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124 lines
4.0 KiB
Makefile
124 lines
4.0 KiB
Makefile
images=$(sort $(wildcard images/*.jpg))
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# @andre make wildcard so that it takes any image file but doesn't take the listimg.txt file
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output_ocr:=$(dir_ocr)/output.txt
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tmpfile:= $(shell mktemp)
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space:= $(empty) $(empty)
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newline:= '\n'
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listimgs:= $(subst $(space),$(newline), $(images) ) # list of the images, with one filename on each line $(subst $(delimitator),$(replacement),$(list))
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OS:= $(shell uname)
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# Colors: add color to output ie @echo $(color_r) output text
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color_w:="\033[0;29m"
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color_r:="\033[0;31m"
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color_g:="\033[0;32m"
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color_b:="\033[0;34m"
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# HELP / SELF DOCUMENTATION
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# rules where first line contains comment with 2x# (see example in clean rule)
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.DEFAULT_GOAL := help # help rule as default when you run: make
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.PHONY: help
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help:
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@grep -E '^[a-zA-Z_-\/]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
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# CLEAN
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clean: ## removes output (target) files
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rm ocr/output.txt
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rm $(wildcard output/*)
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rm $(tmpfile)
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# ADMINISTRATIVE RECIPES
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dirs: ## create the dirs in working dir
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@-mkdir -p images/
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@-mkdir -p images-tiff/
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@-mkdir -p output/
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@-mkdir -p ocr/
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@-mkdir -p hocr/
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@echo $(color_r)'Directories made': images/ output/
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testif:
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ifeq ($(OS),Darwin)
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@echo $(OS)
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endif
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# POST-PROCESSING RECIPES
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ocr/output.txt: ## ocr with tesseract
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echo $(listimgs) > $(@D)/list.txt
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@echo $(basename $@ .txt)
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tesseract $(@D)/list.txt $(basename $@ .txt)
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python3 src/build_database.py $(@)
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tiffs: ## convert images/ to images-tiff/ Depends on IM
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echo $(images)
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for i in $(images); \
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do tiff=`basename $$i .jpg`.tiff; \
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convert -density 300 $$i images-tiff/$$tiff; \
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echo $$tiff; \
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done;
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hocrs: ## hocr with tesseract and then change extension to .html
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for i in images-tiff/*.tiff; \
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do echo $$i; hocrfile=`basename $$i .tiff`; \
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tesseract $$i hocr/$$hocrfile hocr; \
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mv hocr/$$hocrfile.hocr hocr/$$hocrfile.html; \
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done;
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#OUTPUT GENERATION RECIPES
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output/wordtagger/index.html: ocr/output.txt ## Analyzes OCR'ed text using a Part of Speech (POS) tagger. Outputs a string of tags (e.g. nouns, verbs, adjectives, and adverbs). Dependencies: python3's nltk, jinja2
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mkdir -p output/wordtagger
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cp src/wordtagger/jquery.min.js output/wordtagger
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cp src/wordtagger/script.js output/wordtagger
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cp src/wordtagger/style.css output/wordtagger
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cat $< | python3 src/wordtagger/wordtagger.py
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# install nltk's 'averaged_perceptron_tagger':
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# $ python 3
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# >>> import nltk
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# >>> nltk.download('averaged_perceptron_tagger')
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output/chatbot.txt: ocr/output.txt ## Comments a text with a simple chatbot. Dependencies: python3's chatterbot
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cat $< | python3 src/textbotconversation.py $(@)
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output/n7.txt: ocr/output.txt ## Replaces nouns with the 7th noun that follows. Dependencies: 91k_nouns
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cat $< | python3 src/n_7.py > $(@)
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carlandre: ocr/output.txt ## Alice: Creates visual poetry out of a text. Dependencies: pytest
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@python3 src/carlandre.py
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.PHONY: carlandre
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# cat $(@) > /dev/usb/lp0
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overunder: ocr/output.txt ## Alice: An interpreted language that translate simple weaving instructions and creates a weaving pattern on text.
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@python3 src/overunder.py
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.PHONY: overunder
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visualization: $(images) $(tmpfile) ##Creates data visualization from images/*.jpg. Dependencies: mplayer
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@echo $(tmpfile)
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for i in $(images); do \
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cat $$i >> $(tmpfile); \
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done;
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ifeq ($(OS),Darwin)
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cat $(tmpfile) | mplayer -sws 4 -zoom -vf dsize=720:720 -demuxer rawvideo -rawvideo w=56:h=64:i420:fps=25 -;
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else
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cat $(tmpfile) | mplayer -vo x11 -sws 4 -zoom -vf dsize=720:720 -demuxer rawvideo -rawvideo w=50:h=50:i420:fps=25 -;
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endif
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tts: output/chatbot.txt ocr/output.txt ## text to speech. Dependencies: espeak
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@echo $(color_r) speaking $?
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@echo $(color_w)
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cat $? | espeak
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ttssr-human-only: ocr/output.txt ## Loop: text to speech-speech recognition. Dependencies: espeak, pocketsphinx
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bash src/ttssr-loop-human-only.sh ocr/output.txt
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chatbook: ocr/output.txt #chatbot based on the knowledge of the scans Dependencies: nltk_rake, irc, nltk
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python3 src/chatbook.py
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