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notebook.tex
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notebook.tex
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% Default to the notebook output style
% Inherit from the specified cell style.
\documentclass[11pt]{article}
\usepackage[T1]{fontenc}
% Nicer default font (+ math font) than Computer Modern for most use cases
\usepackage{mathpazo}
% Basic figure setup, for now with no caption control since it's done
% automatically by Pandoc (which extracts  syntax from Markdown).
\usepackage{graphicx}
% We will generate all images so they have a width \maxwidth. This means
% that they will get their normal width if they fit onto the page, but
% are scaled down if they would overflow the margins.
\makeatletter
\def\maxwidth{\ifdim\Gin@nat@width>\linewidth\linewidth
\else\Gin@nat@width\fi}
\makeatother
\let\Oldincludegraphics\includegraphics
% Set max figure width to be 80% of text width, for now hardcoded.
\renewcommand{\includegraphics}[1]{\Oldincludegraphics[width=.8\maxwidth]{#1}}
% Ensure that by default, figures have no caption (until we provide a
% proper Figure object with a Caption API and a way to capture that
% in the conversion process - todo).
\usepackage{caption}
\DeclareCaptionLabelFormat{nolabel}{}
\captionsetup{labelformat=nolabel}
\usepackage{adjustbox} % Used to constrain images to a maximum size
\usepackage{xcolor} % Allow colors to be defined
\usepackage{enumerate} % Needed for markdown enumerations to work
\usepackage{geometry} % Used to adjust the document margins
\usepackage{amsmath} % Equations
\usepackage{amssymb} % Equations
\usepackage{textcomp} % defines textquotesingle
% Hack from http://tex.stackexchange.com/a/47451/13684:
\AtBeginDocument{%
\def\PYZsq{\textquotesingle}% Upright quotes in Pygmentized code
}
\usepackage{upquote} % Upright quotes for verbatim code
\usepackage{eurosym} % defines \euro
\usepackage[mathletters]{ucs} % Extended unicode (utf-8) support
\usepackage[utf8x]{inputenc} % Allow utf-8 characters in the tex document
\usepackage{fancyvrb} % verbatim replacement that allows latex
\usepackage{grffile} % extends the file name processing of package graphics
% to support a larger range
% The hyperref package gives us a pdf with properly built
% internal navigation ('pdf bookmarks' for the table of contents,
% internal cross-reference links, web links for URLs, etc.)
\usepackage{hyperref}
\usepackage{longtable} % longtable support required by pandoc >1.10
\usepackage{booktabs} % table support for pandoc > 1.12.2
\usepackage[inline]{enumitem} % IRkernel/repr support (it uses the enumerate* environment)
\usepackage[normalem]{ulem} % ulem is needed to support strikethroughs (\sout)
% normalem makes italics be italics, not underlines
% Colors for the hyperref package
\definecolor{urlcolor}{rgb}{0,.145,.698}
\definecolor{linkcolor}{rgb}{.71,0.21,0.01}
\definecolor{citecolor}{rgb}{.12,.54,.11}
% ANSI colors
\definecolor{ansi-black}{HTML}{3E424D}
\definecolor{ansi-black-intense}{HTML}{282C36}
\definecolor{ansi-red}{HTML}{E75C58}
\definecolor{ansi-red-intense}{HTML}{B22B31}
\definecolor{ansi-green}{HTML}{00A250}
\definecolor{ansi-green-intense}{HTML}{007427}
\definecolor{ansi-yellow}{HTML}{DDB62B}
\definecolor{ansi-yellow-intense}{HTML}{B27D12}
\definecolor{ansi-blue}{HTML}{208FFB}
\definecolor{ansi-blue-intense}{HTML}{0065CA}
\definecolor{ansi-magenta}{HTML}{D160C4}
\definecolor{ansi-magenta-intense}{HTML}{A03196}
\definecolor{ansi-cyan}{HTML}{60C6C8}
\definecolor{ansi-cyan-intense}{HTML}{258F8F}
\definecolor{ansi-white}{HTML}{C5C1B4}
\definecolor{ansi-white-intense}{HTML}{A1A6B2}
% commands and environments needed by pandoc snippets
% extracted from the output of `pandoc -s`
\providecommand{\tightlist}{%
\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}
\DefineVerbatimEnvironment{Highlighting}{Verbatim}{commandchars=\\\{\}}
% Add ',fontsize=\small' for more characters per line
\newenvironment{Shaded}{}{}
\newcommand{\KeywordTok}[1]{\textcolor[rgb]{0.00,0.44,0.13}{\textbf{{#1}}}}
\newcommand{\DataTypeTok}[1]{\textcolor[rgb]{0.56,0.13,0.00}{{#1}}}
\newcommand{\DecValTok}[1]{\textcolor[rgb]{0.25,0.63,0.44}{{#1}}}
\newcommand{\BaseNTok}[1]{\textcolor[rgb]{0.25,0.63,0.44}{{#1}}}
\newcommand{\FloatTok}[1]{\textcolor[rgb]{0.25,0.63,0.44}{{#1}}}
\newcommand{\CharTok}[1]{\textcolor[rgb]{0.25,0.44,0.63}{{#1}}}
\newcommand{\StringTok}[1]{\textcolor[rgb]{0.25,0.44,0.63}{{#1}}}
\newcommand{\CommentTok}[1]{\textcolor[rgb]{0.38,0.63,0.69}{\textit{{#1}}}}
\newcommand{\OtherTok}[1]{\textcolor[rgb]{0.00,0.44,0.13}{{#1}}}
\newcommand{\AlertTok}[1]{\textcolor[rgb]{1.00,0.00,0.00}{\textbf{{#1}}}}
\newcommand{\FunctionTok}[1]{\textcolor[rgb]{0.02,0.16,0.49}{{#1}}}
\newcommand{\RegionMarkerTok}[1]{{#1}}
\newcommand{\ErrorTok}[1]{\textcolor[rgb]{1.00,0.00,0.00}{\textbf{{#1}}}}
\newcommand{\NormalTok}[1]{{#1}}
% Additional commands for more recent versions of Pandoc
\newcommand{\ConstantTok}[1]{\textcolor[rgb]{0.53,0.00,0.00}{{#1}}}
\newcommand{\SpecialCharTok}[1]{\textcolor[rgb]{0.25,0.44,0.63}{{#1}}}
\newcommand{\VerbatimStringTok}[1]{\textcolor[rgb]{0.25,0.44,0.63}{{#1}}}
\newcommand{\SpecialStringTok}[1]{\textcolor[rgb]{0.73,0.40,0.53}{{#1}}}
\newcommand{\ImportTok}[1]{{#1}}
\newcommand{\DocumentationTok}[1]{\textcolor[rgb]{0.73,0.13,0.13}{\textit{{#1}}}}
\newcommand{\AnnotationTok}[1]{\textcolor[rgb]{0.38,0.63,0.69}{\textbf{\textit{{#1}}}}}
\newcommand{\CommentVarTok}[1]{\textcolor[rgb]{0.38,0.63,0.69}{\textbf{\textit{{#1}}}}}
\newcommand{\VariableTok}[1]{\textcolor[rgb]{0.10,0.09,0.49}{{#1}}}
\newcommand{\ControlFlowTok}[1]{\textcolor[rgb]{0.00,0.44,0.13}{\textbf{{#1}}}}
\newcommand{\OperatorTok}[1]{\textcolor[rgb]{0.40,0.40,0.40}{{#1}}}
\newcommand{\BuiltInTok}[1]{{#1}}
\newcommand{\ExtensionTok}[1]{{#1}}
\newcommand{\PreprocessorTok}[1]{\textcolor[rgb]{0.74,0.48,0.00}{{#1}}}
\newcommand{\AttributeTok}[1]{\textcolor[rgb]{0.49,0.56,0.16}{{#1}}}
\newcommand{\InformationTok}[1]{\textcolor[rgb]{0.38,0.63,0.69}{\textbf{\textit{{#1}}}}}
\newcommand{\WarningTok}[1]{\textcolor[rgb]{0.38,0.63,0.69}{\textbf{\textit{{#1}}}}}
% Define a nice break command that doesn't care if a line doesn't already
% exist.
\def\br{\hspace*{\fill} \\* }
% Math Jax compatability definitions
\def\gt{>}
\def\lt{<}
% Document parameters
\title{HW2\_part1\_get\_des}
% Pygments definitions
\makeatletter
\def\PY@reset{\let\PY@it=\relax \let\PY@bf=\relax%
\let\PY@ul=\relax \let\PY@tc=\relax%
\let\PY@bc=\relax \let\PY@ff=\relax}
\def\PY@tok#1{\csname PY@tok@#1\endcsname}
\def\PY@toks#1+{\ifx\relax#1\empty\else%
\PY@tok{#1}\expandafter\PY@toks\fi}
\def\PY@do#1{\PY@bc{\PY@tc{\PY@ul{%
\PY@it{\PY@bf{\PY@ff{#1}}}}}}}
\def\PY#1#2{\PY@reset\PY@toks#1+\relax+\PY@do{#2}}
\expandafter\def\csname PY@tok@w\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.73,0.73}{##1}}}
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\def\PYZbs{\char`\\}
\def\PYZus{\char`\_}
\def\PYZob{\char`\{}
\def\PYZcb{\char`\}}
\def\PYZca{\char`\^}
\def\PYZam{\char`\&}
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\def\PYZsh{\char`\#}
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% for compatibility with earlier versions
\def\PYZat{@}
\def\PYZlb{[}
\def\PYZrb{]}
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% Exact colors from NB
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\definecolor{outcolor}{rgb}{0.545, 0.0, 0.0}
% Prevent overflowing lines due to hard-to-break entities
\sloppy
% Setup hyperref package
\hypersetup{
breaklinks=true, % so long urls are correctly broken across lines
colorlinks=true,
urlcolor=urlcolor,
linkcolor=linkcolor,
citecolor=citecolor,
}
% Slightly bigger margins than the latex defaults
\geometry{verbose,tmargin=1in,bmargin=1in,lmargin=1in,rmargin=1in}
\begin{document}
\maketitle
\hypertarget{hw2-solution-part-1}{%
\subsection{HW2 Solution Part 1}\label{hw2-solution-part-1}}
\textbf{step1}: get keypoints for each images
\textbf{step2}: get patches for each keypoints
\textbf{step3}: get descriptions for each keypoints (by forward pass
patches to the network)
step4: caculate the similarity matrices
step5: get topK similar images for each query
step6: draw recall vs precision curves
\begin{center}\rule{0.5\linewidth}{\linethickness}\end{center}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}1}]:} \PY{k+kn}{import} \PY{n+nn}{os}
\PY{n}{os}\PY{o}{.}\PY{n}{environ}\PY{p}{[}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{CUDA\PYZus{}VISIBLE\PYZus{}DEVICES}\PY{l+s+s2}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{1}\PY{l+s+s2}{\PYZdq{}}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}2}]:} \PY{c+c1}{\PYZsh{} load packages}
\PY{k+kn}{from} \PY{n+nn}{\PYZus{}\PYZus{}future\PYZus{}\PYZus{}} \PY{k}{import} \PY{n}{division}\PY{p}{,} \PY{n}{print\PYZus{}function}
\PY{k+kn}{import} \PY{n+nn}{glob}
\PY{k+kn}{import} \PY{n+nn}{os}
\PY{k+kn}{import} \PY{n+nn}{cv2}
\PY{k+kn}{import} \PY{n+nn}{PIL}
\PY{k+kn}{import} \PY{n+nn}{random}
\PY{k+kn}{import} \PY{n+nn}{numpy} \PY{k}{as} \PY{n+nn}{np}
\PY{c+c1}{\PYZsh{} import pandas as pd}
\PY{k+kn}{import} \PY{n+nn}{matplotlib}\PY{n+nn}{.}\PY{n+nn}{pyplot} \PY{k}{as} \PY{n+nn}{plt}
\PY{k+kn}{import} \PY{n+nn}{matplotlib}\PY{n+nn}{.}\PY{n+nn}{image} \PY{k}{as} \PY{n+nn}{mpimg}
\PY{k+kn}{import} \PY{n+nn}{torch}
\PY{k+kn}{import} \PY{n+nn}{torch}\PY{n+nn}{.}\PY{n+nn}{nn}\PY{n+nn}{.}\PY{n+nn}{init}
\PY{k+kn}{import} \PY{n+nn}{torch}\PY{n+nn}{.}\PY{n+nn}{nn} \PY{k}{as} \PY{n+nn}{nn}
\PY{k+kn}{import} \PY{n+nn}{torch}\PY{n+nn}{.}\PY{n+nn}{optim} \PY{k}{as} \PY{n+nn}{optim}
\PY{k+kn}{import} \PY{n+nn}{torch}\PY{n+nn}{.}\PY{n+nn}{backends}\PY{n+nn}{.}\PY{n+nn}{cudnn} \PY{k}{as} \PY{n+nn}{cudnn}
\PY{k+kn}{import} \PY{n+nn}{torch}\PY{n+nn}{.}\PY{n+nn}{nn}\PY{n+nn}{.}\PY{n+nn}{functional} \PY{k}{as} \PY{n+nn}{F}
\PY{k+kn}{import} \PY{n+nn}{torchvision}\PY{n+nn}{.}\PY{n+nn}{datasets} \PY{k}{as} \PY{n+nn}{dset}
\PY{k+kn}{import} \PY{n+nn}{torchvision}\PY{n+nn}{.}\PY{n+nn}{transforms} \PY{k}{as} \PY{n+nn}{transforms}
\PY{k+kn}{from} \PY{n+nn}{tqdm} \PY{k}{import} \PY{n}{tqdm}
\PY{k+kn}{from} \PY{n+nn}{torch}\PY{n+nn}{.}\PY{n+nn}{autograd} \PY{k}{import} \PY{n}{Variable}
\PY{k+kn}{from} \PY{n+nn}{copy} \PY{k}{import} \PY{n}{deepcopy}\PY{p}{,} \PY{n}{copy}
\PY{k+kn}{from} \PY{n+nn}{Utils} \PY{k}{import} \PY{n}{cv2\PYZus{}scale36}\PY{p}{,} \PY{n}{cv2\PYZus{}scale}\PY{p}{,} \PY{n}{np\PYZus{}reshape}\PY{p}{,} \PY{n}{np\PYZus{}reshape64}
\PY{k+kn}{from} \PY{n+nn}{scipy}\PY{n+nn}{.}\PY{n+nn}{optimize} \PY{k}{import} \PY{n}{linear\PYZus{}sum\PYZus{}assignment}
\PY{n}{np}\PY{o}{.}\PY{n}{set\PYZus{}printoptions}\PY{p}{(}\PY{n}{suppress}\PY{o}{=}\PY{k+kc}{True}\PY{p}{)}
\end{Verbatim}
\hypertarget{compute-the-fundamental-matrix-f-for-the-manually-selected-keypoints}{%
\section{Compute the fundamental matrix F for the manually selected
keypoints}\label{compute-the-fundamental-matrix-f-for-the-manually-selected-keypoints}}
First, generation of the C0 matrices for each pairs
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}15}]:} \PY{c+c1}{\PYZsh{} Image 11 and 12}
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\PY{c+c1}{\PYZsh{}print(C0)}
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\PY{c+c1}{\PYZsh{} Coordinates of the keypoints for each image 1 of the five pairs}
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\PY{c+c1}{\PYZsh{} Coordinates of the keypoints for each image 2 of the five pairs}
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\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
5
\end{Verbatim}
\hypertarget{compute-the-fundamental-matrix-f0-based-on-c0-using-wf-0}{%
\subsubsection{Compute the Fundamental Matrix F0 based on C0 using: W*f
= 0}\label{compute-the-fundamental-matrix-f0-based-on-c0-using-wf-0}}
\begin{Verbatim}[commandchars=\\\{\}]
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\PY{c+c1}{\PYZsh{} SVD}
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\PY{n+nb}{print}\PY{p}{(}\PY{n}{F}\PY{p}{)}
\PY{n}{torch}\PY{o}{.}\PY{n}{save}\PY{p}{(}\PY{n}{F}\PY{p}{,} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/fundamental\PYZus{}matrix\PYZus{}0\PYZus{}images\PYZus{}pair\PYZus{}}\PY{l+s+si}{\PYZob{}\PYZcb{}}\PY{l+s+s2}{\PYZdq{}}\PY{o}{.}\PY{n}{format}\PY{p}{(}\PY{n}{m}\PY{o}{+}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}\PYZus{}}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
Image 1: W matrix
[[ 25597. 33748. 143. 41528. 54752. 232. 179. 236. 1.]
[ 944. 6400. 16. 23600. 160000. 400. 59. 400. 1.]
[ 5723. 28320. 59. 46560. 230400. 480. 97. 480. 1.]
[ 32565. 83166. 167. 97500. 249000. 500. 195. 498. 1.]
[137940. 207273. 363. 216220. 324899. 569. 380. 571. 1.]
[363573. 246561. 597. 250299. 169743. 411. 609. 413. 1.]
[206067. 287421. 447. 295501. 412163. 641. 461. 643. 1.]
[784068. 43071. 879. 44600. 2450. 50. 892. 49. 1.]
[610742. 413930. 781. 412896. 279840. 528. 782. 530. 1.]
[606841. 497002. 779. 495444. 405768. 636. 779. 638. 1.]]
\_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_
f = last column V transposed
[-0.00000012 0.00004452 -0.02110133 -0.00004641 -0.00000091 0.01201702
0.02204132 -0.00950205 -0.99941694]
Image 1: Fundamental Matrix F0
[[-0.00000012 0.00004452 -0.02110133]
[-0.00004641 -0.00000091 0.01201702]
[ 0.02204132 -0.00950205 -0.99941694]]
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Image 2: W matrix
[[ 832. 2912. 16. 9516. 33306. 183. 52. 182. 1.]
[121910. 60120. 334. 65700. 32400. 180. 365. 180. 1.]
[152592. 53108. 374. 58344. 20306. 143. 408. 142. 1.]
[331452. 108252. 558. 115236. 37636. 194. 594. 194. 1.]
[192042. 101097. 423. 108960. 57360. 240. 454. 239. 1.]
[374463. 265320. 603. 273861. 194040. 441. 621. 440. 1.]
[ 99189. 133797. 309. 139314. 187922. 434. 321. 433. 1.]
[ 10622. 30738. 94. 37177. 107583. 329. 113. 327. 1.]
[134520. 113988. 354. 122740. 104006. 323. 380. 322. 1.]
[ 41172. 40232. 188. 47304. 46224. 216. 219. 214. 1.]]
\_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_
f = last column V transposed
[-0.00000042 0.0000887 -0.02176812 -0.00008699 -0.00000711 0.03859894
0.02178061 -0.03319439 -0.99822843]
Image 2: Fundamental Matrix F0
[[-0.00000042 0.0000887 -0.02176812]
[-0.00008699 -0.00000711 0.03859894]
[ 0.02178061 -0.03319439 -0.99822843]]
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Image 3: W matrix
[[ 41000. 37720. 205. 37000. 34040. 185. 200. 184. 1.]
[ 60198. 74422. 254. 69678. 86142. 294. 237. 293. 1.]
[166992. 53676. 426. 49000. 15750. 125. 392. 126. 1.]
[ 32802. 9625. 77. 54528. 16000. 128. 426. 125. 1.]
[ 17040. 54528. 426. 5000. 16000. 125. 40. 128. 1.]
[ 31476. 27267. 183. 25628. 22201. 149. 172. 149. 1.]
[ 48805. 33823. 227. 32035. 22201. 149. 215. 149. 1.]
[ 67068. 23460. 276. 20655. 7225. 85. 243. 85. 1.]
[ 8547. 4773. 111. 3311. 1849. 43. 77. 43. 1.]
[ 64989. 20169. 249. 21141. 6561. 81. 261. 81. 1.]]
\_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_
f = last column V transposed
[-0.00000146 -0.00015244 0.01749345 0.00011652 0.00001653 -0.24890633
-0.01287673 0.25466266 -0.93419522]
Image 3: Fundamental Matrix F0
[[-0.00000146 -0.00015244 0.01749345]
[ 0.00011652 0.00001653 -0.24890633]
[-0.01287673 0.25466266 -0.93419522]]
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Image 4: W matrix
[[ 1408. 8800. 44. 6336. 39600. 198. 32. 200. 1.]
[157700. 41420. 380. 46895. 12317. 113. 415. 109. 1.]
[251563. 72150. 481. 76881. 22050. 147. 523. 150. 1.]
[166964. 234960. 356. 291249. 409860. 621. 469. 660. 1.]
[127444. 217138. 302. 281896. 480292. 668. 422. 719. 1.]
[ 78637. 113353. 263. 124384. 179296. 416. 299. 431. 1.]
[ 6474. 38180. 83. 33930. 200100. 435. 78. 460. 1.]
[196794. 268801. 377. 346086. 472719. 663. 522. 713. 1.]
[ 27030. 60738. 159. 63410. 142486. 373. 170. 382. 1.]
[ 11130. 64365. 105. 59360. 343280. 560. 106. 613. 1.]]
\_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_
f = last column V transposed
[ 0.00000426 0.00009031 -0.07760512 -0.0000925 -0.0000011 0.00610541
0.06847118 -0.00572924 0.99459491]
Image 4: Fundamental Matrix F0
[[ 0.00000426 0.00009031 -0.07760512]
[-0.0000925 -0.0000011 0.00610541]
[ 0.06847118 -0.00572924 0.99459491]]
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
Image 5: W matrix
[[ 544896. 56320. 704. 56502. 5840. 73. 774. 80.
1.]
[ 298496. 240128. 512. 270512. 217616. 464. 583. 469.
1.]
[ 973440. 428160. 960. 448188. 197132. 442. 1014. 446.
1.]
[ 832893. 1117620. 887. 1183140. 1587600. 1260. 939. 1260.
1.]
[ 844778. 394706. 893. 415294. 194038. 439. 946. 442.
1.]
[ 9798. 62376. 69. 128084. 815408. 902. 142. 904.
1.]
[1243008. 1336881. 1079. 1427328. 1535121. 1239. 1152. 1239.
1.]
[ 319662. 504450. 531. 570696. 900600. 948. 602. 950.
1.]
[ 17955. 114240. 105. 186048. 1183744. 1088. 171. 1088.
1.]
[1556060. 1179750. 1210. 1253850. 950625. 975. 1286. 975.
1.]]
\_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_ \_\_
f = last column V transposed
[ 0.00000003 0.00000599 -0.00670189 -0.0000064 -0.0000001 -0.02166038
0.00710481 0.02268284 -0.99946032]
Image 5: Fundamental Matrix F0
[[ 0.00000003 0.00000599 -0.00670189]
[-0.0000064 -0.0000001 -0.02166038]
[ 0.00710481 0.02268284 -0.99946032]]
\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_
\end{Verbatim}
\hypertarget{detect-100-strongest-interest-points-sift-in-each-image-then-compute-their-deep-features-and-finally-match-them-one-to-one}{%
\subsection{Detect 100 strongest interest points (SIFT) in each image,
then, compute their deep features, and finally match them
one-to-one}\label{detect-100-strongest-interest-points-sift-in-each-image-then-compute-their-deep-features-and-finally-match-them-one-to-one}}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}19}]:} \PY{c+c1}{\PYZsh{} parameters setting}
\PY{n}{query\PYZus{}path} \PY{o}{=} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{stereo/image1/}\PY{l+s+s2}{\PYZdq{}}
\PY{n}{image\PYZus{}path} \PY{o}{=} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{stereo/image2/}\PY{l+s+s2}{\PYZdq{}}
\PY{n}{query\PYZus{}num} \PY{o}{=} \PY{l+m+mi}{5}
\PY{n}{image\PYZus{}num} \PY{o}{=} \PY{l+m+mi}{5}
\PY{n}{kps\PYZus{}num} \PY{o}{=} \PY{l+m+mi}{100} \PY{c+c1}{\PYZsh{}number of keypoints we want to detect }
\PY{n}{patch\PYZus{}size} \PY{o}{=} \PY{l+m+mi}{32}
\PY{n}{patches} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{zeros}\PY{p}{(}\PY{n}{query\PYZus{}num}\PY{o}{+}\PY{n}{image\PYZus{}num}\PY{p}{,} \PY{n}{kps\PYZus{}num}\PY{p}{,}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{patch\PYZus{}size}\PY{p}{,} \PY{n}{patch\PYZus{}size}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}4}]:} \PY{c+c1}{\PYZsh{} Initiate SURF detector}
\PY{n}{surf} \PY{o}{=} \PY{n}{cv2}\PY{o}{.}\PY{n}{xfeatures2d}\PY{o}{.}\PY{n}{SURF\PYZus{}create}\PY{p}{(}\PY{n}{kps\PYZus{}num}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}5}]:} \PY{k}{def} \PY{n+nf}{getPatches}\PY{p}{(}\PY{n}{kps}\PY{p}{,} \PY{n}{img}\PY{p}{,} \PY{n}{size}\PY{o}{=}\PY{l+m+mi}{32}\PY{p}{,} \PY{n}{num}\PY{o}{=}\PY{l+m+mi}{500}\PY{p}{)}\PY{p}{:}
\PY{n}{res} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{zeros}\PY{p}{(}\PY{n}{num}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{,} \PY{n}{size}\PY{p}{,} \PY{n}{size}\PY{p}{)}
\PY{k}{if} \PY{n+nb}{type}\PY{p}{(}\PY{n}{img}\PY{p}{)} \PY{o+ow}{is} \PY{n}{np}\PY{o}{.}\PY{n}{ndarray}\PY{p}{:}
\PY{n}{img} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{from\PYZus{}numpy}\PY{p}{(}\PY{n}{img}\PY{p}{)}
\PY{n}{h}\PY{p}{,} \PY{n}{w} \PY{o}{=} \PY{n}{img}\PY{o}{.}\PY{n}{shape} \PY{c+c1}{\PYZsh{} note: for image, the x direction is the verticle, y\PYZhy{}direction is the horizontal...}
\PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{n}{num}\PY{p}{)}\PY{p}{:}
\PY{n}{cx}\PY{p}{,} \PY{n}{cy} \PY{o}{=} \PY{n}{kps}\PY{p}{[}\PY{n}{i}\PY{p}{]}
\PY{n}{cx}\PY{p}{,} \PY{n}{cy} \PY{o}{=} \PY{n+nb}{int}\PY{p}{(}\PY{n}{cx}\PY{p}{)}\PY{p}{,} \PY{n+nb}{int}\PY{p}{(}\PY{n}{cy}\PY{p}{)}
\PY{n}{dd} \PY{o}{=} \PY{n+nb}{int}\PY{p}{(}\PY{n}{size}\PY{o}{/}\PY{l+m+mi}{2}\PY{p}{)}
\PY{n}{xmin}\PY{p}{,} \PY{n}{xmax} \PY{o}{=} \PY{n+nb}{max}\PY{p}{(}\PY{l+m+mi}{0}\PY{p}{,} \PY{n}{cx} \PY{o}{\PYZhy{}} \PY{n}{dd}\PY{p}{)}\PY{p}{,} \PY{n+nb}{min}\PY{p}{(}\PY{n}{w}\PY{p}{,} \PY{n}{cx} \PY{o}{+} \PY{n}{dd} \PY{p}{)} \PY{o}{\PYZhy{}} \PY{l+m+mi}{1}
\PY{n}{ymin}\PY{p}{,} \PY{n}{ymax} \PY{o}{=} \PY{n+nb}{max}\PY{p}{(}\PY{l+m+mi}{0}\PY{p}{,} \PY{n}{cy} \PY{o}{\PYZhy{}} \PY{n}{dd}\PY{p}{)}\PY{p}{,} \PY{n+nb}{min}\PY{p}{(}\PY{n}{h}\PY{p}{,} \PY{n}{cy} \PY{o}{+} \PY{n}{dd} \PY{p}{)} \PY{o}{\PYZhy{}} \PY{l+m+mi}{1}
\PY{n}{xmin\PYZus{}res}\PY{p}{,} \PY{n}{xmax\PYZus{}res} \PY{o}{=} \PY{n}{dd} \PY{o}{\PYZhy{}} \PY{n+nb}{min}\PY{p}{(}\PY{n}{dd}\PY{p}{,}\PY{n}{cx}\PY{p}{)}\PY{p}{,} \PY{n}{dd} \PY{o}{+} \PY{n+nb}{min}\PY{p}{(}\PY{n}{dd}\PY{p}{,} \PY{n}{w} \PY{o}{\PYZhy{}} \PY{n}{cx}\PY{p}{)}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}
\PY{n}{ymin\PYZus{}res}\PY{p}{,} \PY{n}{ymax\PYZus{}res} \PY{o}{=} \PY{n}{dd} \PY{o}{\PYZhy{}} \PY{n+nb}{min}\PY{p}{(}\PY{n}{dd}\PY{p}{,}\PY{n}{cy}\PY{p}{)}\PY{p}{,} \PY{n}{dd} \PY{o}{+} \PY{n+nb}{min}\PY{p}{(}\PY{n}{dd}\PY{p}{,} \PY{n}{h} \PY{o}{\PYZhy{}} \PY{n}{cy}\PY{p}{)}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}
\PY{n}{res}\PY{p}{[}\PY{n}{i}\PY{p}{,} \PY{l+m+mi}{0}\PY{p}{,} \PY{n}{ymin\PYZus{}res}\PY{p}{:} \PY{n}{ymax\PYZus{}res}\PY{p}{,} \PY{n}{xmin\PYZus{}res}\PY{p}{:} \PY{n}{xmax\PYZus{}res}\PY{p}{]} \PY{o}{=} \PY{n}{img}\PY{p}{[}\PY{n}{ymin}\PY{p}{:} \PY{n}{ymax}\PY{p}{,} \PY{n}{xmin}\PY{p}{:} \PY{n}{xmax}\PY{p}{]}
\PY{k}{return} \PY{n}{res}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}28}]:} \PY{c+c1}{\PYZsh{} tensor for query/image patches}
\PY{n}{save} \PY{o}{=} \PY{k+kc}{False}
\PY{k}{for} \PY{n}{idx} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{n}{query\PYZus{}num}\PY{o}{+}\PY{n}{image\PYZus{}num}\PY{p}{)}\PY{p}{:}
\PY{k}{if} \PY{n}{idx} \PY{o}{==} \PY{l+m+mi}{0}\PY{p}{:}
\PY{n+nb}{print}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{Images 1: coordinates pi}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{k}{if} \PY{n}{idx} \PY{o}{==} \PY{n}{query\PYZus{}num}\PY{p}{:}
\PY{n+nb}{print}\PY{p}{(}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{Images 2: coordinates qi}\PY{l+s+s1}{\PYZsq{}}\PY{p}{)}
\PY{k}{if} \PY{n}{idx} \PY{o}{\PYZlt{}} \PY{n}{query\PYZus{}num}\PY{p}{:}
\PY{n}{img\PYZus{}dir} \PY{o}{=} \PY{n}{os}\PY{o}{.}\PY{n}{path}\PY{o}{.}\PY{n}{join}\PY{p}{(}\PY{n}{query\PYZus{}path}\PY{p}{,}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{image}\PY{l+s+si}{\PYZob{}\PYZcb{}}\PY{l+s+s2}{.png}\PY{l+s+s2}{\PYZdq{}}\PY{o}{.}\PY{n}{format}\PY{p}{(}\PY{n}{idx}\PY{o}{+}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{)}
\PY{k}{else}\PY{p}{:}
\PY{n}{img\PYZus{}dir} \PY{o}{=} \PY{n}{os}\PY{o}{.}\PY{n}{path}\PY{o}{.}\PY{n}{join}\PY{p}{(}\PY{n}{image\PYZus{}path}\PY{p}{,}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{image}\PY{l+s+si}{\PYZob{}\PYZcb{}}\PY{l+s+s2}{.png}\PY{l+s+s2}{\PYZdq{}}\PY{o}{.}\PY{n}{format}\PY{p}{(}\PY{n}{idx}\PY{o}{+}\PY{l+m+mi}{1}\PY{o}{\PYZhy{}}\PY{n}{query\PYZus{}num}\PY{p}{)}\PY{p}{)}
\PY{n}{image} \PY{o}{=} \PY{n}{cv2}\PY{o}{.}\PY{n}{imread}\PY{p}{(}\PY{n}{img\PYZus{}dir}\PY{p}{)}
\PY{n}{img}\PY{o}{=} \PY{n}{cv2}\PY{o}{.}\PY{n}{cvtColor}\PY{p}{(}\PY{n}{image}\PY{p}{,}\PY{n}{cv2}\PY{o}{.}\PY{n}{COLOR\PYZus{}BGR2GRAY}\PY{p}{)}
\PY{c+c1}{\PYZsh{}\PYZsh{} find the keypoints and descriptors with SURF}
\PY{n}{kps}\PY{p}{,} \PY{n}{des} \PY{o}{=} \PY{n}{surf}\PY{o}{.}\PY{n}{detectAndCompute}\PY{p}{(}\PY{n}{img}\PY{p}{,} \PY{k+kc}{None}\PY{p}{)}
\PY{n}{keypoints\PYZus{}img} \PY{o}{=} \PY{p}{[}\PY{n}{kps}\PY{p}{[}\PY{n}{a}\PY{p}{]}\PY{o}{.}\PY{n}{pt} \PY{k}{for} \PY{n}{a} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{n}{kps\PYZus{}num}\PY{p}{)}\PY{p}{]}
\PY{n}{keypoints\PYZus{}img2} \PY{o}{=} \PY{p}{[}\PY{n}{kps}\PY{p}{[}\PY{n}{a}\PY{p}{]} \PY{k}{for} \PY{n}{a} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{n}{kps\PYZus{}num}\PY{p}{)}\PY{p}{]}
\PY{n}{patches}\PY{p}{[}\PY{n}{idx}\PY{p}{]} \PY{o}{=} \PY{n}{getPatches}\PY{p}{(}\PY{n}{keypoints\PYZus{}img}\PY{p}{,} \PY{n}{img}\PY{p}{,} \PY{n}{size}\PY{o}{=}\PY{n}{patch\PYZus{}size}\PY{p}{,} \PY{n}{num}\PY{o}{=}\PY{n}{kps\PYZus{}num}\PY{p}{)}
\PY{c+c1}{\PYZsh{}\PYZsh{} plot keypoints on each image}
\PY{n}{img2} \PY{o}{=} \PY{n}{cv2}\PY{o}{.}\PY{n}{drawKeypoints}\PY{p}{(}\PY{n}{img}\PY{p}{,} \PY{n}{keypoints\PYZus{}img2}\PY{p}{,} \PY{k+kc}{None}\PY{p}{,} \PY{n}{color}\PY{o}{=}\PY{p}{(}\PY{l+m+mi}{255}\PY{p}{,}\PY{l+m+mi}{0}\PY{p}{,}\PY{l+m+mi}{0}\PY{p}{)}\PY{p}{,} \PY{n}{flags}\PY{o}{=}\PY{n}{cv2}\PY{o}{.}\PY{n}{DRAW\PYZus{}MATCHES\PYZus{}FLAGS\PYZus{}DRAW\PYZus{}RICH\PYZus{}KEYPOINTS}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{imshow}\PY{p}{(}\PY{n}{img2}\PY{p}{)}
\PY{n}{plt}\PY{o}{.}\PY{n}{show}\PY{p}{(}\PY{p}{)}
\PY{c+c1}{\PYZsh{} Saving the coordinates (x,y) of the detected keypoints}
\PY{k}{if} \PY{n}{save}\PY{p}{:}
\PY{k}{if} \PY{n}{idx} \PY{o}{\PYZlt{}} \PY{n}{query\PYZus{}num}\PY{p}{:}
\PY{n}{torch}\PY{o}{.}\PY{n}{save}\PY{p}{(}\PY{n}{keypoints\PYZus{}img}\PY{p}{,} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image1\PYZus{}}\PY{l+s+si}{\PYZob{}\PYZcb{}}\PY{l+s+s2}{.pt}\PY{l+s+s2}{\PYZdq{}}\PY{o}{.}\PY{n}{format}\PY{p}{(}\PY{n}{idx}\PY{o}{+}\PY{l+m+mi}{1}\PY{p}{)}\PY{p}{)}
\PY{k}{else}\PY{p}{:}
\PY{n}{torch}\PY{o}{.}\PY{n}{save}\PY{p}{(}\PY{n}{keypoints\PYZus{}img}\PY{p}{,} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image2\PYZus{}}\PY{l+s+si}{\PYZob{}\PYZcb{}}\PY{l+s+s2}{.pt}\PY{l+s+s2}{\PYZdq{}}\PY{o}{.}\PY{n}{format}\PY{p}{(}\PY{n}{idx}\PY{o}{+}\PY{l+m+mi}{1}\PY{o}{\PYZhy{}}\PY{n}{query\PYZus{}num}\PY{p}{)}\PY{p}{)}
\PY{n}{output\PYZus{}dir\PYZus{}patches} \PY{o}{=} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/keypoints\PYZus{}patches\PYZus{}images.pt}\PY{l+s+s2}{\PYZdq{}}
\PY{n}{torch}\PY{o}{.}\PY{n}{save}\PY{p}{(}\PY{n}{patches}\PY{p}{,} \PY{n}{output\PYZus{}dir\PYZus{}patches}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{patches}\PY{o}{.}\PY{n}{shape}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
Images 1: coordinates pi
\end{Verbatim}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_1.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_2.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_3.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_4.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_5.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{Verbatim}[commandchars=\\\{\}]
Images 2: coordinates qi
\end{Verbatim}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_7.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_8.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_9.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_10.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{center}
\adjustimage{max size={0.9\linewidth}{0.9\paperheight}}{output_12_11.png}
\end{center}
{ \hspace*{\fill} \\}
\begin{Verbatim}[commandchars=\\\{\}]
torch.Size([10, 100, 1, 32, 32])
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor} }]:} \PY{c+c1}{\PYZsh{}\PYZsh{}\PYZsh{} Load the coordinates of the detected keypoints (using SIFT)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}41}]:} \PY{n}{keypoints\PYZus{}coordinates\PYZus{}11} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image1\PYZus{}1.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}12} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image1\PYZus{}2.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}13} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image1\PYZus{}3.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}14} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image1\PYZus{}4.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}15} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image1\PYZus{}5.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}11}\PY{p}{)}\PY{p}{)} \PY{c+c1}{\PYZsh{} = 100}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}21} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image2\PYZus{}1.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}22} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image2\PYZus{}2.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}23} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image2\PYZus{}3.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}24} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image2\PYZus{}4.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}25} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/detected\PYZus{}SIFT\PYZus{}keypoints\PYZus{}coordinates\PYZus{}image2\PYZus{}5.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{c+c1}{\PYZsh{}print(keypoints\PYZus{}coordinates\PYZus{}12)}
\PY{c+c1}{\PYZsh{} IMAGES 1}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}p} \PY{o}{=} \PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}11}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}12}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}13}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}14}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}15}\PY{p}{]}
\PY{c+c1}{\PYZsh{} IMAGES 2}
\PY{n}{keypoints\PYZus{}coordinates\PYZus{}q} \PY{o}{=} \PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}21}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}22}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}23}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}24}\PY{p}{]}\PY{p}{,}\PY{p}{[}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}25}\PY{p}{]}
\PY{n}{keypoints\PYZus{}coordinates} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{zeros}\PY{p}{(}\PY{n}{query\PYZus{}num}\PY{o}{+}\PY{n}{image\PYZus{}num}\PY{p}{,}\PY{l+m+mi}{2}\PY{p}{,} \PY{n}{kps\PYZus{}num}\PY{p}{,} \PY{l+m+mi}{3}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}p}\PY{p}{)}\PY{p}{)} \PY{c+c1}{\PYZsh{} =5}
\PY{n+nb}{print}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}q}\PY{p}{)}\PY{p}{)} \PY{c+c1}{\PYZsh{} =5}
\PY{n+nb}{print}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}q}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{)}\PY{p}{)} \PY{c+c1}{\PYZsh{} =100}
\PY{c+c1}{\PYZsh{}print(keypoints\PYZus{}coordinates\PYZus{}p[0][0][1])}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
100
5
5
100
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor} }]:}
\end{Verbatim}
\hypertarget{import-pre-trained-cnn}{%
\subsection{Import pre-trained CNN}\label{import-pre-trained-cnn}}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}42}]:} \PY{c+c1}{\PYZsh{} import network, load pretrained weights, and turn on testing mode}
\PY{k+kn}{from} \PY{n+nn}{descriptor\PYZus{}CNN3} \PY{k}{import} \PY{n}{DesNet}
\PY{n}{model} \PY{o}{=} \PY{n}{DesNet}\PY{p}{(}\PY{p}{)}
\PY{n}{model}\PY{o}{.}\PY{n}{cuda}\PY{p}{(}\PY{p}{)}
\PY{n}{model}\PY{o}{.}\PY{n}{eval}\PY{p}{(}\PY{p}{)}
\PY{n}{trained\PYZus{}weights} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{checkpoint.pth}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\PY{n}{model}\PY{o}{.}\PY{n}{load\PYZus{}state\PYZus{}dict}\PY{p}{(}\PY{n}{trained\PYZus{}weights}\PY{p}{[}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{state\PYZus{}dict}\PY{l+s+s2}{\PYZdq{}}\PY{p}{]}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}43}]:} \PY{c+c1}{\PYZsh{} Load the patches }
\PY{n}{patches\PYZus{}dir\PYZus{}images} \PY{o}{=} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/keypoints\PYZus{}patches\PYZus{}images.pt}\PY{l+s+s2}{\PYZdq{}}
\PY{n}{patches} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{n}{patches\PYZus{}dir\PYZus{}images}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{patches}\PY{o}{.}\PY{n}{shape}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
torch.Size([10, 100, 1, 32, 32])
\end{Verbatim}
\hypertarget{getting-the-keypoints-descriptions-using-the-previously-imported-cnn}{%
\subsection{Getting the keypoints descriptions using the previously
imported
CNN}\label{getting-the-keypoints-descriptions-using-the-previously-imported-cnn}}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}44}]:} \PY{n}{model}\PY{o}{.}\PY{n}{eval}\PY{p}{(}\PY{p}{)}
\PY{k}{with} \PY{n}{torch}\PY{o}{.}\PY{n}{no\PYZus{}grad}\PY{p}{(}\PY{p}{)}\PY{p}{:}
\PY{n}{des1} \PY{o}{=} \PY{n}{model}\PY{p}{(}\PY{n}{patches}\PY{p}{[}\PY{p}{:}\PY{n}{query\PYZus{}num}\PY{p}{]}\PY{o}{.}\PY{n}{view}\PY{p}{(}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{,} \PY{n}{patch\PYZus{}size}\PY{p}{,}\PY{n}{patch\PYZus{}size}\PY{p}{)}\PY{o}{.}\PY{n}{cuda}\PY{p}{(}\PY{p}{)}\PY{p}{)}\PY{o}{.}\PY{n}{view}\PY{p}{(}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{kps\PYZus{}num}\PY{p}{,} \PY{l+m+mi}{128}\PY{p}{)}
\PY{n}{des2} \PY{o}{=} \PY{n}{model}\PY{p}{(}\PY{n}{patches}\PY{p}{[}\PY{n}{query\PYZus{}num}\PY{p}{:}\PY{p}{]}\PY{o}{.}\PY{n}{view}\PY{p}{(}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{,} \PY{n}{patch\PYZus{}size}\PY{p}{,}\PY{n}{patch\PYZus{}size}\PY{p}{)}\PY{o}{.}\PY{n}{cuda}\PY{p}{(}\PY{p}{)}\PY{p}{)}\PY{o}{.}\PY{n}{view}\PY{p}{(}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{,} \PY{n}{kps\PYZus{}num}\PY{p}{,} \PY{l+m+mi}{128}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}45}]:} \PY{n+nb}{print}\PY{p}{(}\PY{n}{des1}\PY{o}{.}\PY{n}{shape}\PY{p}{)} \PY{c+c1}{\PYZsh{} [number of images, number of keypoints, 128]}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{des2}\PY{o}{.}\PY{n}{shape}\PY{p}{)} \PY{c+c1}{\PYZsh{} [number of images, number of keypoints, 128]}
\PY{c+c1}{\PYZsh{} save keypoints descriptions into a pytorch file}
\PY{n}{des\PYZus{}dir} \PY{o}{=} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/images\PYZus{}keypoints\PYZus{}descriptions.pt}\PY{l+s+s2}{\PYZdq{}}
\PY{c+c1}{\PYZsh{}torch.save(description\PYZus{}images, des\PYZus{}dir)}
\PY{c+c1}{\PYZsh{} save descriptions }
\PY{c+c1}{\PYZsh{}print(des1)}
\PY{n}{torch}\PY{o}{.}\PY{n}{save}\PY{p}{(}\PY{p}{[}\PY{n}{des1}\PY{p}{,} \PY{n}{des2}\PY{p}{]}\PY{p}{,} \PY{n}{des\PYZus{}dir}\PY{p}{)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
torch.Size([5, 100, 128])
torch.Size([5, 100, 128])
\end{Verbatim}
\hypertarget{getting-one-to-one-similitude-matrix}{%
\section{Getting one to one similitude
matrix}\label{getting-one-to-one-similitude-matrix}}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}13}]:} \PY{p}{[}\PY{n}{des1}\PY{p}{,} \PY{n}{des2}\PY{p}{]} \PY{o}{=} \PY{n}{torch}\PY{o}{.}\PY{n}{load}\PY{p}{(}\PY{n}{des\PYZus{}dir}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{des1}\PY{o}{.}\PY{n}{shape}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{des2}\PY{o}{.}\PY{n}{shape}\PY{p}{)}
\PY{c+c1}{\PYZsh{}print(images\PYZus{}description)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
torch.Size([5, 100, 128])
torch.Size([5, 100, 128])
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}47}]:} \PY{n+nb}{print}\PY{p}{(}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}p}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{99}\PY{p}{]}\PY{p}{)}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{keypoints\PYZus{}coordinates\PYZus{}p}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)}
\PY{c+c1}{\PYZsh{}keypoints\PYZus{}coordinates\PYZus{}p[number of the pair][?][number of the (x,y)]}
\PY{c+c1}{\PYZsh{}print(keypoints\PYZus{}coordinates\PYZus{}p)}
\end{Verbatim}
\begin{Verbatim}[commandchars=\\\{\}]
(138.15528869628906, 308.47613525390625)
(447.8544921875, 639.9784545898438)
\end{Verbatim}
\hypertarget{hungarian}{%
\subsection{Hungarian}\label{hungarian}}
\begin{Verbatim}[commandchars=\\\{\}]
{\color{incolor}In [{\color{incolor}48}]:} \PY{n}{save} \PY{o}{=} \PY{k+kc}{False}
\PY{k+kn}{from} \PY{n+nn}{munkres} \PY{k}{import} \PY{n}{Munkres}
\PY{n}{C\PYZus{}onetoone} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{zeros}\PY{p}{(}\PY{p}{(}\PY{l+m+mi}{5}\PY{p}{,}\PY{l+m+mi}{100}\PY{p}{,}\PY{l+m+mi}{2}\PY{p}{,}\PY{l+m+mi}{3}\PY{p}{)}\PY{p}{)}
\PY{n}{sim\PYZus{}matrix} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{zeros}\PY{p}{(}\PY{p}{(}\PY{l+m+mi}{5}\PY{p}{,}\PY{l+m+mi}{5}\PY{p}{)}\PY{p}{)}
\PY{k}{for} \PY{n}{qkeypoint} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{l+m+mi}{5}\PY{p}{)}\PY{p}{:}
\PY{k}{for} \PY{n}{images\PYZus{}keypoint} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{l+m+mi}{5}\PY{p}{)}\PY{p}{:}
\PY{n}{cost\PYZus{}matrix} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{zeros}\PY{p}{(}\PY{p}{(}\PY{l+m+mi}{100}\PY{p}{,} \PY{l+m+mi}{100}\PY{p}{)}\PY{p}{)}
\PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{l+m+mi}{100}\PY{p}{)}\PY{p}{:}
\PY{k}{for} \PY{n}{j} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{l+m+mi}{100}\PY{p}{)}\PY{p}{:}
\PY{n}{cost\PYZus{}matrix}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{[}\PY{n}{j}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{linalg}\PY{o}{.}\PY{n}{norm}\PY{p}{(}\PY{n}{des1}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{o}{.}\PY{n}{cpu}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{numpy}\PY{p}{(}\PY{p}{)} \PY{o}{\PYZhy{}} \PY{n}{des2}\PY{p}{[}\PY{n}{images\PYZus{}keypoint}\PY{p}{]}\PY{p}{[}\PY{n}{j}\PY{p}{]}\PY{o}{.}\PY{n}{cpu}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{numpy}\PY{p}{(}\PY{p}{)}\PY{p}{)}
\PY{c+c1}{\PYZsh{} Hungarian: one\PYZhy{}to\PYZhy{}one matching}
\PY{n}{m} \PY{o}{=} \PY{n}{Munkres}\PY{p}{(}\PY{p}{)}
\PY{n}{indexes} \PY{o}{=} \PY{n}{m}\PY{o}{.}\PY{n}{compute}\PY{p}{(}\PY{n}{np}\PY{o}{.}\PY{n}{copy}\PY{p}{(}\PY{n}{cost\PYZus{}matrix}\PY{p}{)}\PY{p}{)}
\PY{k}{for} \PY{n}{m} \PY{o+ow}{in} \PY{n}{indexes}\PY{p}{:}
\PY{n}{sim\PYZus{}matrix}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{,} \PY{n}{images\PYZus{}keypoint}\PY{p}{]} \PY{o}{+}\PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{exp}\PY{p}{(}\PY{o}{\PYZhy{}}\PY{n}{cost\PYZus{}matrix}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{)}
\PY{k}{for} \PY{n}{m} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{l+m+mi}{0}\PY{p}{,}\PY{n+nb}{len}\PY{p}{(}\PY{n}{indexes}\PY{p}{)}\PY{p}{)}\PY{p}{:}
\PY{n}{C\PYZus{}onetoone}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]} \PY{o}{=} \PY{n}{keypoints\PYZus{}coordinates\PYZus{}p}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{n}{indexes}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}
\PY{n}{C\PYZus{}onetoone}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]} \PY{o}{=} \PY{n}{keypoints\PYZus{}coordinates\PYZus{}p}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{n}{indexes}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}
\PY{n}{C\PYZus{}onetoone}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} \PY{o}{=} \PY{l+m+mi}{1}
\PY{n}{C\PYZus{}onetoone}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]} \PY{o}{=} \PY{n}{keypoints\PYZus{}coordinates\PYZus{}q}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{n}{indexes}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}
\PY{n}{C\PYZus{}onetoone}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]} \PY{o}{=} \PY{n}{keypoints\PYZus{}coordinates\PYZus{}q}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{n}{indexes}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}
\PY{n}{C\PYZus{}onetoone}\PY{p}{[}\PY{n}{qkeypoint}\PY{p}{]}\PY{p}{[}\PY{n}{m}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} \PY{o}{=} \PY{l+m+mi}{1}
\PY{n+nb}{print}\PY{p}{(}\PY{n}{C\PYZus{}onetoone}\PY{p}{)}
\PY{k}{if} \PY{n}{save}\PY{p}{:}
\PY{n}{torch}\PY{o}{.}\PY{n}{save}\PY{p}{(}\PY{n}{C\PYZus{}onetoone}\PY{p}{,} \PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{results/C\PYZus{}onetoone\PYZus{}coordinates\PYZus{}100.pt}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
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