TensorFlow Object Detection API tutorialtensorflow-object-detection-api-tutorial.readthedocs.io/en/v1.9.1/ 在纠正本教程时,对象检测模型培训和评估未迁移到TensorFlow 2.x。从个人测试来看,使用预先训练的模型进行检测似乎是可行的,但是还不可能训练和评估模型。迁移完成后,将生成TensorFlow 2.x的版本。 tenso...
Together, these features make TensorFlow the perfect framework for machine intelligence at a production scale. In this TensorFlow tutorial, you will learn how you can use simple yet powerful machine learning methods in TensorFlow and how you can use some of its auxiliary libraries to debug, visuali...
在object_detection目录下面找到object_detection_tutorial.ipynb文件 在liunx服务器上执行jupyter notebook需要使用到浏览器,由于本机没有安装,该部分暂时没有显示 执行步骤: 1 jupyter notebook --ip=0.0.0.0 --port=8080 会出现: 使用提供的URL访问文件夹object_detection,运行object_detection_tutorial.ipynb,一步步...
$ sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.8.0-cp27-none-linux_x86_64.whl # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7. Requires CUDA toolkit 7.5 and CuDNN v4. # For other versions, see "Install from sources" below. $ sudo pip in...
CPU performance is faster than GPU on your network. Find out if your workload is sufficient to take advantage of the GPU. On small networks running with small batch sizes, the CPU may perform faster overall due to the overhead related to dispatching computations to the GPU. This will get ...
This message shows that your installation appears to be working correctly. To generate this message, Docker took the following steps: 1\. The Docker client contacted the Docker daemon. 2\. The Docker daemon pulled the "hello-world" image from the Docker Hub. (amd64) 3\. The Docker daemon...
In this tutorial, you’ll install TensorFlow’s “CPU support only” version. This installation is ideal for people looking to install and use TensorFlow, but who don’t have an Nvidia graphics card or don’t need to run performance-critical applications. ...
Monte Carlo (tfp.monte_carlo): Tools for computing Monte Carlo expectations. TensorFlow Probability is under active development. Interfaces may change at any time. Examples Seetensorflow_probability/examples/for end-to-end examples. It includes tutorial notebooks such as: ...
Before running the model, you need to prepare the training data and bucket for storing checkpoints. Refer to theTransformer tutorialto learn how to generate the training data and create buckets. CONF=mtf_transformer_paper_tr_0_mesh_8
从这里选择object_detection_tutorial.ipynb。 从这里,你应该能在主菜单中运行单元格,并选择全部运行。 你应该得到以下结果: 在下一个教程中,我们将介绍,如何通过稍微修改此示例代码,来实时标注来自网络摄像头流的数据。 二、视频流的目标检测 欢迎阅读 TensorFlow 目标检测 API 教程的第二部分。 在本教程中,我们将...