{"diffoscope-json-version": 1, "source1": "/srv/reproducible-results/rbuild-debian/r-b-build.69txe1bE/b1/g2o_0~20230806-4.1_armhf.changes", "source2": "/srv/reproducible-results/rbuild-debian/r-b-build.69txe1bE/b2/g2o_0~20230806-4.1_armhf.changes", "unified_diff": null, "details": [{"source1": "Files", "source2": "Files", "unified_diff": "@@ -1,5 +1,5 @@\n \n 3438624c2db6aa12d512f3c9a7360ab7 124056 libdevel optional libg2o-dev_0~20230806-4.1_armhf.deb\n- 4ac1a65f7ef4952ffaf27b93173014ce 208954096 doc optional libg2o-doc_0~20230806-4.1_all.deb\n+ e7266cd4387abdfc8cbfd2b81bdc7081 208953828 doc optional libg2o-doc_0~20230806-4.1_all.deb\n 1cb7e1e13a53ab531405e7a175a3ba82 148517668 debug optional libg2o0t64-dbgsym_0~20230806-4.1_armhf.deb\n e46a714874132a014a3ed6b0990b6003 692320 libs optional libg2o0t64_0~20230806-4.1_armhf.deb\n"}, {"source1": "libg2o-doc_0~20230806-4.1_all.deb", "source2": "libg2o-doc_0~20230806-4.1_all.deb", "unified_diff": null, "details": [{"source1": "file list", "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 162192 2024-02-28 09:35:01.000000 control.tar.xz\n--rw-r--r-- 0 0 0 208791712 2024-02-28 09:35:01.000000 data.tar.xz\n+-rw-r--r-- 0 0 0 162172 2024-02-28 09:35:01.000000 control.tar.xz\n+-rw-r--r-- 0 0 0 208791464 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: 313543\n+Installed-Size: 313544\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-April 24, 2024\n+April 25, 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"}]}]}]}]}]}]}