我正在尝试使用来自Teachable Machine网站的代码:
from keras.models import load_model
from PIL import Image, ImageOps
import numpy as np
# Load the model
model = load_model('keras_model.h5')
# 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('<IMAGE_PATH>')
#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.ANTIALIAS)
#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)
print(prediction)
但是当运行代码时,我得到以下错误:ModuleNotFoundError: No module named 'tensorflow.compat'
我试着在两台不同的机器上运行代码,卸载并重新安装tensorflow, pip, keras,似乎没有任何帮助。
我使用Python 3.9和tensorflow 2.8.0
这只是发生在我身上,但我弄清楚了。您的.py脚本文件名与tensorflow库的一个文件相同。你可以重命名你的python脚本,它会工作得很好。
您使用的是哪个版本的TensorFlow ?在终端上使用以下命令查看您使用的是哪个版本:
python -c 'import tensorflow as tf; print(tf.__version__)' # for Python 2
python3 -c 'import tensorflow as tf; print(tf.__version__)' # for Python 3
或
>>> import tensorflow as tf
>>> print(tf.__version__)
2.4.1
尝试安装tensorflow==1.15
pip install tensorflow==1.15
import tensorflow.compat.v2 as tf