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@ -177,7 +177,7 @@ the main training process, with command-lines that have been tested for real. On
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Linux at least, you should be able to just copy-paste the command lines into
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Linux at least, you should be able to just copy-paste the command lines into
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your terminal. To make the `tesstrain.sh` script work, it will be necessary to
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your terminal. To make the `tesstrain.sh` script work, it will be necessary to
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either set `PATH` to include your local `training` and `api` directories, or use
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either set `PATH` to include your local `training` and `api` directories, or use
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`make install.`
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`make install`.
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# Creating Training Data
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# Creating Training Data
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@ -297,7 +297,7 @@ end. This is entirely contrary to the way base Tesseract is trained!
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If using the rendering code, (via `tesstrain.sh`) then it will shuffle the
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If using the rendering code, (via `tesstrain.sh`) then it will shuffle the
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sample text lines within each file, but you will get a set of files, each
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sample text lines within each file, but you will get a set of files, each
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containing training samples from a single font. To add a more even mix at least,
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containing training samples from a single font. To add a more even mix at least,
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you should use the `16` flag value for `train_mode,` *even if you don't want the
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you should use the `16` flag value for `train_mode`, *even if you don't want the
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unicharset compressed.*
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unicharset compressed.*
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### Model output
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### Model output
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@ -329,13 +329,13 @@ that many imperfect ones seen since the last perfect sample.
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### Debug Interval and Visual Debugging
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### Debug Interval and Visual Debugging
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With zero (default) `--debug_interval,` the trainer outputs a progress report
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With zero (default) `--debug_interval`, the trainer outputs a progress report
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every 100 iterations.
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every 100 iterations.
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With `--debug_interval -1,` the trainer outputs verbose text debug for every
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With `--debug_interval -1`, the trainer outputs verbose text debug for every
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training iteration.
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training iteration.
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With `--debug_interval > 0,` the trainer displays several windows of debug
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With `--debug_interval > 0`, the trainer displays several windows of debug
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information on the layers of the network. In the special case of
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information on the layers of the network. In the special case of
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`--debug_interval 1` it waits for a click in the `LSTMForward` window before
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`--debug_interval 1` it waits for a click in the `LSTMForward` window before
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continuing to the next iteration, but for all others it just continues and draws
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continuing to the next iteration, but for all others it just continues and draws
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@ -367,7 +367,7 @@ expect from the bottom layer.
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lines are drawn to show the peak output for each character, and the character
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lines are drawn to show the peak output for each character, and the character
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itself is drawn to the right of the line.
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itself is drawn to the right of the line.
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The other two windows worth looking at are `CTC Outputs` and `CTC Targets.`
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The other two windows worth looking at are `CTC Outputs` and `CTC Targets`.
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These show the current output of the network and the targets as a line graph of
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These show the current output of the network and the targets as a line graph of
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strength of output against image x-coordinate. Instead of a heatmap, like the
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strength of output against image x-coordinate. Instead of a heatmap, like the
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`Output` window, a different colored line is drawn for each character class and
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`Output` window, a different colored line is drawn for each character class and
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@ -399,8 +399,8 @@ You should observe that by 500 iterations, the spaces (white) are starting to
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show on the `CTC Outputs` window and by 800 iterations green lines appear on
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show on the `CTC Outputs` window and by 800 iterations green lines appear on
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the `LSTMForward` window where there are spaces in the image.
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the `LSTMForward` window where there are spaces in the image.
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By 600 iterations, there are noticeable non-space bumps in the `CTC Outputs.`
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By 600 iterations, there are noticeable non-space bumps in the `CTC Outputs`.
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Note that the `CTC Targets,` which started at all the same height are now varied
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Note that the `CTC Targets`, which started at all the same height are now varied
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in height because of the definite output for spaces. At the same time, the
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in height because of the definite output for spaces. At the same time, the
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characters and positioning of the green lines in the `LSTMTraining` window are
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characters and positioning of the green lines in the `LSTMTraining` window are
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not as accurate as they once were, because the partial output from the network
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not as accurate as they once were, because the partial output from the network
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@ -569,7 +569,7 @@ layers of an existing network model, replace some of them with new randomized
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layers, and train with your data. The command-line is mostly the same as
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layers, and train with your data. The command-line is mostly the same as
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[Training from scratch](#training-from-scratch), as you have to supply a
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[Training from scratch](#training-from-scratch), as you have to supply a
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unicharset and net_spec, and you also have to provide a model to
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unicharset and net_spec, and you also have to provide a model to
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`--continue_from` and `--append_index.`
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`--continue_from` and `--append_index`.
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The `--append_index` argument tells it to remove all layers **above** the layer
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The `--append_index` argument tells it to remove all layers **above** the layer
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with the given index, (starting from zero, in the outermost series) and then
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with the given index, (starting from zero, in the outermost series) and then
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@ -744,7 +744,7 @@ The dawg files are optional. It will work without them, but they do usually
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provide some small improvement in accuracy.
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provide some small improvement in accuracy.
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**NOTE** Tesseract 4.00 will now run happily with a traineddata file that
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**NOTE** Tesseract 4.00 will now run happily with a traineddata file that
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contains *just* `lang.lstm.` The `lstm-*-dawgs` are optional, and *none of the
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contains *just* `lang.lstm`. The `lstm-*-dawgs` are optional, and *none of the
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other files are required or used with OEM_LSTM_ONLY as the OCR engine mode.*
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other files are required or used with OEM_LSTM_ONLY as the OCR engine mode.*
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No bigrams, unichar ambigs or any of the other files are needed or even have
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No bigrams, unichar ambigs or any of the other files are needed or even have
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any effect if present.
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any effect if present.
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