search

tesseract-ocr / tesstrain

Train Tesseract LSTM with make
Apache License 2.0
620 stars 181 forks source link

How do I adjust my data to an existing model via make? #198

Closed ryancarloscorrea closed 3 years ago

ryancarloscorrea commented 3 years ago

I have the .png, .gt.txt files. box, .lstmf. I have already managed to generate .traineddata, but it is very bad on my own ... I would like to add my training data to an existing model, it would be por.traineddata (portuguese). How do I do this with make? already seen in the documentation, in the forum. but nothing worked for me.

I cannot share my .pgn and .gt.txt as they are confidential files... data-training.zip

Where should I change in the makefile to train with my images from por.traineddata?

my Makefile: 

export

## Make sure that sort always uses the same sort order.
LC_ALL := C

SHELL := /bin/bash
LOCAL := $(PWD)/usr
PATH := $(LOCAL)/bin:$(PATH)

# Path to the .traineddata directory with traineddata suitable for training 
# (for example from tesseract-ocr/tessdata_best). Default: $(LOCAL)/share/tessdata
TESSDATA =  $(LOCAL)/share/tessdata

# Name of the model to be built. Default: $(MODEL_NAME)
MODEL_NAME = foo

# Data directory for output files, proto model, start model, etc. Default: $(DATA_DIR)
DATA_DIR = data

# Output directory for generated files. Default: $(OUTPUT_DIR)
OUTPUT_DIR = $(DATA_DIR)/$(MODEL_NAME)

# Optional Wordlist file for Dictionary dawg. Default: $(WORDLIST_FILE)
WORDLIST_FILE := $(OUTPUT_DIR)/$(MODEL_NAME).wordlist

# Optional Numbers file for number patterns dawg. Default: $(NUMBERS_FILE)
NUMBERS_FILE := $(OUTPUT_DIR)/$(MODEL_NAME).numbers

# Optional Punc file for Punctuation dawg. Default: $(PUNC_FILE)
PUNC_FILE := $(OUTPUT_DIR)/$(MODEL_NAME).punc

# Name of the model to continue from. Default: '$(START_MODEL)'
START_MODEL =

LAST_CHECKPOINT = $(OUTPUT_DIR)/checkpoints/$(MODEL_NAME)_checkpoint

# Name of the proto model. Default: '$(PROTO_MODEL)'
PROTO_MODEL = $(OUTPUT_DIR)/$(MODEL_NAME).traineddata

# No of cores to use for compiling leptonica/tesseract. Default: $(CORES)
CORES = 4

# Leptonica version. Default: $(LEPTONICA_VERSION)
LEPTONICA_VERSION := 1.80.0

# Tesseract commit. Default: $(TESSERACT_VERSION)
TESSERACT_VERSION := 4.1.1

# Tesseract model repo to use. Default: $(TESSDATA_REPO)
TESSDATA_REPO = _best

# Ground truth directory. Default: $(GROUND_TRUTH_DIR)
GROUND_TRUTH_DIR := $(OUTPUT_DIR)-ground-truth

# Max iterations. Default: $(MAX_ITERATIONS)
MAX_ITERATIONS := 85000
# Debug Interval. Default:  $(DEBUG_INTERVAL)
DEBUG_INTERVAL := 1

# Learning rate. Default: $(LEARNING_RATE)
ifdef START_MODEL
LEARNING_RATE := 0.0001
else
LEARNING_RATE := 0.002
endif

# Network specification. Default: $(NET_SPEC)
NET_SPEC := [1,36,0,1 Ct3,3,16 Mp3,3 Lfys48 Lfx96 Lrx96 Lfx256 O1c\#\#\#]

# Language Type - Indic, RTL or blank. Default: '$(LANG_TYPE)'
LANG_TYPE ?=

# Normalization mode - 2, 1 - for unicharset_extractor and Pass through Recoder for combine_lang_model
ifeq ($(LANG_TYPE),Indic)
    NORM_MODE =2
    RECODER =--pass_through_recoder
    GENERATE_BOX_SCRIPT =generate_wordstr_box.py
else
ifeq ($(LANG_TYPE),RTL)
    NORM_MODE =3
    RECODER =--pass_through_recoder --lang_is_rtl
    GENERATE_BOX_SCRIPT =generate_wordstr_box.py
else
    NORM_MODE =2
    RECODER=
    GENERATE_BOX_SCRIPT =generate_line_box.py
endif
endif

# Page segmentation mode. Default: $(PSM)
PSM = 6

# Random seed for shuffling of the training data. Default: $(RANDOM_SEED)
RANDOM_SEED := 0

# Ratio of train / eval training data. Default: $(RATIO_TRAIN)
RATIO_TRAIN := 0.90

# Default Target Error Rate. Default: $(TARGET_ERROR_RATE)
TARGET_ERROR_RATE := 0.01

# BEGIN-EVAL makefile-parser --make-help Makefile

help:
    @echo ""
    @echo "  Targets"
    @echo ""
    @echo "    unicharset       Create unicharset"
    @echo "    lists            Create lists of lstmf filenames for training and eval"
    @echo "    training         Start training"
    @echo "    traineddata      Create best and fast .traineddata files from each .checkpoint file"
    @echo "    proto-model      Build the proto model"
    @echo "    leptonica        Build leptonica"
    @echo "    tesseract        Build tesseract"
    @echo "    tesseract-langs  Download tesseract-langs"
    @echo "    clean-box        Clean generated .box files"
    @echo "    clean-lstmf      Clean generated .lstmf files"
    @echo "    clean-output     Clean generated output files"
    @echo "    clean            Clean all generated files"
    @echo ""
    @echo "  Variables"
    @echo ""
    @echo "    TESSDATA           Path to the .traineddata directory with traineddata suitable for training "
    @echo "                       (for example from tesseract-ocr/tessdata_best). Default: $(LOCAL)/share/tessdata"
    @echo "    MODEL_NAME         Name of the model to be built. Default: $(MODEL_NAME)"
    @echo "    OUTPUT_DIR         Output directory for generated files. Default: $(OUTPUT_DIR)"
    @echo "    WORDLIST_FILE      Optional Wordlist file for Dictionary dawg. Default: $(WORDLIST_FILE)"
    @echo "    NUMBERS_FILE       Optional Numbers file for number patterns dawg. Default: $(NUMBERS_FILE)"
    @echo "    PUNC_FILE          Optional Punc file for Punctuation dawg. Default: $(PUNC_FILE)"
    @echo "    START_MODEL        Name of the model to continue from. Default: '$(START_MODEL)'"
    @echo "    PROTO_MODEL        Name of the proto model. Default: '$(PROTO_MODEL)'"
    @echo "    CORES              No of cores to use for compiling leptonica/tesseract. Default: $(CORES)"
    @echo "    LEPTONICA_VERSION  Leptonica version. Default: $(LEPTONICA_VERSION)"
    @echo "    TESSERACT_VERSION  Tesseract commit. Default: $(TESSERACT_VERSION)"
    @echo "    TESSDATA_REPO      Tesseract model repo to use. Default: $(TESSDATA_REPO)"
    @echo "    GROUND_TRUTH_DIR   Ground truth directory. Default: $(GROUND_TRUTH_DIR)"
    @echo "    MAX_ITERATIONS     Max iterations. Default: $(MAX_ITERATIONS)"
    @echo "    DEBUG_INTERVAL     Debug Interval. Default:  $(DEBUG_INTERVAL)"
    @echo "    LEARNING_RATE      Learning rate. Default: $(LEARNING_RATE)"
    @echo "    NET_SPEC           Network specification. Default: $(NET_SPEC)"
    @echo "    LANG_TYPE          Language Type - Indic, RTL or blank. Default: '$(LANG_TYPE)'"
    @echo "    PSM                Page segmentation mode. Default: $(PSM)"
    @echo "    RANDOM_SEED        Random seed for shuffling of the training data. Default: $(RANDOM_SEED)"
    @echo "    RATIO_TRAIN        Ratio of train / eval training data. Default: $(RATIO_TRAIN)"
    @echo "    TARGET_ERROR_RATE  Default Target Error Rate. Default: $(TARGET_ERROR_RATE)"

# END-EVAL

.PRECIOUS: $(OUTPUT_DIR)/checkpoints/$(MODEL_NAME)*_checkpoint

.PHONY: clean help leptonica lists proto-model tesseract tesseract-langs training unicharset

ALL_GT = $(OUTPUT_DIR)/all-gt
ALL_LSTMF = $(OUTPUT_DIR)/all-lstmf

# Create unicharset
unicharset: $(OUTPUT_DIR)/unicharset

# Create lists of lstmf filenames for training and eval
lists: $(OUTPUT_DIR)/list.train $(OUTPUT_DIR)/list.eval

$(OUTPUT_DIR)/list.eval \
$(OUTPUT_DIR)/list.train: $(ALL_LSTMF)
    @mkdir -p $(OUTPUT_DIR)
    @total=$$(wc -l < $(ALL_LSTMF)); \
      train=$$(echo "$$total * $(RATIO_TRAIN) / 1" | bc); \
      test "$$train" = "0" && \
        echo "Error: missing ground truth for training" && exit 1; \
      eval=$$(echo "$$total - $$train" | bc); \
      test "$$eval" = "0" && \
        echo "Error: missing ground truth for evaluation" && exit 1; \
      set -x; \
      head -n "$$train" $(ALL_LSTMF) > "$(OUTPUT_DIR)/list.train"; \
      tail -n "$$eval" $(ALL_LSTMF) > "$(OUTPUT_DIR)/list.eval"

ifdef START_MODEL
$(OUTPUT_DIR)/unicharset: $(ALL_GT)
    @mkdir -p $(DATA_DIR)/$(START_MODEL)
    combine_tessdata -u $(TESSDATA)/$(START_MODEL).traineddata  $(DATA_DIR)/$(START_MODEL)/$(MODEL_NAME)
    unicharset_extractor --output_unicharset "$(OUTPUT_DIR)/my.unicharset" --norm_mode $(NORM_MODE) "$(ALL_GT)"
    merge_unicharsets $(DATA_DIR)/$(START_MODEL)/$(MODEL_NAME).lstm-unicharset $(OUTPUT_DIR)/my.unicharset  "$@"
else
$(OUTPUT_DIR)/unicharset: $(ALL_GT)
    @mkdir -p $(OUTPUT_DIR)
    unicharset_extractor --output_unicharset "$@" --norm_mode $(NORM_MODE) "$(ALL_GT)"
endif

# Start training
training: $(OUTPUT_DIR).traineddata

$(ALL_GT): $(shell find $(GROUND_TRUTH_DIR) -name '*.gt.txt')
    @mkdir -p $(OUTPUT_DIR)
    find $(GROUND_TRUTH_DIR) -name '*.gt.txt' | xargs cat | sort | uniq > "$@"

.PRECIOUS: %.box
%.box: %.png %.gt.txt
    PYTHONIOENCODING=utf-8 python3 generate_line_box.py -i "$*.png" -t "$*.gt.txt" > "$@"

%.box: %.bin.png %.gt.txt
    PYTHONIOENCODING=utf-8 python3 generate_line_box.py -i "$*.bin.png" -t "$*.gt.txt" > "$@"

%.box: %.nrm.png %.gt.txt
    PYTHONIOENCODING=utf-8 python3 generate_line_box.py -i "$*.nrm.png" -t "$*.gt.txt" > "$@"

%.box: %.tif %.gt.txt
    PYTHONIOENCODING=utf-8 python3 $(GENERATE_BOX_SCRIPT) -i "$*.tif" -t "$*.gt.txt" > "$@"

$(ALL_LSTMF): $(patsubst %.gt.txt,%.lstmf,$(shell find $(GROUND_TRUTH_DIR) -name '*.gt.txt'))
    @mkdir -p $(OUTPUT_DIR)
    find $(GROUND_TRUTH_DIR) -name '*.lstmf' | python3 shuffle.py $(RANDOM_SEED) > "$@"

%.lstmf: %.box
    @if test -f "$*.png"; then \
      image="$*.png"; \
    elif test -f "$*.bin.png"; then \
      image="$*.bin.png"; \
    elif test -f "$*.nrm.png"; then \
      image="$*.nrm.png"; \
    else \
      image="$*.tif"; \
    fi; \
    set -x; \
    tesseract "$${image}" $* -l por --psm $(PSM) lstm.train

CHECKPOINT_FILES := $(wildcard $(OUTPUT_DIR)/checkpoints/$(MODEL_NAME)*.checkpoint)
.PHONY: traineddata

# Create best and fast .traineddata files from each .checkpoint file
traineddata: $(OUTPUT_DIR)/tessdata_best $(OUTPUT_DIR)/tessdata_fast

traineddata: $(subst checkpoints,tessdata_best,$(patsubst %.checkpoint,%.traineddata,$(CHECKPOINT_FILES)))
traineddata: $(subst checkpoints,tessdata_fast,$(patsubst %.checkpoint,%.traineddata,$(CHECKPOINT_FILES)))
$(OUTPUT_DIR)/tessdata_best $(OUTPUT_DIR)/tessdata_fast:
    mkdir $@
$(OUTPUT_DIR)/tessdata_best/%.traineddata: $(OUTPUT_DIR)/checkpoints/%.checkpoint
    lstmtraining \
          --stop_training \
          --continue_from $< \
          --traineddata $(PROTO_MODEL) \
          --model_output $@
$(OUTPUT_DIR)/tessdata_fast/%.traineddata: $(OUTPUT_DIR)/checkpoints/%.checkpoint
    lstmtraining \
          --stop_training \
          --continue_from $< \
          --traineddata $(PROTO_MODEL) \
          --convert_to_int \
          --model_output $@

# Build the proto model
proto-model: $(PROTO_MODEL)

$(PROTO_MODEL): $(OUTPUT_DIR)/unicharset $(DATA_DIR)/radical-stroke.txt
    combine_lang_model \
      --input_unicharset $(OUTPUT_DIR)/unicharset \
      --script_dir $(DATA_DIR) \
      --numbers $(NUMBERS_FILE) \
      --puncs $(PUNC_FILE) \
      --words $(WORDLIST_FILE) \
      --output_dir $(DATA_DIR) \
      $(RECODER) \
      --lang $(MODEL_NAME)

ifdef START_MODEL
$(LAST_CHECKPOINT): unicharset lists $(PROTO_MODEL)
    @mkdir -p $(OUTPUT_DIR)/checkpoints
    lstmtraining \
      --debug_interval $(DEBUG_INTERVAL) \
      --traineddata $(PROTO_MODEL) \
      --old_traineddata $(TESSDATA)/$(START_MODEL).traineddata \
      --continue_from $(DATA_DIR)/$(START_MODEL)/$(MODEL_NAME).lstm \
      --learning_rate $(LEARNING_RATE) \
      --model_output $(OUTPUT_DIR)/checkpoints/$(MODEL_NAME) \
      --train_listfile $(OUTPUT_DIR)/list.train \
      --eval_listfile $(OUTPUT_DIR)/list.eval \
      --max_iterations $(MAX_ITERATIONS) \
      --target_error_rate $(TARGET_ERROR_RATE)
$(OUTPUT_DIR).traineddata: $(LAST_CHECKPOINT)
    lstmtraining \
    --stop_training \
    --continue_from $(LAST_CHECKPOINT) \
    --traineddata $(PROTO_MODEL) \
    --model_output $@
else
$(LAST_CHECKPOINT): unicharset lists $(PROTO_MODEL)
    @mkdir -p $(OUTPUT_DIR)/checkpoints
    lstmtraining \
      --debug_interval $(DEBUG_INTERVAL) \
      --traineddata $(PROTO_MODEL) \
      --learning_rate $(LEARNING_RATE) \
      --net_spec "$(subst c###,c`head -n1 $(OUTPUT_DIR)/unicharset`,$(NET_SPEC))" \
      --model_output $(OUTPUT_DIR)/checkpoints/$(MODEL_NAME) \
      --train_listfile $(OUTPUT_DIR)/list.train \
      --eval_listfile $(OUTPUT_DIR)/list.eval \
      --max_iterations $(MAX_ITERATIONS) \
      --target_error_rate $(TARGET_ERROR_RATE)
$(OUTPUT_DIR).traineddata: $(LAST_CHECKPOINT)
    lstmtraining \
    --stop_training \
    --continue_from $(LAST_CHECKPOINT) \
    --traineddata $(PROTO_MODEL) \
    --model_output $@
endif

$(DATA_DIR)/radical-stroke.txt:
    wget -O$@ 'https://github.com/tesseract-ocr/langdata_lstm/raw/master/radical-stroke.txt'

# Build leptonica
leptonica: leptonica.built

leptonica.built: leptonica-$(LEPTONICA_VERSION)
    cd $< ; \
        ./configure --prefix=$(LOCAL) && \
        make -j$(CORES) install SUBDIRS=src && \
        date > "$@"

leptonica-$(LEPTONICA_VERSION): leptonica-$(LEPTONICA_VERSION).tar.gz
    tar xf "$<"

leptonica-$(LEPTONICA_VERSION).tar.gz:
    wget 'http://www.leptonica.org/source/$@'

# Build tesseract
tesseract: tesseract.built tesseract-langs

tesseract.built: tesseract-$(TESSERACT_VERSION)
    cd $< && \
        sh autogen.sh && \
        PKG_CONFIG_PATH="$(LOCAL)/lib/pkgconfig" \
            ./configure --prefix=$(LOCAL) && \
        LDFLAGS="-L$(LOCAL)/lib"\
            make -j$(CORES) install && \
        LDFLAGS="-L$(LOCAL)/lib"\
            make -j$(CORES) training-install && \
        date > "$@"

tesseract-$(TESSERACT_VERSION):
    wget https://github.com/tesseract-ocr/tesseract/archive/$(TESSERACT_VERSION).zip
    unzip $(TESSERACT_VERSION).zip

# Download tesseract-langs
tesseract-langs: $(TESSDATA)/por.traineddata

$(TESSDATA)/por.traineddata:
    cd $(TESSDATA) && wget https://github.com/tesseract-ocr/tessdata$(TESSDATA_REPO)/raw/master/$(notdir $@)

# Clean generated .box files
.PHONY: clean-box
clean-box:
    find $(GROUND_TRUTH_DIR) -name '*.box' -delete

# Clean generated .lstmf files
.PHONY: clean-lstmf
clean-lstmf:
    find $(GROUND_TRUTH_DIR) -name '*.lstmf' -delete

# Clean generated output files
.PHONY: clean-output
clean-output:
    rm -rf $(OUTPUT_DIR)

# Clean all generated files
clean: clean-box clean-lstmf clean-output
stale[bot] commented 3 years ago

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

wrznr commented 3 years ago

@ryancarloscorrea Could you please try to reformat your issue? It is unreadable in its current display.

kba commented 3 years ago

@ryancarloscorrea Could you please try to reformat your issue? It is unreadable in its current display.

I added ``` fences around the makefile

wrznr commented 3 years ago

@ryancarloscorrea Good news! You do not have to change the Makefile at all. It already is suited for fine tuning existing Teseract models. Pls. refer to the excellent documentation by @stweil here: https://github.com/tesseract-ocr/tesstrain/wiki/GT4HistOCR

ryancarloscorrea commented 3 years ago

@wrznr thank you!! Worked, got it a few weeks ago.