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Awesome Open Source

Caffe-model

Caffe models (include classification, detection and segmentation) and deploy prototxt for resnet, resnext, inception_v3, inception_v4, inception_resnet, wider_resnet, densenet, aligned-inception-resne(x)t, DPNs and other networks.

Clone the caffe-model repository

git clone https://github.com/soeaver/caffe-model --recursive

We recommend using these caffe models with py-RFCN-priv

Please install py-RFCN-priv for evaluating and finetuning.

Disclaimer

Most of the pre-train models are converted from other projects, the main contribution belongs to the original authors.

Project links:

mxnet-model-gallerytensorflow slimcraftGBDResNeXtDenseNetwide-residual-networkskeras deep-learning-modelsademxappDPNsSenet

CLS (Classification, more details are in cls)

Performance on imagenet validation.

Top-1/5 error of pre-train models in this repository (Pre-train models download urls).

Network 224/299
(single-crop)
224/299
(12-crop)
320/395
(single-crop)
320/395
(12-crop)
resnet101-v2 21.95/6.12 19.99/5.04 20.37/5.16 19.29/4.57
resnet152-v2 20.85/5.42 19.24/4.68 19.66/4.73 18.84/4.32
resnet269-v2 19.71/5.00 18.25/4.20 18.70/4.33 17.87/3.85
inception-v3 21.67/5.75 19.60/4.73 20.10/4.82 19.25/4.24
xception 20.90/5.49 19.68/4.90 19.58/4.77 18.91/4.39
inception-v4 20.03/5.09 18.60/4.30 18.68/4.32 18.12/3.92
inception-resnet-v2 19.86/4.83 18.46/4.08 18.75/4.02 18.15/3.71
resnext50-32x4d 22.37/6.31 20.53/5.35 21.10/5.53 20.37/5.03
resnext101-32x4d 21.30/5.79 19.47/4.89 19.91/4.97 19.19/4.59
resnext101-64x4d 20.60/5.41 18.88/4.59 19.26/4.63 18.48/4.31
wrn50-2
(resnet50-1x128d)
22.13/6.13 20.09/5.06 20.68/5.28 19.83/4.87
air101 21.32/5.76 19.36/4.84 19.92/4.75 19.05/4.43
dpn-92 20.81/5.47 18.99/4.59 19.23/4.64 18.68/4.24
dpn-107 19.70/5.06 ../.. 18.41/4.25 ../..

DET (Detection, more details are in det)

Object Detection Performance on PASCAL VOC.

Original faster rcnn train on VOC 2007+2012 trainval and test on VOC 2007 test.

Network [email protected] train speed train memory test speed test memory
resnet18 70.02 9.5 img/s 1,235MB 17.5 img/s 989MB
resnet101-v2 79.6 3.1 img/s 6,495MB 7.1 img/s 4,573MB
resnet152-v2 80.72 2.8 img/s 9,315MB 6.2 img/s 6,021MB
wrn50-2 78.59 2.1 img/s 4,895MB 4.9 img/s 3,499MB
resnext50-32x4d 77.99 3.6 img/s 5,315MB 7.4 img/s 4,305MB
resnext101-32x4d 79.98 2.7 img/s 7,836MB 6.3 img/s 5,705MB
resnext101-64x4d 80.71 2.0 img/s
(batch=96)
11,277MB 3.7 img/s 9,461MB
inception-v3 78.6 4.1 img/s 4,325MB 7.3 img/s 3,445MB
inception-v4 81.49 2.6 img/s 6,759MB 5.4 img/s 4,683MB
inception-resnet-v2 80.0 2.0 img/s
(batch=112)
11,497MB 3.2 img/s 8,409MB
densenet-201 77.53 3.9 img/s
(batch=72)
10,073MB 5.5 img/s 9,955MB
resnet38a 80.1 1.4 img/s 8,723MB 3.4 img/s 5,501MB

SEG (Segmentation, more details are in seg)

Object Segmentation Performance on PASCAL VOC.

PSPNet training on SBD (10,582 images) and testing on VOC 2012 validation (1,449 images).

Network mIoU(%) pixel acc(%) training
speed
training
memory
testing
speed
testing
memory
resnet101-v2 77.94 94.94 1.6 img/s 8,023MB 3.0 img/s 4,071MB
resnet101-v2-selu 77.10 94.80 1.6 img/s 8,017MB 3.0 img/s 4,065MB
resnext101-32x4d 77.79 94.92 1.3 img/s 8,891MB 2.6 img/s 5,241MB
air101 77.64 94.93 1.3 img/s 10,017MB 2.5 img/s 5,241MB
inception-v4 77.58 94.83 -- img/s --MB -- img/s --MB

License

caffe-model is released under the MIT License (refer to the LICENSE file for details).

Acknowlegement

I greatly thank Yangqing Jia and BVLC group for developing Caffe.

And I would like to thank all the authors of every network.


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