function scores = matcaffe_demo(im, use_gpu)
% scores = matcaffe_demo(im, use_gpu)
-%
+%
% Demo of the matlab wrapper using the ILSVRC network.
%
% input
% scores = matcaffe_demo(im, 1);
% [score, class] = max(scores);
-model_def_file = '../../examples/imagenet_deploy.prototxt';
+model_def_file = '../../models/imagenet.prototxt';
% NOTE: you'll have to get the pre-trained ILSVRC network
-model_file = '../../examples/alexnet_train_iter_470000';
+model_file = '../../models/caffe_reference_imagenet_model';
% init caffe network (spews logging info)
caffe('init', model_def_file, model_file);
# Optional arguments.
parser.add_argument(
"--model_def",
- default="examples/imagenet_deploy.prototxt",
+ default="../../../models/imagenet.prototxt",
help="Model definition file."
)
parser.add_argument(
"--pretrained_model",
- default="examples/caffe_reference_imagenet_model",
+ default="../../../models/caffe_reference_imagenet_model",
help="Trained model weights file."
)
parser.add_argument(