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"source2": "file list", "unified_diff": "@@ -1,3 +1,3 @@\n -rw-r--r-- 0 0 0 4 2024-02-28 09:35:01.000000 debian-binary\n--rw-r--r-- 0 0 0 162176 2024-02-28 09:35:01.000000 control.tar.xz\n--rw-r--r-- 0 0 0 208790636 2024-02-28 09:35:01.000000 data.tar.xz\n+-rw-r--r-- 0 0 0 162128 2024-02-28 09:35:01.000000 control.tar.xz\n+-rw-r--r-- 0 0 0 208792452 2024-02-28 09:35:01.000000 data.tar.xz\n"}, {"source1": "control.tar.xz", "source2": "control.tar.xz", "unified_diff": null, "details": [{"source1": "control.tar", "source2": "control.tar", "unified_diff": null, "details": [{"source1": "./control", "source2": "./control", "unified_diff": "@@ -1,13 +1,13 @@\n Package: libg2o-doc\n Source: g2o\n Version: 0~20230806-4.1\n Architecture: all\n Maintainer: Debian Science Maintainers \n-Installed-Size: 313544\n+Installed-Size: 313543\n Section: doc\n Priority: optional\n Homepage: http://www.g2o.org\n Description: C++ framework for optimizing graph-based nonlinear error functions\n A wide range of problems in robotics as well as in computer-vision involve the\n minimization of a non-linear error function that can be represented as a graph.\n Typical instances are simultaneous localization and mapping (SLAM) or bundle\n"}, {"source1": "./md5sums", "source2": "./md5sums", "unified_diff": null, "details": [{"source1": "./md5sums", "source2": "./md5sums", "comments": ["Files differ"], "unified_diff": null}]}]}]}, {"source1": "data.tar.xz", "source2": "data.tar.xz", "unified_diff": null, "details": [{"source1": "data.tar", "source2": "data.tar", "unified_diff": null, "details": [{"source1": "file list", "source2": "file list", "unified_diff": "@@ -180,15 +180,15 @@\n -rw-r--r-- 0 root (0) root (0) 2075 2023-08-06 13:01:18.000000 ./usr/share/doc/libg2o-dev/examples/tutorial_slam2d/tutorial_slam2d.cpp.gz\n -rw-r--r-- 0 root (0) root (0) 2021 2023-08-06 13:01:18.000000 ./usr/share/doc/libg2o-dev/examples/tutorial_slam2d/types_tutorial_slam2d.cpp\n -rw-r--r-- 0 root (0) root (0) 1613 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09:35:01.000000 ./usr/share/doc/libg2o-dev/html/FlexLexer_8h.html\n -rw-r--r-- 0 root (0) root (0) 1537 2024-02-28 09:35:01.000000 ./usr/share/doc/libg2o-dev/html/FlexLexer_8h__dep__incl.map\n -rw-r--r-- 0 root (0) root (0) 32 2024-02-28 09:35:01.000000 ./usr/share/doc/libg2o-dev/html/FlexLexer_8h__dep__incl.md5\n -rw-r--r-- 0 root (0) root (0) 39947 2024-02-28 09:35:01.000000 ./usr/share/doc/libg2o-dev/html/FlexLexer_8h__dep__incl.png\n -rw-r--r-- 0 root (0) root (0) 503 2024-02-28 09:35:01.000000 ./usr/share/doc/libg2o-dev/html/FlexLexer_8h__incl.map\n -rw-r--r-- 0 root (0) root (0) 32 2024-02-28 09:35:01.000000 ./usr/share/doc/libg2o-dev/html/FlexLexer_8h__incl.md5\n"}, {"source1": "./usr/share/doc/libg2o-dev/g2o.pdf.gz", "source2": "./usr/share/doc/libg2o-dev/g2o.pdf.gz", "unified_diff": null, "details": [{"source1": "g2o.pdf", "source2": "g2o.pdf", "unified_diff": null, "details": [{"source1": "pdftotext {} -", "source2": "pdftotext {} -", "unified_diff": "@@ -1,12 +1,12 @@\n g2o: A general Framework for (Hyper) Graph Optimization\n Giorgio Grisetti, Rainer Ku\u0308mmerle, Hauke Strasdat, Kurt Konolige\n email: {grisetti,kuemmerl}@informatik.uni-freiburg.de\n strasdat@gmail.com konolige@willowgarage.com\n-May 3, 2024\n+May 4, 2024\n In this document we describe a C++ framework for performing the optimization of nonlinear least\n squares problems that can be embedded as a graph or in a hyper-graph. A hyper-graph is an extension\n of a graph where an edge can connect multiple nodes and not only two. Several problems in robotics and\n in computer vision require to find the optimum of an error function with respect of a set of parameters.\n Examples include, popular applications like SLAM and Bundle adjustment.\n In the literature, many approaches have been proposed to address this class of problems. The naive\n implementation of standard methods, like Levenberg-Marquardt or Gauss-Newton can lead to acceptable\n"}]}]}]}]}]}]}