代码报错--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-35-480e4084491e> in <cell line: 13>() 12 graph = tf.Graph() 13 with graph.as_default(): ---> 14 od_graph_def = tf.GraphDef() 15 with tf.io.gfile.GFile(model_filename, 'rb') as fid: 16 serialized_graph = fid.read() AttributeError: module 'tensorflow' has no attribute 'GraphDef'
时间: 2023-08-15 14:05:58 浏览: 63
这个错误是因为TensorFlow的版本更新导致的。在最新版本的TensorFlow中,`tf.GraphDef()`已被移除。
为了解决这个问题,你可以尝试使用`tf.compat.v1`模块来替代`tf`模块。下面是修改后的代码:
```python
import cv2
import numpy as np
import urllib.request
import tensorflow.compat.v1 as tf
# 下载DeepLabv3+模型权重文件
model_url = "http://download.tensorflow.org/models/deeplabv3_mnv2_pascal_train_aug_2018_01_29.tar.gz"
tar_filename = "deeplabv3_mnv2_pascal_train_aug.tar.gz"
urllib.request.urlretrieve(model_url, tar_filename)
# 解压缩
with tarfile.open(tar_filename, "r:gz") as tar:
tar.extractall()
model_filename = "deeplabv3_mnv2_pascal_train_aug/frozen_inference_graph.pb"
# 加载模型
graph = tf.Graph()
with graph.as_default():
od_graph_def = tf.compat.v1.GraphDef()
with tf.io.gfile.GFile(model_filename, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')
# 读取图像
image_path = "your_image.jpg"
image = cv2.imread(image_path)
# 进行图像分割
with tf.compat.v1.Session(graph=graph) as sess:
input_tensor = graph.get_tensor_by_name('ImageTensor:0')
output_tensor = graph.get_tensor_by_name('SemanticPredictions:0')
output = sess.run(output_tensor, feed_dict={input_tensor: image})
# 解码并可视化分割结果
segmentation_mask = np.squeeze(output)
segmentation_mask = np.uint8(segmentation_mask)
segmentation_mask = cv2.resize(segmentation_mask, (image.shape[1], image.shape[0]), interpolation=cv2.INTER_NEAREST)
# 显示原始图像和分割结果
cv2.imshow("Image", image)
cv2.imshow("Segmentation Mask", segmentation_mask)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
请确保你已经安装了兼容的TensorFlow版本,并重新运行代码。如果你仍然遇到问题,请告诉我,我会尽力帮助你解决。