Comments (1)
Hi!
- You can replace the image data layer by lMDB. The difference is, that a LMDB dataset transforms all images to be square shape and hence changes the aspect ratio. The image data layer preserves the aspect ratio, hence the results might vary a bit.
- You can use the linux tool convert to resize all images in a folder. Do something like find . -name "*.JPEG" and pipe it to convert. These scaled images are only useful for the image data layer though.
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Related Issues (20)
- BN0 mean and variance HOT 1
- Why there is no scale layer after each batch norm layer? HOT 2
- Worse performance than the reported one in Res50 HOT 2
- Would you mind share resnet34.caffemodel? HOT 5
- Would you mind share labels file? HOT 3
- Would you mind sharing VGG16 model? HOT 2
- Difference between ResNet and VGG train.prototxt? HOT 2
- ResNet50: bottom blob of expand layer HOT 6
- VGG19 bn model ,great accuracy gap between training phase and test phase HOT 2
- VGG19BN: weird values of 'data/bn' parameters. HOT 2
- running VGG19_BN pretrained model need so much GPU memory HOT 3
- Where is the vgg16 pretrained modelS with BN? HOT 3
- can not reproduce validation accuracy with pretrained model
- Question about the license
- train on multi gpus HOT 2
- Unable to download model file from uni-jeana.de
- Check failed: target_blobs.size() == source_layer.blobs_size() (5 vs. 3) Incompatible number of blobs for layer data_bn
- No scale layers after batchnorm HOT 2
- Clarification on "validation set of ILSVRC 2012 - 2016 classiifcation task" HOT 1
- Regarding Image pre-processing. HOT 6
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