TensorFlow-Slim 图像分类库

TF-slim是用于定义，训练和评估复杂模型的TensorFlow（tensorflow.contrib.slim）的新型轻量级高级API。 该目录包含用于训练和评估使用TF-slim的几种广泛使用的卷积神经网络（CNN）图像分类模型的代码。 它包含脚本，允许您从头开始训练模型或从预训练的网络权重微调它们。 它还包含用于下载标准图像数据集的代码，将其转换为TensorFlow 的原生 TFRecord 格式，并使用 TF-Slim 的数据读取和序列实用程序进行读取。 您可以轻松地对任何这些数据集上的任何模型进行训练，如下所示。 我们还包括一个jupyter notebook，它提供了如何使用TF-Slim进行图像分类的工作示例。

TF-slim is a new lightweight high-level API of TensorFlow (tensorflow.contrib.slim) for defining, training and evaluating complex models. This directory contains code for training and evaluating several widely used Convolutional Neural Network (CNN) image classification models using TF-slim. It contains scripts that will allow you to train models from scratch or fine-tune them from pre-trained network weights. It also contains code for downloading standard image datasets, converting them to TensorFlow’s native TFRecord format and reading them in using TF-Slim’s data reading and queueing utilities. You can easily train any model on any of these datasets, as we demonstrate below. We’ve also included a jupyter notebook, which provides working examples of how to use TF-Slim for image classification.

项目地址：https://github.com/tensorflow/models/tree/master/slim
tensorflownews
http://www.tensorflownews.com