bvlc_reference_caffenet.caffemodel
---
name: BAIR/BVLC CaffeNet Model
caffemodel: bvlc_reference_caffenet.caffemodel
caffemodel_url: http://dl.caffe.berkeleyvision.org/bvlc_reference_caffenet.caffemodel
license: unrestricted
sha1: 4c8d77deb20ea792f84eb5e6d0a11ca0a8660a46
This model is the result of following the Caffe [ImageNet model training instructions](http://caffe.berkeleyvision.org/gathered/examples/imagenet.html).
It is a replication of the model described in the [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) publication with some differences:
This model is snapshot of iteration 310,000.
The best validation performance during training was iteration 313,000 with validation accuracy 57.412% and loss 1.82328.
This model obtains a top-1 accuracy 57.4% and a top-5 accuracy 80.4% on the validation set, using just the center crop.
(Using the average of 10 crops, (4 + 1 center) * 2 mirror, should obtain a bit higher accuracy still.)
This model was trained by Jeff Donahue @jeffdonahue
This model is released for unrestricted use.
whale@sea:/media/whale/wsWin10/wsUbuntu16.04/DlFrames/caffe$ ./build/install/bin/classification \
/media/whale/wsWin10/wsUbuntu16.04/DlFrames/caffe/models/bvlc_reference_caffenet/deploy.prototxt \
/media/whale/wsWin10/wsUbuntu16.04/DlFrames/caffe/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel \
data/ilsvrc12/imagenet_mean.binaryproto \
/media/whale/wsWin10/wsCaffe/model-zoo/VGG16/synset_words.txt \
/media/whale/wsWin10/images/person/2.jpg
labels_.size() = 1000 output_layer->channels() = 1000 ---------- Prediction for /media/whale/wsWin10/images/person/2.jpg ----------
0.3411 - "n03676483 lipstick, lip rouge"
0.1024 - "n03325584 feather boa, boa"
0.0978 - "n07615774 ice lolly, lolly, lollipop, popsicle"
0.0734 - "n02786058 Band Aid"
0.0601 - "n04357314 sunscreen, sunblock, sun blocker"
翻译: 口红,口红
whale@sea:/media/whale/wsWin10/wsUbuntu16.04/DlFrames/caffe$ ./build/install/bin/classification \
/media/whale/wsWin10/wsUbuntu16.04/DlFrames/caffe/models/bvlc_reference_caffenet/deploy.prototxt \
/media/whale/wsWin10/wsUbuntu16.04/DlFrames/caffe/models/bvlc_reference_caffenet/bvlc_reference_caffenet.caffemodel \
data/ilsvrc12/imagenet_mean.binaryproto \
/media/whale/wsWin10/wsCaffe/model-zoo/VGG16/synset_words.txt \
/media/whale/wsWin10/images/person/3.jpg
labels_.size() = 1000 output_layer->channels() = 1000 ---------- Prediction for /media/whale/wsWin10/images/person/3.jpg ----------
0.4030 - "n02883205 bow tie, bow-tie, bowtie"
0.3799 - "n04350905 suit, suit of clothes"
0.0473 - "n02865351 bolo tie, bolo, bola tie, bola"
0.0131 - "n04591157 Windsor tie"
0.0114 - "n02786058 Band Aid"
领结,领带,领结
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