Using Yolo9000 - Sudhakar17/darknet GitHub Wiki
Simultaneous detection and classification of 9000 objects: darknet.exe detector test cfg/combine9k.data cfg/yolo9000.cfg yolo9000.weights data/dog.jpg
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yolo9000.weights
- (186 MB Yolo9000 Model) requires 4 GB GPU-RAM: http://pjreddie.com/media/files/yolo9000.weights -
yolo9000.cfg
- cfg-file of the Yolo9000, also there are paths to the9k.tree
andcoco9k.map
https://github.com/AlexeyAB/darknet/blob/617cf313ccb1fe005db3f7d88dec04a04bd97cc2/cfg/yolo9000.cfg#L217-L218-
9k.tree
- WordTree of 9418 categories -<label> <parent_it>
, ifparent_id == -1
then this label hasn't parent: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/9k.tree -
coco9k.map
- map 80 categories from MSCOCO to WordTree9k.tree
: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/coco9k.map
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combine9k.data
- data file, there are paths to:9k.labels
,9k.names
,inet9k.map
, (change path to yourcombine9k.train.list
): https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/combine9k.data-
9k.labels
- 9418 labels of objects: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/9k.labels -
9k.names
- 9418 names of objects: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/9k.names -
inet9k.map
- map 200 categories from ImageNet to WordTree9k.tree
: https://raw.githubusercontent.com/AlexeyAB/darknet/master/build/darknet/x64/data/inet9k.map
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