We manually converted the original torch models into caffe format from https://github.com/liuzhuang13/DenseNet.
For details of these networks, please read the original paper:
Pretrained DenseNet Models on ImageNet
The top-1/5 accuracy rates by using single center crop (crop size: 224x224, image size: 256xN)
|DenseNet 121 (k=32)||74.91||92.19||caffemodel (30.8 MB)||netscope, netron|
|DenseNet 169 (k=32)||76.09||93.14||caffemodel (54.6 MB)||netscope, netron|
|DenseNet 201 (k=32)||77.31||93.64||caffemodel (77.3 MB)||netscope, netron|
|DenseNet 161 (k=48)||77.64||93.79||caffemodel (110 MB)||netscope, netron|
Update (July 27, 2017): for your convenience, we also provide a link to these models on Baidu Disk.
Due to compatibility reasons, several modifications have been made:
- BGR mean values [103.94,116.78,123.68] are subtracted
- scale: 0.017 is used, instead of the original std values for image preprocessing
- ceil_mode: false is used in the first pooling layers ('pool1')