基于TensorFlow实现色情图片离线识别（离线鉴黄）.zip

<div align="center"> <img src="https://www.tensorflow.org/images/tf_logo_social.png"> </div> ----------------- | **`Documentation`** | |-----------------| | [](https://www.tensorflow.org/api_docs/) | **TensorFlow** is an open source software library for numerical computation using data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device without rewriting code. TensorFlow also includes [TensorBoard](https://github.com/tensorflow/tensorboard), a data visualization toolkit. TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization for the purposes of conducting machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well. TensorFlow provides stable Python and C APIs as well as non-guaranteed backwards compatible API's for C++, Go, Java, JavaScript, and Swift. Keep up to date with release announcements and security updates by subscribing to [announce@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce). ## Installation To install the current release for CPU-only: ``` pip install tensorflow ``` Use the GPU package for CUDA-enabled GPU cards: ``` pip install tensorflow-gpu ``` *See [Installing TensorFlow](https://www.tensorflow.org/install) for detailed instructions, and how to build from source.* People who are a little more adventurous can also try our nightly binaries: **Nightly pip packages** * We are pleased to announce that TensorFlow now offers nightly pip packages under the [tf-nightly](https://pypi.python.org/pypi/tf-nightly) and [tf-nightly-gpu](https://pypi.python.org/pypi/tf-nightly-gpu) project on PyPi. Simply run `pip install tf-nightly` or `pip install tf-nightly-gpu` in a clean environment to install the nightly TensorFlow build. We support CPU and GPU packages on Linux, Mac, and Windows. #### *Try your first TensorFlow program* ```shell $ python ``` ```python >>> import tensorflow as tf >>> tf.enable_eager_execution() >>> tf.add(1, 2).numpy() 3 >>> hello = tf.constant('Hello, TensorFlow!') >>> hello.numpy() 'Hello, TensorFlow!' ``` Learn more examples about how to do specific tasks in TensorFlow at the [tutorials page of tensorflow.org](https://www.tensorflow.org/tutorials/). ## Contribution guidelines **If you want to contribute to TensorFlow, be sure to review the [contribution guidelines](CONTRIBUTING.md). This project adheres to TensorFlow's [code of conduct](CODE_OF_CONDUCT.md). By participating, you are expected to uphold this code.** **We use [GitHub issues](https://github.com/tensorflow/tensorflow/issues) for tracking requests and bugs, please see [TensorFlow Discuss](https://groups.google.com/a/tensorflow.org/forum/#!forum/discuss) for general questions and discussion, and please direct specific questions to [Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow).** The TensorFlow project strives to abide by generally accepted best practices in open-source software development: [](https://bestpractices.coreinfrastructure.org/projects/1486) [](CODE_OF_CONDUCT.md) ## Continuous build status ### Official Builds | Build Type | Status | Artifacts | | --- | --- | --- | | **Linux CPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.html) | [pypi](https://pypi.org/project/tf-nightly/) | | **Linux GPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-gpu-py3.html) | [pypi](https://pypi.org/project/tf-nightly-gpu/) | | **Linux XLA** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.html) | TBA | | **MacOS** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/macos-py2-cc.html) | [pypi](https://pypi.org/project/tf-nightly/) | | **Windows CPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-cpu.html) | [pypi](https://pypi.org/project/tf-nightly/) | | **Windows GPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-gpu.html) | [pypi](https://pypi.org/project/tf-nightly-gpu/) | | **Android** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/android.html) | [](https://bintray.com/google/tensorflow/tensorflow/_latestVersion) | | **Raspberry Pi 0 and 1** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py2.html) [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.html) | [Py2](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp27-none-linux_armv6l.whl) [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv6l.whl) | | **Raspberry Pi 2 and 3** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py2.html) [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html) | [Py2](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp27-none-linux_armv7l.whl) [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl) | ### Community Supported Builds Build Type | Status | Artifacts --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- **Linux s390x** Nightly | [](http://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_CI/) | [Nightly](http://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_CI/) **Linux s390x CPU** Stable Release | [](https://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_Release_Build/) | [Release](https://ibmz-ci.osuosl.org/job/TensorFlow_IBMZ_Release_