Add fact sheet

doc/fact-sheet/Makefile

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+# Makefile for LaTeX documents
+#
+# Intended for use in Linux and Git Bash
+# TeXstudio (MiKTeX) compatibility through TeX directives
+#
+# by Dominik Mueller (@MuellerDominik)
+#
+# Targets:
+#
+# all						Build document if necessary
+# build						Always (re)build document
+# pdflatex					Run pdfLaTeX
+# debug						Run pdfLaTeX in verbose mode
+# bibliography, bib			Run biber
+# glossary, makeglossaries	Run makeglossaries
+# snapshot					Create snapshot
+# remove-snapshots			Remove all snapshots
+# directives				Add proper TeX directives
+# remove-directives			Remove all TeX directives
+# clean						Remove auxiliary files
+# purge						Remove all generated files
+
+# Document name
+DOCUMENT = fact-sheet
+OUTPUT = p5_aionfpga_fact-sheet_canzani_mueller
+
+# Directories and auxiliary files
+TEMP_DIR = temp
+BUILD_DIR = build
+SECTIONS_DIR = sections
+SNAPSHOTS_DIR = snapshots
+PDF_FILE = $(BUILD_DIR)/$(OUTPUT).pdf
+BIB_FILE = $(BUILD_DIR)/$(OUTPUT).bcf
+GLOSS_FILE = $(BUILD_DIR)/$(OUTPUT).glo
+
+# Source files (omit whitespaces) and timestamp
+TEX_FILES := $(shell find . -name "*.tex")
+TIMESTAMP := $(shell date +%Y-%m-%d_%H-%M-%S)
+
+# Document ID (sliced for TeX directive 'document-id')
+DOC_ID := $(shell echo -n $(TIMESTAMP) | sha256sum | cut -c1-32)
+DOC_ID1 := $(shell echo -n $(DOC_ID) | cut -c1-8)
+DOC_ID2 := $(shell echo -n $(DOC_ID) | cut -c9-12)
+DOC_ID3 := $(shell echo -n $(DOC_ID) | cut -c13-16)
+DOC_ID4 := $(shell echo -n $(DOC_ID) | cut -c17-20)
+DOC_ID5 := $(shell echo -n $(DOC_ID) | cut -c21-32)
+
+# Commands (with their respective arguments)
+PDFLATEX_ARGS = -output-directory=$(BUILD_DIR) -jobname=$(OUTPUT) $(DOCUMENT)
+PDFLATEX = pdflatex -interaction=batchmode $(PDFLATEX_ARGS) > /dev/null 2>&1
+PDFLATEX_DEBUG = pdflatex -interaction=nonstopmode -halt-on-error $(PDFLATEX_ARGS)
+BIBLIOGRAPHY = biber --onlylog --output-directory $(BUILD_DIR) $(OUTPUT)
+GLOSSARY = makeglossaries -q -d $(BUILD_DIR) $(OUTPUT)
+
+# TeX directives for TeXstudio with MiKTeX on Windows (Perl installed)
+DIR_ID = % !TeX document-id = {$(DOC_ID1)-$(DOC_ID2)-$(DOC_ID3)-$(DOC_ID4)-$(DOC_ID5)}
+DIR_COMPILE = % !TeX TXS-program:compile = pdflatex -synctex=1 -interaction=nonstopmode $(PDFLATEX_ARGS).tex
+DIR_BIB = % !TeX TXS-program:bibliography = biber --output-directory $(BUILD_DIR) $(OUTPUT)
+DIR_GLOSS = % !TeX TXS-program:glossary = makeglossaries -d $(BUILD_DIR) $(OUTPUT)
+DIR_VIEW = % !TeX TXS-program:view = txs:///view-pdf ./$(BUILD_DIR)/$(OUTPUT).pdf
+DIRECTIVES = $(DIR_ID)\n$(DIR_COMPILE)\n$(DIR_BIB)\n$(DIR_GLOSS)\n$(DIR_VIEW)\n\n
+
+# Rebuilds document if source files (*.tex only) have been changed
+.PHONY: all
+all: $(PDF_FILE)
+
+.PHONY: build
+build $(PDF_FILE): $(TEX_FILES)
+	@mkdir -p $(BUILD_DIR)/$(SECTIONS_DIR)/
+	@$(PDFLATEX)
+	@$(BIBLIOGRAPHY)
+	@$(GLOSSARY)
+	@$(PDFLATEX)
+	@$(PDFLATEX)
+
+.PHONY: pdflatex
+pdflatex $(BIB_FILE) $(GLOSS_FILE):
+	@$(PDFLATEX)
+
+.PHONY: debug
+debug:
+	@$(PDFLATEX_DEBUG)
+
+.PHONY: bibliography bib
+bibliography bib: $(BIB_FILE)
+	@$(BIBLIOGRAPHY)
+
+.PHONY: glossary makeglossaries
+glossary makeglossaries: $(GLOSS_FILE)
+	@$(GLOSSARY)
+
+.PHONY: snapshot
+snapshot:
+	@mkdir -p $(SNAPSHOTS_DIR)/
+	@cp -f $(PDF_FILE) $(SNAPSHOTS_DIR)/$(OUTPUT)_$(TIMESTAMP).pdf
+
+.PHONY: remove-snapshots
+remove-snapshots:
+	@rm -rf $(SNAPSHOTS_DIR)/
+
+# Removes all TeX directives and prepends the ones specified in this Makefile
+.PHONY: directives
+directives:
+	@sed -i '/^% !TeX/d' $(DOCUMENT).tex
+	@sed -i '/./,$$!d' $(DOCUMENT).tex
+	@sed -i '1s;^;$(DIRECTIVES);' $(DOCUMENT).tex
+
+# Removes all TeX directives and leading blank lines
+.PHONY: remove-directives
+remove-directives:
+	@sed -i '/^% !TeX/d' $(DOCUMENT).tex
+	@sed -i '/./,$$!d' $(DOCUMENT).tex
+
+.PHONY: clean
+clean:
+	@mkdir -p $(TEMP_DIR)/
+	@cp -f $(PDF_FILE) $(TEMP_DIR)/$(OUTPUT).pdf > /dev/null 2>&1 || :
+	@rm -rf $(BUILD_DIR)/* > /dev/null 2>&1 || :
+	@cp -f $(TEMP_DIR)/$(OUTPUT).pdf $(PDF_FILE) > /dev/null 2>&1 || :
+	@rm -rf $(TEMP_DIR)/
+
+.PHONY: purge
+purge:
+	@rm -rf $(BUILD_DIR)/ $(TEMP_DIR)/

doc/fact-sheet/content.tex

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+\title{AI High-Performance Solution on FPGA}
+
+\team{Nico Canzani, Dominik M\"uller}
+
+% \client{FHNW Institute for Sensors and Electronics}
+\client{Inst. for Sensors and Electronics}
+% \client{FHNW / ISE}
+
+\coaches{%
+  Prof. Michael Pichler,\\
+  Prof. Dr. Hanspeter Schmid
+}
+
+\repo{https://git.io/p5-aionfpga}
+% curl -i https://git.io -F "url=https://github.com/MuellerDominik/P5-AIonFPGA/" -F "code=p5-aionfpga"
+
+\fssummary{
+  In a world of self-driving cars and automated quality control in manufacturing, real-time image classification is becoming increasingly important.
+  % Artificial intelligence, and deep learning in particular, are achieving excellent classification accuracies, but there are some challenges.
+  Artificial intelligence (AI), and deep learning in particular, are achieving excellent classification accuracies.
+  % However, a large labeled dataset of training data is required to train deep convolutional neural networks.
+  % However, a large labeled dataset of training data is required to train a convolutional neural networks (CNN).
+  However, the training of a convolutional neural network (CNN) requires a sufficiently large labeled dataset.
+  % However, the training of a deep convolutional neural network (CNN) required a sufficiently large labeled dataset.
+}
+
+\fsgraphics{
+  \begin{minipage}[t]{0.5\textwidth}
+      \begin{minipage}[t]{0.98\textwidth}
+        \includegraphics[width=\textwidth]{graphics/1574952009_278_10_stuffed-bunny.png}
+        \graphicscaption{Image of the \textit{Stuffed Bunny}} % Example / Sample
+      \end{minipage}
+  \end{minipage}%
+  \begin{minipage}[t]{0.5\textwidth}
+    \begin{flushright}
+      \begin{minipage}[t]{0.98\textwidth}
+        \includegraphics[width=\textwidth]{graphics/1574943825_125_8_hand-featherball.png}
+        \graphicscaption{Image of the \textit{Hand Featherball}} % Example / Sample
+      \end{minipage}
+    \end{flushright}
+  \end{minipage}
+}
+
+\fscontent{
+  % \section{Problem Statement}
+  \section{Difficulty}
+  Collecting a sufficiently large dataset of pictures is not trivial.
+  When done manually, the camera has to be started and stopped for each throw.
+  This likely creates many empty frames at the beginning and at the end of the capture.
+  Those empty and therefore invalid frames must be removed to avoid errors during the training of the CNN later on.
+  Furthermore, each valid frame must be labeled.
+  This procedure is very error-prone if it is performed manually for each individual frame.
+
+  \newcol
+  \section{Software}
+  % To reliably detect a throw, a simple image change detection algorithm is implemented.
+  % It requires a repeated difference computation and therefore a circular buffer is used.
+  % To simplify this task, a camera throw detection mechanism is implemented and various Python scripts are used.
+  To simplify the image collection, a camera throw detection mechanism is implemented and various Python scripts are used.
+  The goal of the throw detection is to extract valid frames of a throw --- with objects on them --- from the continuous data stream of the camera.
+  Therefore, the throw detection needs to work in real time.
+  % At a frame rate of \SI{200}{fps}, there is $<\SI{5}{ms}$ to process a single frame (without the use of parallel computing).
+  At a frame rate of \SI{200}{fps}, there is less than \SI{5}{ms} to process a single frame.
+  % Due to this time constraint, a simple image change detection algorithm is employed.
+  Due to this time constraint, a simple image change detection algorithm is implemented.
+
+  \newcol
+  % \section{Labeled Dataset}
+  \section{Dataset}
+  % The dataset contains images of 22 different throwing objects.
+  The dataset contains images of 22 different throwing objects, ranging from sports equipment to toys.
+  It is fully labeled and consists of more than \num{15000} usable images with at least 480 images of each object.
+  % All images were collected over the course of two days.
+  % The employed software allowed to collected all images over the course of two days.
+  The employed software made it possible to collect all images over the course of only two days.
+  % The above images show an example image of the \textit{Stuffed Bunny} and of the \textit{Hand Featherball}.
+  The above images are two examples from the labeled dataset.
+  The first one shows the \textit{Stuffed Bunny} and the second one shows the \textit{Hand Featherball}.
+}
+
+\infobox{Throwing Booth}{
+  % \begin{minipage}[t][][b]{0.45\textwidth}
+  %   \includegraphics[height=50mm]{graphics/top_assembly.png}
+  % \end{minipage}\hfill%
+  \begin{minipage}{0.65\textwidth}
+    The throwing booth is constructed from general-purpose aluminium profiles.
+    % The rear panel is made of a white ABS plastic sheet for its robust impact strength and has a target hole. % features a target hole
+    Due to its robust impact strength, the rear panel is made of a white ABS plastic sheet and has a target hole.
+    % The side panel is made of a foamed PVC sheet to reduce light reflections.
+    The white side panel serves as a consistent background for the images.
+    It is made of a foamed PVC sheet with a fine-textured surface to reduce light reflections.
+    % The image acquisition system consists of a Baumer industrial camera and a suitable lens.
+    The image acquisition system consists of a Baumer industrial camera combined with a suitable lens. % imaging environment
+    % Strong diffuse lighting is used to minimize the required exposure time and to evenly illuminate the side panel.
+    Strong diffuse lighting is used to minimize the required exposure time and to illuminate the side panel as evenly as possible.
+    % A monitor is used to display the detected object. % display the result
+    Finally, a monitor is used to display the detected object.
+  \end{minipage}\hfill%
+  \begin{minipage}{0.32\textwidth}
+    \includegraphics[width=\textwidth]{graphics/top_assembly.png}
+  \end{minipage}
+}

doc/fact-sheet/fact-sheet.tex

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+% !TeX document-id = {f144be9f-d20a-6673-972c-41c90886e461}
+% !TeX TXS-program:compile = pdflatex -synctex=1 -interaction=nonstopmode -output-directory=build -jobname=p5_aionfpga_fact-sheet_canzani_mueller fact-sheet.tex
+% !TeX TXS-program:bibliography = biber --output-directory build p5_aionfpga_fact-sheet_canzani_mueller
+% !TeX TXS-program:glossary = makeglossaries -d build p5_aionfpga_fact-sheet_canzani_mueller
+% !TeX TXS-program:view = txs:///view-pdf ./build/p5_aionfpga_fact-sheet_canzani_mueller.pdf
+
+\documentclass[english]{fhnwfactsheet}
+% \usepackage{tikz}
+% \usepackage{lipsum}
+
+\begin{document}
+  \includefactsheet{content.tex}
+\end{document}