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updated docs
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dusty-nv committed Jul 15, 2020
1 parent ee77977 commit 6bb1908
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10 changes: 5 additions & 5 deletions docs/pytorch-cat-dog.md
Original file line number Diff line number Diff line change
Expand Up @@ -151,13 +151,13 @@ imagenet.py --model=cat_dog/resnet18.onnx --input_blob=input_0 --output_blob=out
There are 200 test images included with the dataset between the cat and dog classes, or you can download your own pictures to try. You can process them all like this:

``` bash
$ mkdir $DATASET/test_output_cat $DATASET/test_output_dog
mkdir $DATASET/test_output_cat $DATASET/test_output_dog

$ imagenet --model=$NET/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=$DATASET/../labels.txt \
$DATASET/test/cat $DATASET/test_output_cat
imagenet --model=$NET/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=$DATASET/../labels.txt \
$DATASET/test/cat $DATASET/test_output_cat

$ imagenet --model=$NET/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=$DATASET/../labels.txt \
$DATASET/test/dog $DATASET/test_output_dog
imagenet --model=$NET/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=$DATASET/../labels.txt \
$DATASET/test/dog $DATASET/test_output_dog
```

In this instance, all the images will be read from the dataset's `test/` directory, and saved to the `test_output/` directory.
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7 changes: 4 additions & 3 deletions docs/pytorch-plants.md
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Expand Up @@ -151,9 +151,10 @@ There are a bunch of test images included with the dataset, or you can download
If you want to classify all of the test images at once, you can run the program on the entire directory:

``` bash
$ mkdir $DATASET/test_output
$ imagenet --model=$NET/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=$DATASET/../labels.txt \
$DATASET/test $DATASET/test_output
mkdir $DATASET/test_output

imagenet --model=$NET/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=$DATASET/../labels.txt \
$DATASET/test $DATASET/test_output
```

In this instance, all the images will be read from the dataset's `test/` directory, and saved to the `test_output/` directory.
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