content/en/_sources/docs/model_zoo/examples/caffe/README.md.txt

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# Use parameters pre-trained from Caffe in SINGA

In this example, we use SINGA to load the VGG parameters trained by Caffe to do image classification.

## Run this example
You can run this example by simply executing `run.sh vgg16` or `run.sh vgg19`
The script does the following work.

### Obtain the Caffe model
* Download caffe model prototxt and parameter binary file.
* Currently we only support the latest caffe format, if your model is in
    previous version of caffe, please update it to current format.(This is
    supported by caffe)
* After updating, we can obtain two files, i.e., the prototxt and parameter
    binary file.

### Prepare test images
A few sample images are downloaded into the `test` folder.

### Predict
The `predict.py` script creates the VGG model and read the parameters,

    usage: predict.py [-h] model_txt model_bin imgclass

where `imgclass` refers to the synsets of imagenet dataset for vgg models.
You can start the prediction program by executing the following command:

    python predict.py vgg16.prototxt vgg16.caffemodel synset_words.txt

Then you type in the image path, and the program would output the top-5 labels.

More Caffe models would be tested soon.