TensorFlow-Slim image classification library：TensorFlow-Slim 圖像分類庫

TensorFlow-Slim 圖像分類庫

TF-slim是用于定義，訓練和評估複雜模型的TensorFlow（tensorflow.contrib.slim）的新型輕量級進階API。 該目錄包含用于訓練和評估使用TF-slim的幾種廣泛使用的卷積神經網絡（CNN）圖像分類模型的代碼。 它包含腳本，允許您從頭開始訓練模型或從預訓練的網絡權重微調它們。 它還包含用于下載下傳标準圖像資料集的代碼，将其轉換為TensorFlow 的原生 TFRecord 格式，并使用 TF-Slim 的資料讀取和序列實用程式進行讀取。 您可以輕松地對任何這些資料集上的任何模型進行訓練，如下所示。 我們還包括一個jupyter notebook，它提供了如何使用TF-Slim進行圖像分類的工作示例。

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.

項目位址：

https://github.com/tensorflow/models/tree/master/slim

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