我是一个初学者TensorFlow用户，在尝试加载已经保存的模型用于测试图像的分割时遇到以下问题:
我在我创建的虚拟环境中安装了所有的库。
同样的代码运行在google colab上，现在我正试图在我的机器上运行它。
My Environment
ubuntu16/tensorflow 2.5.0
我的代码
运行代码时:
import os
from glob import glob
from tqdm import tqdm
import cv2
import tensorflow as tf
import nibabel as nib
import numpy as np
import matplotlib.pyplot as plt
test_images = sorted(glob("/mnt/DATA2To/projet/all/Souris/SOD/data/20210726_C321/EXVIVO/IRM/test-20210726_C321/*")) # images 160x120x1
i = 0 # iterator initialized to zero
model = tf.keras.models.load_model("/mnt/DATA2To/projet/all/Souris/SOD/segmentation/segmentation-moelle.h5", compile= False )
`
for path in tqdm(test_images, total=len(test_images)):
x = nib.load(path) # load the images (160x1x120)
new_header = header=x.header.copy() # copy the header to a variable for writing the results at the end
x = nib.load(path).get_data() # get the data from the image loaded
original_image = x
original_image_bis = original_image.transpose((0,2,1))
h, w, _ = original_image_bis.shape
original_image_bis = cv2.resize(original_image_bis, (w, h))
x = x.transpose((0,2,1)) # permute the image axes to (160x120x1)
x = cv2.resize(x, (128, 128)) # resize the image to have a shape of (128x128)
x = (x - x.min()) / (x.max() - x.min()) # do the min-max normalisation
x.shape= x.shape + (1,) # add the third axes (128x128x1)
x = x.astype(np.float32)
x1 = np.expand_dims(x, axis=0)
pred_mask = model.predict(x1)[0]
#pred_mask = (np.where(pred_mask > np.mean(pred_mask), 1,0))
pred_mask = pred_mask.astype(np.float32)
pred_mask1 = cv2.resize(pred_mask, (w, h))
pred_mask1 = (np.where(pred_mask1 > 0.92, 1,0))
pred_mask1.shape= pred_mask1.shape + (1,) # add the third axes (160x120x1)
pred_mask1 = pred_mask1.transpose((0,2,1)) #permute the image axes to (160x1x120)
Sform= new_header.get_base_affine()
pred_mask2 = nib.Nifti1Image(pred_mask1,None, header= new_header)
fname= "/mnt/DATA2To/projet/all/Souris/SOD/data/20210726_C321/EXVIVO/IRM/results-moelle/image%04d.nii" %i
nib.save(pred_mask2, fname)
i+=1
我的错误
我看到这个错误:
(venv) etudiant@PTT:~$ python3 '/home/etudiant/Documents/code/Segmentation.py'
2021-07-28 09:58:12.539200: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /mnt/software//mrtrix/lib::/opt/minc/lib:/opt/minc/lib/InsightToolkit
2021-07-28 09:58:12.539221: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2021-07-28 09:58:13.429146: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /mnt/software//mrtrix/lib::/opt/minc/lib:/opt/minc/lib/InsightToolkit
2021-07-28 09:58:13.429164: W tensorflow/stream_executor/cuda/cuda_driver.cc:326] failed call to cuInit: UNKNOWN ERROR (303)
2021-07-28 09:58:13.429179: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (PTT): /proc/driver/nvidia/version does not exist
2021-07-28 09:58:13.429322: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
0it [00:00, ?it/s]
谁能告诉我什么是错的，如何解决这个问题!?
W代表"警告";I代表"信息">
你的代码没有问题，TF只是告诉你没有找到GPU计算所需的库;这并不意味着TensorFlow不能在CPU上成功运行。
为了避免在将来收到这样的消息，你可以做的是抑制警告。
解决方案1:
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import tensorflow as tf
级别2表示忽略警告和信息，只打印错误。
解决方案2:
import tensorflow as tf
tf.logging.set_verbosity(tf.logging.ERROR)
解决方案3:
import logging
tf.get_logger().setLevel(logging.ERROR)