(WIP) Feature/ieee format output

Makefile

@@ -2,6 +2,8 @@ markdown: dst dst/index.html dst/style.css
 
 server: dst dst/style.css dst/index.md dst/sitemap.xml
 
+
+
 dst/index.html: dst/index.md src/references.bib src/template/index.html dst/style.css
 	pandoc dst/index.md --template src/template/index.html -s --table-of-contents --bibliography=src/references.bib --citeproc --columns 1000 -H src/header.html -V lang=en -o $@
 
@@ -74,7 +76,39 @@ dst/index_emoji.tex: dst dst/index_shortcode.md src/references.bib
 dst/index.tex: dst/index_emoji.tex src/replace_gifs.py
 	python src/replace_gifs.py dst/index_emoji.tex $@
 
+# index to .tex, then compile to PDF
+dst/index_tex.pdf:
+	cp src/references.bib dst 
+	cd dst && rm index.*
+	cd dst && cat bak_index.tex > index.tex
+	cd dst && lualatex index.tex
+	cd dst && biber index.aux
+	cd dst && lualatex index.tex
+	cd dst && lualatex index.tex
+
+
+# set up custom docker image based on https://hub.docker.com/r/pandoc/extra
+# docker:
+# 	cd docker && docker build . -t pandoc/extra/slp
+
+# attempting to use pandoc docker.
+# dst/index_pandock.pdf: dst/index_shortcode.md src/references.bib docker
+# 	cd dst && docker run --volume "$(shell pwd):/data" --user $(shell id -u):$(shell id -g) pandoc/extra/slp -f markdown+emoji -L/data/addons/latex-emoji.lua /data/dst/index_shortcode.md -s -N --pdf-engine=lualatex --shift-heading-level-by=-1 --bibliography=/data/src/references.bib --citeproc -o index_pandock.pdf
+
+# TODO: output in IEEE format.
+# IEEE requires latex format. 
+# dst/ieee_format.tex:
+
+# dst/index_ieee.pdf: dst/index_shortcode.md src/references.bib
+# 	cp src/template/bare_jrnl_new_sample4.tex dst
+# 	cd dst && pandoc --template=bare_jrnl_new_sample4.tex -f markdown+emoji -L../addons/latex-emoji.lua index_shortcode.md -s -N --pdf-engine=lualatex --shift-heading-level-by=-1 --bibliography=../src/references.bib --citeproc -o index.pdf
+
+
+clean:
+	rm -r dst
+	rm -r tmp
 #
 #
 #tex/references.bib: src/references.bib tex
 #	cp src/references.bib $@
+

docker/Dockerfile

@@ -0,0 +1,4 @@
+FROM pandoc/extra
+
+RUN tlmgr install pdflscape
+RUN tlmgr install twemoji-colr

src/index.md

@@ -8,6 +8,7 @@ secnumdepth: 3
 header-includes:
 - |
   \usepackage{pdflscape}
+  \usepackage{graphicx}
 author:
 - Amit Moryossef ([[email protected]](mailto:[email protected]))
 - Yoav Goldberg ([[email protected]](mailto:[email protected]))
@@ -819,8 +820,8 @@ or aligned to the spoken language captions, and showed their DTW is advantageous
 
 @xiao2020skeleton closed the loop by proposing a text-to-pose-to-text model for the case of isolated sign language recognition.
 They first trained a classifier to take a sequence of poses encoded by a BiLSTM and classify the relevant sign, then proposed a production system to take a single sign and sample a constant length sequence of 50 poses from a Gaussian Mixture Model.
-These components are combined such that given a sign class $y$, a pose sequence is generated, then classified back into a sign class $ŷ$,
-and the loss is applied between $y$ and $ŷ$, and not directly on the generated pose sequence.
+These components are combined such that given a sign class $y$, a pose sequence is generated, then classified back into a sign class $\hat{y}$,
+and the loss is applied between $y$ and $\hat{y}$, and not directly on the generated pose sequence.
 They evaluate their approach on the CSL dataset [@dataset:huang2018video] and show that their generated pose sequences 
 almost reach the same classification performance as the reference sequences.
 

src/markdown_fix.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-if type gsed >/dev/null
+if which gsed >/dev/null
 then
   echo "Using gsed"
   function ssed { gsed "$@" ;}