Publishing 2019 R1.1 content and Myriad plugin sources (#162)

[platform/upstream/dldt.git] / inference-engine / samples / hello_request_classification / README.md

diff --git a/inference-engine/samples/hello_request_classification/README.md b/inference-engine/samples/hello_request_classification/README.md
index fd8d35b..261b883 100644 (file)
--- a/inference-engine/samples/hello_request_classification/README.md
+++ b/inference-engine/samples/hello_request_classification/README.md
@@ -5,7 +5,7 @@ The sample is simplified version of [Image Classification Sample](./inference-en
 It demonstrates how to use the new Infer Request API of Inference Engine in applications. Refer to
 [Integrate the Inference Engine New Request API with Your Application](./docs/IE_DG/Integrate_with_customer_application_new_API.md) for details.
 
-> **NOTE**: By default, Inference Engine samples and demos expect input with BGR channels order. If you trained your model to work with RGB order, you need to manually rearrange the default channels order in the sample or demo application or reconvert your model using the Model Optimizer tool with `--reverse_input_channels` argument specified. For more information about the argument, refer to **When to Specify Input Shapes** section of [Converting a Model Using General Conversion Parameters](./docs/MO_DG/prepare_model/convert_model/Converting_Model_General.md).
+> **NOTE**: By default, Inference Engine samples and demos expect input with BGR channels order. If you trained your model to work with RGB order, you need to manually rearrange the default channels order in the sample or demo application or reconvert your model using the Model Optimizer tool with `--reverse_input_channels` argument specified. For more information about the argument, refer to **When to Reverse Input Channels** section of [Converting a Model Using General Conversion Parameters](./docs/MO_DG/prepare_model/convert_model/Converting_Model_General.md).
 
 ## Running