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https://github.com/tesseract-ocr/tesseract.git
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62 lines
2.6 KiB
Protocol Buffer
62 lines
2.6 KiB
Protocol Buffer
syntax = "proto3";
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package tesseract;
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// TODO(rays) How to make this usable both in Google and open source?
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import "third_party/tensorflow/core/framework/graph.proto";
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// This proto is the interface between a python TF graph builder/trainer and
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// the C++ world. The writer of this proto must provide fields as documented
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// by the comments below.
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// The graph must have a placeholder for NetworkIO, Widths and Heights. The
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// following python code creates the appropriate placeholders:
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//
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// input_layer = tf.placeholder(tf.float32,
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// shape=[batch_size, xsize, ysize, depth_dim],
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// name='NetworkIO')
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// widths = tf.placeholder(tf.int32, shape=[batch_size], name='Widths')
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// heights = tf.placeholder(tf.int32, shape=[batch_size], name='Heights')
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// # Flip x and y to the TF convention.
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// input_layer = tf.transpose(input_layer, [0, 2, 1, 3])
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//
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// The widths and heights will be set to indicate the post-scaling size of the
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// input image(s).
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// For now batch_size is ignored and set to 1.
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// The graph should return a 2-dimensional float32 tensor called 'softmax' of
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// shape [sequence_length, num_classes], where sequence_length is allowed to
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// be variable, given by the tensor itself.
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// TODO(rays) determine whether it is worth providing for batch_size >1 and if
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// so, how.
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message TFNetworkModel {
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// The TF graph definition. Required.
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tensorflow.GraphDef graph = 1;
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// The training index. Required to be > 0.
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int64 global_step = 2;
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// The original network definition for reference. Optional
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string spec = 3;
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// Input tensor parameters.
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// Values per pixel. Required to be 1 or 3. Inputs assumed to be float32.
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int32 depth = 4;
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// Image size. Required. Zero implies flexible sizes, fixed if non-zero.
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// If x_size > 0, images will be cropped/padded to the given size, after
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// any scaling required by the y_size.
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// If y_size > 0, images will be scaled isotropically to the given height.
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int32 x_size = 5;
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int32 y_size = 6;
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// Number of images in a batch. Optional.
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int32 batch_size = 8;
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// Output tensor parameters.
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// Number of output classes. Required to match the depth of the softmax.
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int32 num_classes = 9;
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// True if this network needs CTC-like decoding, dropping duplicated labels.
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// The decoder always drops the null character.
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bool using_ctc = 10;
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// Name of input image tensor.
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string image_input = 11;
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// Name of image height and width tensors.
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string image_widths = 12;
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string image_heights = 13;
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// Name of output (softmax) tensor.
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string output_layer = 14;
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}
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