pathon代码实现老照片修复
时间: 2023-12-10 16:04:59 浏览: 74
很高兴回答您的问题!老照片修复是一个非常有趣的话题。以下是一些python代码示例,可以用来实现老照片修复:
1.使用opencv库
```python
import cv2
def restore_image(image_path):
# 加载图像
img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
# 降噪处理
img = cv2.medianBlur(img, 5)
# 缺失部分修复
img = cv2.inpaint(img, cv2.inRange(img, 240, 255), 3, cv2.INPAINT_TELEA)
return img
```
2.使用tensorflow库
```python
import tensorflow as tf
import numpy as np
def restore_image(image_path):
# 加载图像
img = tf.io.read_file(image_path)
img = tf.image.decode_jpeg(img, channels=1)
img = tf.image.convert_image_dtype(img, tf.float32)
# 缺失部分修复
mask = tf.math.greater(img, 0)
img = tf.where(mask, img, tf.random.normal(tf.shape(img)))
inpainted = tf.zeros_like(img)
for i in range(5):
model = tf.keras.Sequential([
tf.keras.layers.Conv2D(64, kernel_size=3, padding='same', activation=tf.nn.relu),
tf.keras.layers.Conv2D(64, kernel_size=3, padding='same', activation=tf.nn.relu),
tf.keras.layers.Conv2D(32, kernel_size=3, padding='same', activation=tf.nn.relu),
tf.keras.layers.Conv2D(1, kernel_size=3, padding='same', activation=tf.nn.relu),
])
model.compile(optimizer='adam', loss='mse')
model.fit(x=img, y=inpainted, epochs=1, batch_size=1)
inpainted = model(img)
# 转化数据类型
inpainted = tf.image.convert_image_dtype(inpainted, tf.uint8)
return inpainted.numpy()[:, :, 0]
```
希望这些代码可以帮助您实现您的老照片修复!