... | ... | @@ -19,20 +19,20 @@ As usual before you can start training your network, you need to get the data an |
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Now you should find four new files in this folder. Those contain the data and the labels for the training and testing dataset.
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In order to be able to use them with *Caffe*, we have to convert the data into one of the supported database formats, this tutorial will use lmdb files. There is also a script to get the conversion done for you. Make sure you are in the CAFFE_ROOT folder again. We assume that you are still in the mnist folder, hence we have to traverse up two nodes in the directory tree.
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In order to be able to use them with *Caffe*, we have to convert the data into one of the supported database formats. For this tutorial, we will use lmdb files. There is also a script distributed with Caffe to get the conversion done for you. Make sure you are in the CAFFE_ROOT folder again. We assume that you are still in the mnist folder, hence we have to traverse up two nodes in the directory tree.
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cd ../..
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./examples/mnist/create_mnist.sh
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It is necessary to start this script from CAFFE_ROOT, as the locations of the source and target files are given relativ to this path in the script.
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It is necessary to start this script from CAFFE_ROOT, as the locations of the source and target files are given relative to this path in the script.
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Now feel free to have a look into the `CAFFE_ROOT/examples/mnist` folder, among many `prototxt` and a few other files there should now be two folders: `mnist_test_lmdb` and `mnist_train_lmdb`. Both again contain two files respectively: `data.mdb` and `lock.mdb`.
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Now feel free to have a look into the `CAFFE_ROOT/examples/mnist` folder. Among multiple `.prototxt` and a few other files there should now exist two folders: `mnist_test_lmdb` and `mnist_train_lmdb`. Both again contain two files respectively: `data.mdb` and `lock.mdb`.
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If this is the case for you, we are finished setting up our databases.
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**Note:** There is also a file [`readme.md`](https://github.com/BVLC/caffe/blob/master/examples/mnist/readme.md). In there you can find some more information what the layers are for and what all the parameters are doing. Don't be bothered with writing all the protobuf definitions though, this is exactly what Barista was made for.
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**Note:** There is also a file [`readme.md`](https://github.com/BVLC/caffe/blob/master/examples/mnist/readme.md). In there you can find some more information about what the layers are for and what all of the parameters are doing. Don't be bothered with writing all the protobuf definitions though, this is exactly what Barista was made for.
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If you want, you can give *Caffe* a trial run. From the CAFFE_ROOT folder start a first training session:
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If you want to, you can give *Caffe* a trial run. From the CAFFE_ROOT folder start a first training session:
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./examples/mnist/train_lenet.sh
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... | ... | |