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diff --git a/tensorflow/examples/label_image/README.md b/tensorflow/examples/label_image/README.md index fbad61a22f..ef0825faaf 100644 --- a/tensorflow/examples/label_image/README.md +++ b/tensorflow/examples/label_image/README.md @@ -6,15 +6,26 @@ to recognize objects in images. ## Description This demo uses a Google Inception model to classify image files that are passed -in on the command line. See -[`googlenet_labels.txt`](data/googlenet_labels.txt) -for the possible classifications, which are the 1,000 categories used in the -Imagenet competition. +in on the command line. ## To build/install/run -As long as you've managed to build the main TensorFlow framework, you should -have everything you need to run this example installed already. +The TensorFlow `GraphDef` that contains the model definition and weights +is not packaged in the repo because of its size. Instead, you must +first download the file to the `data` directory in the source tree: + +```bash +$ wget https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip -O tensorflow/examples/label_image/data/inception5h.zip + +$ unzip tensorflow/examples/label_image/data/inception5h.zip -d tensorflow/examples/label_image/data/ +``` + +Then, as long as you've managed to build the main TensorFlow framework, you +should have everything you need to run this example installed already. + +Once extracted, see the labels file in the data directory for the possible +classifications, which are the 1,000 categories used in the Imagenet +competition. To build it, run this command: |