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The purpose of this project is to reimplement the following paper: using tensorflow
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nets add some models from tfslim Mar 22, 2017
LICENSE Initial commit Mar 22, 2017 add some models from tfslim Mar 22, 2017


The purpose of this project is to reimplement the following paper:

Pre-trained Models

Neural nets work best when they have many parameters, making them powerful function approximators. However, this means they must be trained on very large datasets. Because training models from scratch can be a very computationally intensive process requiring days or even weeks, we provide various pre-trained models, as listed below. These CNNs have been trained on the ILSVRC-2012-CLS image classification dataset.

In the table below, we list each model, the corresponding TensorFlow model file, the link to the model checkpoint, and the top 1 and top 5 accuracy (on the imagenet test set). Note that the VGG and ResNet parameters have been converted from their original caffe formats (here and here), whereas the Inception parameters have been trained internally at Google. Also be aware that these accuracies were computed by evaluating using a single image crop. Some academic papers report higher accuracy by using multiple crops at multiple scales.

Model TF-Slim File Checkpoint Top-1 Accuracy Top-5 Accuracy
Inception V1 Code inception_v1_2016_08_28.tar.gz 69.8 89.6
Inception V2 Code inception_v2_2016_08_28.tar.gz 73.9 91.8
Inception V3 Code inception_v3_2016_08_28.tar.gz 78.0 93.9
Inception V4 Code inception_v4_2016_09_09.tar.gz 80.2 95.2
Inception-ResNet-v2 Code inception_resnet_v2.tar.gz 80.4 95.3
ResNet 50 Code resnet_v1_50.tar.gz 75.2 92.2
ResNet 101 Code resnet_v1_101.tar.gz 76.4 92.9
ResNet 152 Code resnet_v1_152.tar.gz 76.8 93.2
VGG 16 Code vgg_16.tar.gz 71.5 89.8
VGG 19 Code vgg_19.tar.gz 71.1 89.8

Here is an example of how to download the Inception V3 checkpoint:

$ CHECKPOINT_DIR=/tmp/checkpoints
$ wget
$ tar -xvf inception_v3_2016_08_28.tar.gz
$ mv inception_v3.ckpt ${CHECKPOINT_DIR}
$ rm inception_v3_2016_08_28.tar.gz
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