tensorflow:如何计算RGB值和单方差的零均值与

import tensorflow as tf

# 创建一个形状为 (3, 3, 3) 的随机 RGB 张量
rgb_tensor = tf.random.normal(shape=(3, 3, 3))

# 计算每个通道的零均值
mean_values, variance_values = tf.nn.moments(rgb_tensor, axes=(0, 1), keepdims=True)

# 计算中心化后的 RGB 张量
centered_rgb_tensor = rgb_tensor - mean_values

# 计算标准化后的 RGB 张量
normalized_rgb_tensor = centered_rgb_tensor / tf.sqrt(variance_values + 1e-8)  # 添加一个很小的值以避免除以0的情况

# 打印结果
print("Original RGB tensor:")
print(rgb_tensor.numpy())
print("
Mean values for each channel:")
print(mean_values.numpy())
print("
Variance values for each channel:")
print(variance_values.numpy())
print("
Centered RGB tensor:")
print(centered_rgb_tensor.numpy())
print("
Normalized RGB tensor:")
print(normalized_rgb_tensor.numpy())