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[66.158.151.227]) by smtp.gmail.com with ESMTPSA id kc4-20020a05622a44c400b00400aa16bf38sm737703qtb.82.2023.08.01.07.02.12 (version=TLS1_3 cipher=TLS_AES_256_GCM_SHA384 bits=256/256); Tue, 01 Aug 2023 07:02:13 -0700 (PDT) From: Maxim Cournoyer To: Ricardo Wurmus Cc: guix-devel@gnu.org Subject: Re: Binary descriptors for OpenCV References: <874jlk9kl3.fsf@elephly.net> Date: Tue, 01 Aug 2023 10:02:11 -0400 In-Reply-To: <874jlk9kl3.fsf@elephly.net> (Ricardo Wurmus's message of "Mon, 31 Jul 2023 15:12:49 +0200") Message-ID: <87o7jqsvx8.fsf@gmail.com> User-Agent: Gnus/5.13 (Gnus v5.13) Emacs/28.2 (gnu/linux) MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable Received-SPF: pass client-ip=2607:f8b0:4864:20::829; envelope-from=maxim.cournoyer@gmail.com; helo=mail-qt1-x829.google.com X-Spam_score_int: -20 X-Spam_score: -2.1 X-Spam_bar: -- X-Spam_report: (-2.1 / 5.0 requ) BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, DKIM_VALID_EF=-0.1, FREEMAIL_FROM=0.001, RCVD_IN_DNSWL_NONE=-0.0001, SPF_HELO_NONE=0.001, SPF_PASS=-0.001, T_SCC_BODY_TEXT_LINE=-0.01 autolearn=ham autolearn_force=no X-Spam_action: no action X-BeenThere: guix-devel@gnu.org X-Mailman-Version: 2.1.29 Precedence: list List-Id: "Development of GNU Guix and the GNU System distribution." List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , Errors-To: guix-devel-bounces+larch=yhetil.org@gnu.org Sender: guix-devel-bounces+larch=yhetil.org@gnu.org X-Migadu-Flow: FLOW_IN X-Migadu-Country: US X-Migadu-Spam-Score: -7.10 X-Spam-Score: -7.10 X-Migadu-Queue-Id: 692C141645 X-Migadu-Scanner: mx1.migadu.com X-TUID: GXttd8P6Olew Hi Ricardo, Ricardo Wurmus writes: > Hi Guix, > > I=E2=80=99d like to draw your attention to https://issues.guix.gnu.org/64= 945. > It=E2=80=99s a patch that adds binary descriptors to OpenCV. > > These descriptors are the result of a very expensive computation, which > could be performed with lots of memory and GPUs. The result is a small > number of very small descriptors in binary format, which OpenCV can use > as an input to a feature detection algorithm. > > This is probably one of the simplest cases of machine learning output; > the output is small and compared to other machine learning models > require only a small amount of computation. But it=E2=80=99s above the > threshold for our build farm and not something we can have users > recompute on install. > > The software used to generate these descriptors is freely licensed, and > the descriptors are living in the twilight zone of assets that are not > quite software but clearly not just decorative either. They are large > arguments to image feature detection algorithms, much like an image mask > would be. > > What shall we do with this patch? Can we accept it or does it cross a > line we don=E2=80=99t want to cross? We should ask what is the FSF's opinion about it, if they have one. I personally see trained data models as data more than code; so when their licensing allows them to be redistributed I see no objection to package them in Guix. One example is the 'tesseract-ocr-tessdata-fast' package, which contains the data of the trained models. Debian also packages the models of the different languages as 'tesseract-ocr-eng, 'tesseract-ocr-fra', etc. [0]; even Parabola offers with its 'tesseract-data-*' packages [1]. [0] https://packages.debian.org/search?suite=3Dstable§ion=3Dall&arch= =3Dany&searchon=3Dnames&keywords=3Dtesseract [1] https://www.parabola.nu/groups/x86_64/tesseract-data/ --=20 Thanks, Maxim