@@ -47,8 +47,8 @@ Add the following code to your script to create a new Custom Vision service proj
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``` javascript
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const util = require (' util' );
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const fs = require (' fs' );
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- const TrainingApiClient = require (" @azure/cognitiveservices-customvision-training" );
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- const PredictionApiClient = require (" @azure/cognitiveservices-customvision-prediction" );
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+ const TrainingApi = require (" @azure/cognitiveservices-customvision-training" );
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+ const PredictionApi = require (" @azure/cognitiveservices-customvision-prediction" );
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const setTimeoutPromise = util .promisify (setTimeout);
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@@ -61,7 +61,7 @@ const endPoint = "https://<my-resource-name>.cognitiveservices.azure.com/"
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const publishIterationName = " classifyModel" ;
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- const trainer = new TrainingApiClient (trainingKey, endPoint);
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+ const trainer = new TrainingApi.TrainingAPIClient (trainingKey, endPoint);
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(async () => {
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console .log (" Creating project..." );
@@ -129,7 +129,7 @@ await trainer.publishIteration(sampleProject.id, trainingIteration.id, publishIt
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To send an image to the prediction endpoint and retrieve the prediction, add the following code to the end of the file:
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` ` ` javascript
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- const predictor = new PredictionApiClient (predictionKey, endPoint);
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+ const predictor = new PredictionApi.PredictionAPIClient (predictionKey, endPoint);
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const testFile = fs .readFileSync (` ${ sampleDataRoot} /Test/test_image.jpg` );
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const results = await predictor .classifyImage (sampleProject .id , publishIterationName, testFile);
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