gray')
axs[1].imshow(edges_pred, cmap='gray')
```
请注意,这只是一个简单的代码示例,可能需要对您的数据进行一些修改和优化以获得更好的结果。希望这可以帮助到您!
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