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Publier une image simplement
13 avril 2011, par ,
Mis à jour : Février 2012
Langue : français
Type : Video
Autres articles (58)
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Submit bugs and patches
13 avril 2011Unfortunately a software is never perfect.
If you think you have found a bug, report it using our ticket system. Please to help us to fix it by providing the following information : the browser you are using, including the exact version as precise an explanation as possible of the problem if possible, the steps taken resulting in the problem a link to the site / page in question
If you think you have solved the bug, fill in a ticket and attach to it a corrective patch.
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Personnaliser en ajoutant son logo, sa bannière ou son image de fond
5 septembre 2013, parCertains thèmes prennent en compte trois éléments de personnalisation : l’ajout d’un logo ; l’ajout d’une bannière l’ajout d’une image de fond ;
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Ecrire une actualité
21 juin 2013, parPrésentez les changements dans votre MédiaSPIP ou les actualités de vos projets sur votre MédiaSPIP grâce à la rubrique actualités.
Dans le thème par défaut spipeo de MédiaSPIP, les actualités sont affichées en bas de la page principale sous les éditoriaux.
Vous pouvez personnaliser le formulaire de création d’une actualité.
Formulaire de création d’une actualité Dans le cas d’un document de type actualité, les champs proposés par défaut sont : Date de publication ( personnaliser la date de publication ) (...)
Sur d’autres sites (13326)
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checkasm : Implement helpers for defining and checking padded rects
21 mars, par Martin Storsjöcheckasm : Implement helpers for defining and checking padded rects
This backports similar functionality from dav1d, from commits
35d1d011fda4a92bcaf42d30ed137583b27d7f6d and
d130da9c315d5a1d3968d278bbee2238ad9051e7.This allows detecting writes out of bounds, on all 4 sides of
the intended destination rectangle.The bounds checking also can optionally allow small overwrites
(up to a specified alignment), while still checking for larger
overwrites past the intended allowed region.Signed-off-by : Martin Storsjö <martin@martin.st>
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lavd/v4l2 : detect device name truncation
25 novembre 2021, par Anton Khirnovlavd/v4l2 : detect device name truncation
Silences the following warning with gcc 10 :
src/libavdevice/v4l2.c : In function ‘v4l2_get_device_list’ :
src/libavdevice/v4l2.c:1042:64 : warning : ‘%s’ directive output may be truncated writing up to 255 bytes into a region of size 251 [-Wformat-truncation=]
1042 | ret = snprintf(device_name, sizeof(device_name), "/dev/%s", entry->d_name) ;
| ^
src/libavdevice/v4l2.c:1042:15 : note : ‘snprintf’ output between 6 and 261 bytes into a destination of size 256
1042 | ret = snprintf(device_name, sizeof(device_name), "/dev/%s", entry->d_name) ;
| ^Previous patches intending to silence it have proposed increasing the
buffer size, but doing that correctly seems to be tricky. Failing on
truncation is simpler and just as effective (as excessively long device
names are unlikely). -
lavfi/dnn_classify : add filter dnn_classify for classification based on detection...
17 mars 2021, par Guo, Yejunlavfi/dnn_classify : add filter dnn_classify for classification based on detection bounding boxes
classification is done on every detection bounding box in frame's side data,
which are the results of object detection (filter dnn_detect).Please refer to commit log of dnn_detect for the material for detection,
and see below for classification.download material for classifcation :
wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/emotions-recognition-retail-0003.bin
wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/emotions-recognition-retail-0003.xml
wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/emotions-recognition-retail-0003.labelrun command as :
./ffmpeg -i cici.jpg -vf dnn_detect=dnn_backend=openvino:model=face-detection-adas-0001.xml:input=data:output=detection_out:confidence=0.6:labels=face-detection-adas-0001.label,dnn_classify=dnn_backend=openvino:model=emotions-recognition-retail-0003.xml:input=data:output=prob_emotion:confidence=0.3:labels=emotions-recognition-retail-0003.label:target=face,showinfo -f null -We'll see the detect&classify result as below :
[Parsed_showinfo_2 @ 0x55b7d25e77c0] side data - detection bounding boxes :
[Parsed_showinfo_2 @ 0x55b7d25e77c0] source : face-detection-adas-0001.xml, emotions-recognition-retail-0003.xml
[Parsed_showinfo_2 @ 0x55b7d25e77c0] index : 0, region : (1005, 813) -> (1086, 905), label : face, confidence : 10000/10000.
[Parsed_showinfo_2 @ 0x55b7d25e77c0] classify : label : happy, confidence : 6757/10000.
[Parsed_showinfo_2 @ 0x55b7d25e77c0] index : 1, region : (888, 839) -> (967, 926), label : face, confidence : 6917/10000.
[Parsed_showinfo_2 @ 0x55b7d25e77c0] classify : label : anger, confidence : 4320/10000.Signed-off-by : Guo, Yejun <yejun.guo@intel.com>