我做了一个模型，可以检测一个人的脸是朝右、朝左还是朝中间，我用下面的代码做了一个预测：

from keras.models import load_model
from PIL import Image, ImageOps
import numpy as np

# Disable scientific notation for clarity
np.set_printoptions(suppress=True)

# Load the model
model = load_model('models//keras_Model.h5', compile=False)

# Load the labels
class_names = open('models//labels.txt', 'r').readlines()

# Create the array of the right shape to feed into the keras model
# The 'length' or number of images you can put into the array is
# determined by the first position in the shape tuple, in this case 1.
data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)

# Replace this with the path to your image
image = Image.open('IMG.png').convert('RGB')

# resize the image to a 224x224 with the same strategy as in TM2:
# resizing the image to be at least 224x224 and then cropping from the center
size = (224, 224)
image = ImageOps.fit(image, size, Image.Resampling.LANCZOS)

# turn the image into a numpy array
image_array = np.asarray(image)

# Normalize the image
normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1

# Load the image into the array
data[0] = normalized_image_array

# run the inference

prediction = model.predict(data)
index = np.argmax(prediction)
class_name = class_names[index]
confidence_score = prediction[0][index]

print('Class:', class_name, end='')
print('Confidence score:', confidence_score)

这段代码给出了正确的预测，下面是labels.txt文件：

0 Left_Side_Face
1 Middle_Face
2 Right_Side_Face

我现在想做的是说，例如，人已经把他们的头转向右侧，我想打印的消息'面对电脑'，但当我尝试这样做，我失败了。
下面是我尝试的代码：

if class_name == "2 Right_Side_Face":
    print('face the computer')
if class_name == "0 Left_Side_Face":
    print('face the computer')
else:
    print('Invalid class name')
    print('exiting.....')

问题是，每当我运行上面的代码时，它都会转到else并打印"Invalid class name"，当我删除else时，代码中没有错误，它只是跳过if语句。

• • 问题：**

当TensorFlow模型检测到特定类时，如何执行操作（打印消息、警报等）？
编辑：下面是我给模型输入右侧脸图像时脚本的输出：

Class: 2 Right_Side_Face
Confidence score: 0.84736574
Invalid class name
exiting....