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| |
| # Image Classification using Inception V4 |
| |
| In this example, we convert Inception V4 trained on Tensorflow to SINGA for image classification. Tested on SINGA version 1.1.1 with [parameters pretrained by tensorflow](https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz). |
| |
| ## Instructions |
| |
| * Download the parameter checkpoint file |
| |
| $ wget https://s3-ap-southeast-1.amazonaws.com/dlfile/inception_v4.tar.gz |
| $ tar xvf inception_v4.tar.gz |
| |
| * Download [synset_word.txt](https://github.com/BVLC/caffe/blob/master/data/ilsvrc12/get_ilsvrc_aux.sh) file. |
| |
| * Run the program |
| |
| # use cpu |
| $ python serve.py -C & |
| # use gpu |
| $ python serve.py & |
| |
| * Submit images for classification |
| |
| $ curl -i -F image=@image1.jpg http://localhost:9999/api |
| $ curl -i -F image=@image2.jpg http://localhost:9999/api |
| $ curl -i -F image=@image3.jpg http://localhost:9999/api |
| |
| image1.jpg, image2.jpg and image3.jpg should be downloaded before executing the above commands. |
| |
| ## Details |
| |
| We first extract the parameter values from [Tensorflow's checkpoint file](http://download.tensorflow.org/models/inception_v4_2016_09_09.tar.gz) into a pickle version. |
| After downloading and decompressing the checkpoint file, run the following script |
| |
| $ python convert.py --file_name=inception_v4.ckpt |
