TensorFlow是一个深度学习框架，支持Linux平台，Windows平台，Mac平台，甚至手机移动设备等各种平台。TensorFlow提供了非常丰富的深度学习相关的API，可以说目前所有深度学习框架里，提供的API最全的，包括基本的向量矩阵计算、各种优化算法、各种卷积神经网络和循环神经网络基本单元的实现、以及可视化的辅助工具、等等。
基于TensorFlow的API是可以做其它语言绑定的，目前只有Python语言绑定是谷歌公司官方推荐和支持的，实现的功能也是最权威最完整的。除了对Python的大力支持外，其它语言的绑定就显得非常弱小，几乎不能用。TensorFlow.NET是用C#语言对TensorFlow API进行绑定，并最大化保持Python的接口使用习惯，让其它模型代码能快速的迁移到.NET。
v0.3.0主要是新增了一个图像识别的示例程序和修复一些Bug。具体代码可以参考TensorFlowNET.Examples的LabelImage的样例。
private NDArray ReadTensorFromImageFile(string file_name,
int input_height = 299,
int input_width = 299,
int input_mean = 0,
int input_std = 255)
{
return with<Graph, NDArray>(tf.Graph().as_default(), graph =>
{
var file_reader = tf.read_file(file_name, "file_reader");
var image_reader = tf.image.decode_jpeg(file_reader, channels: 3, name: "jpeg_reader");
var caster = tf.cast(image_reader, tf.float32);
var dims_expander = tf.expand_dims(caster, 0);
var resize = tf.constant(new int[] { input_height, input_width });
var bilinear = tf.image.resize_bilinear(dims_expander, resize);
var sub = tf.subtract(bilinear, new float[] { input_mean });
var normalized = tf.divide(sub, new float[] { input_std });
return with<Session, NDArray>(tf.Session(graph), sess => sess.run(normalized));
});
}
2/18/2019 2:49:18 AM Starting LabelImage label_image_data\inception_v3_2016_08_28_frozen.pb.tar.gz already exists. label_image_data\grace_hopper.jpg already exists. 2019-02-18 20:49:19.499758: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 create_op: Const 'file_reader/filename', inputs: empty, control_inputs: empty, outputs: file_reader/filename:0 create_op: ReadFile 'file_reader', inputs: file_reader/filename:0, control_inputs: empty, outputs: file_reader:0 create_op: DecodeJpeg 'jpeg_reader', inputs: file_reader:0, control_inputs: empty, outputs: jpeg_reader:0 create_op: Cast 'Cast/Cast', inputs: jpeg_reader:0, control_inputs: empty, outputs: Cast/Cast:0 create_op: Const 'ExpandDims/dim', inputs: empty, control_inputs: empty, outputs: ExpandDims/dim:0 create_op: ExpandDims 'ExpandDims', inputs: Cast/Cast:0, ExpandDims/dim:0, control_inputs: empty, outputs: ExpandDims:0 create_op: Const 'Const', inputs: empty, control_inputs: empty, outputs: Const:0 create_op: ResizeBilinear 'ResizeBilinear', inputs: ExpandDims:0, Const:0, control_inputs: empty, outputs: ResizeBilinear:0 create_op: Const 'y', inputs: empty, control_inputs: empty, outputs: y:0 create_op: Sub 'Sub', inputs: ResizeBilinear:0, y:0, control_inputs: empty, outputs: Sub:0 create_op: Const 'y_1', inputs: empty, control_inputs: empty, outputs: y_1:0 create_op: RealDiv 'truediv', inputs: Sub:0, y_1:0, control_inputs: empty, outputs: truediv:0 grace_hopper.jpg: 653 military uniform, 0.8343058 grace_hopper.jpg: 668 mortarboard, 0.02186947 grace_hopper.jpg: 401 academic gown, 0.01035806 grace_hopper.jpg: 716 pickelhaube, 0.008008132 grace_hopper.jpg: 466 bulletproof vest, 0.005350832 2/19/2019 2:49:26 AM Completed LabelImage
文档地址：Document
仓库地址: Github
聊天室: Gitter
软件下载地址：NuGet