The Product Search feature is in maintenance mode. For better scalability and the same functionality as Product Search, use the Vision Warehouse .

Creating your reference images & indexing

Reference images are images containing various views of your products. The following recommendations apply:

Make sure the size of the file doesn't exceed the maximum size (20MB).
Consider viewpoints that logically highlight the product and contain relevant visual information.
Create reference images that supplement any missing viewpoints. For example, if you only have images of the right shoe in a pair, provide mirrored versions of those files as the left shoe.
Upload the highest resolution image available.
Show the product against a white background.
Convert PNGs with transparent backgrounds to a solid background.

Images must be stored in a Cloud Storage bucket. If you're authenticating your image create call with an API key, the bucket must be public. If you're authenticating with a service account, that service account must have read access on the bucket.

Creating a single reference image

You can add a reference image to an existing product. This then allows you to search for the product by the image.

REST

Before using any of the request data, make the following replacements:

PROJECT_ID : Your Google Cloud project ID.
LOCATION_ID : A valid location identifier. Valid location identifiers are: us-west1 , us-east1 , europe-west1 , and asia-east1 .
PRODUCT_ID : The ID for the product that is associated with a reference image. This ID is either randomly set or specified by the user at product creation time.
CLOUD_STORAGE_IMAGE_URI : the path to a valid image file in a Cloud Storage bucket. You must at least have read privileges to the file. Example:
- ```
gs://storage-bucket/filename.jpg
```

Note : The boundingPolys field is optional. If you don't specify a bounding box, Cloud Vision API will try to infer regions of interest in the image that are compatible with the productCategory on the parent product.

HTTP method and URL:

POST https://vision.googleapis.com/v1/projects/ project-id 
/locations/ location-id 
/products/ product-id 
/referenceImages

Request JSON body:

{
  "uri": " cloud-storage-image-uri 
",
  "boundingPolys": [
    {
      "vertices": [
        {
          "x": X_MIN 
,
          "y": Y_MIN 
},
        {
          "x": X_MAX 
,
          "y": Y_MIN 
},
        {
          "x": X_MAX 
,
          "y": Y_MAX 
},
        {
          "x": X_MIN 
,
          "y": Y_MAX 
}
      ]
    }
  ]
}

To send your request, choose one of these options:

curl

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell , which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list .

Save the request body in a file named request.json , and execute the following command:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: project-id 
" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/projects/ project-id 
/locations/ location-id 
/products/ product-id 
/referenceImages"

PowerShell

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list .

Save the request body in a file named request.json , and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = " project-id 
" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://vision.googleapis.com/v1/projects/ project-id 
/locations/ location-id 
/products/ product-id 
/referenceImages" | Select-Object -Expand Content

If the request is successful, the server returns a 200 OK HTTP status code and the response in JSON format.

You should see output similar to the following. The example request specified a single boundingPoly in the image. The vertices for the bounding box are not normalized; the vertex values are the actual pixel values, and not relative to the original image and scaled from 0 to 1. These vertices have the following values: [(33,22),(282,22),(282,278),(33,278)].

{
  "name": "projects/ project-id 
/locations/ location-id 
/products/ product-id 
/referenceImages/ image-id 
",
  "uri": "gs:// storage-bucket 
/ filename 
.jpg",
  "boundingPolys": [
    {
      "vertices": [
        {
          "x": 33,
          "y": 22
        },
        {
          "x": 282,
          "y": 22
        },
        {
          "x": 282,
          "y": 278
        },
        {
          "x": 33,
          "y": 278
        }
      ]
    }
  ]
}

Go

To learn how to install and use the client library for Vision API Product Search, see Vision API Product Search client libraries . For more information, see the Vision API Product Search Go API reference documentation .

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  import 
  
 ( 
  
 "context" 
  
 "fmt" 
  
 "io" 
  
 vision 
  
 "cloud.google.com/go/vision/apiv1" 
  
 "cloud.google.com/go/vision/v2/apiv1/visionpb" 
 ) 
 // createReferenceImage creates a reference image for a product. 
 func 
  
 createReferenceImage 
 ( 
 w 
  
 io 
 . 
 Writer 
 , 
  
 projectID 
  
 string 
 , 
  
 location 
  
 string 
 , 
  
 productID 
  
 string 
 , 
  
 referenceImageID 
  
 string 
 , 
  
 gcsURI 
  
 string 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 c 
 , 
  
 err 
  
 := 
  
 vision 
 . 
 NewProductSearchClient 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewProductSearchClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 c 
 . 
 Close 
 () 
  
 req 
  
 := 
  
& visionpb 
 . 
  CreateReferenceImageRequest 
 
 { 
  
 Parent 
 : 
  
 fmt 
 . 
 Sprintf 
 ( 
 "projects/%s/locations/%s/products/%s" 
 , 
  
 projectID 
 , 
  
 location 
 , 
  
 productID 
 ), 
  
 ReferenceImage 
 : 
  
& visionpb 
 . 
  ReferenceImage 
 
 { 
  
 Uri 
 : 
  
 gcsURI 
 , 
  
 }, 
  
 ReferenceImageId 
 : 
  
 referenceImageID 
 , 
  
 } 
  
 resp 
 , 
  
 err 
  
 := 
  
 c 
 . 
 CreateReferenceImage 
 ( 
 ctx 
 , 
  
 req 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "CreateReferenceImage: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Reference image name: %s\n" 
 , 
  
 resp 
 . 
 Name 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Reference image uri: %s\n" 
 , 
  
 resp 
 . 
 Uri 
 ) 
  
 return 
  
 nil 
 }

Java

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  /** 
 * Create a reference image. 
 * 
 * @param projectId - Id of the project. 
 * @param computeRegion - Region name. 
 * @param productId - Id of the product. 
 * @param referenceImageId - Id of the image. 
 * @param gcsUri - Google Cloud Storage path of the input image. 
 * @throws IOException - on I/O errors. 
 */ 
 public 
  
 static 
  
 void 
  
 createReferenceImage 
 ( 
  
 String 
  
 projectId 
 , 
  
 String 
  
 computeRegion 
 , 
  
 String 
  
 productId 
 , 
  
 String 
  
 referenceImageId 
 , 
  
 String 
  
 gcsUri 
 ) 
  
 throws 
  
 IOException 
  
 { 
  
 try 
  
 ( 
 ProductSearchClient 
  
 client 
  
 = 
  
 ProductSearchClient 
 . 
 create 
 ()) 
  
 { 
  
 // Get the full path of the product. 
  
 String 
  
 formattedParent 
  
 = 
  
 ProductName 
 . 
 format 
 ( 
 projectId 
 , 
  
 computeRegion 
 , 
  
 productId 
 ); 
  
 // Create a reference image. 
  
 ReferenceImage 
  
 referenceImage 
  
 = 
  
 ReferenceImage 
 . 
 newBuilder 
 (). 
 setUri 
 ( 
 gcsUri 
 ). 
 build 
 (); 
  
 ReferenceImage 
  
 image 
  
 = 
  
 client 
 . 
 createReferenceImage 
 ( 
 formattedParent 
 , 
  
 referenceImage 
 , 
  
 referenceImageId 
 ); 
  
 // Display the reference image information. 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Reference image name: %s" 
 , 
  
 image 
 . 
 getName 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Reference image uri: %s" 
 , 
  
 image 
 . 
 getUri 
 ())); 
  
 } 
 }

Node.js

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  const 
  
 vision 
  
 = 
  
 require 
 ( 
 ' @google-cloud/vision 
' 
 ); 
 const 
  
 client 
  
 = 
  
 new 
  
 vision 
 . 
  ProductSearchClient 
 
 (); 
 async 
  
 function 
  
 createReferenceImage 
 () 
  
 { 
  
 /** 
 * TODO(developer): Uncomment the following line before running the sample. 
 */ 
  
 // const projectId = 'Your Google Cloud project Id'; 
  
 // const location = 'A compute region name'; 
  
 // const productId = 'Id of the product'; 
  
 // const referenceImageId = 'Id of the reference image'; 
  
 // const gcsUri = 'Google Cloud Storage path of the input image'; 
  
 const 
  
 formattedParent 
  
 = 
  
 client 
 . 
 productPath 
 ( 
 projectId 
 , 
  
 location 
 , 
  
 productId 
 ); 
  
 const 
  
 referenceImage 
  
 = 
  
 { 
  
 uri 
 : 
  
 gcsUri 
 , 
  
 }; 
  
 const 
  
 request 
  
 = 
  
 { 
  
 parent 
 : 
  
 formattedParent 
 , 
  
 referenceImage 
 : 
  
 referenceImage 
 , 
  
 referenceImageId 
 : 
  
 referenceImageId 
 , 
  
 }; 
  
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 createReferenceImage 
 ( 
 request 
 ); 
  
 console 
 . 
 log 
 ( 
 `response.name: 
 ${ 
 response 
 . 
 name 
 } 
 ` 
 ); 
  
 console 
 . 
 log 
 ( 
 `response.uri: 
 ${ 
 response 
 . 
 uri 
 } 
 ` 
 ); 
 } 
 createReferenceImage 
 ();

Python

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  from 
  
 google.cloud 
  
 import 
 vision 
 def 
  
 create_reference_image 
 ( 
 project_id 
 , 
 location 
 , 
 product_id 
 , 
 reference_image_id 
 , 
 gcs_uri 
 ): 
  
 """Create a reference image. 
 Args: 
 project_id: Id of the project. 
 location: A compute region name. 
 product_id: Id of the product. 
 reference_image_id: Id of the reference image. 
 gcs_uri: Google Cloud Storage path of the input image. 
 """ 
 client 
 = 
 vision 
 . 
  ProductSearchClient 
 
 () 
 # Get the full path of the product. 
 product_path 
 = 
 client 
 . 
  product_path 
 
 ( 
 project 
 = 
 project_id 
 , 
 location 
 = 
 location 
 , 
 product 
 = 
 product_id 
 ) 
 # Create a reference image. 
 reference_image 
 = 
 vision 
 . 
  ReferenceImage 
 
 ( 
 uri 
 = 
 gcs_uri 
 ) 
 # The response is the reference image with `name` populated. 
 image 
 = 
 client 
 . 
  create_reference_image 
 
 ( 
 parent 
 = 
 product_path 
 , 
 reference_image 
 = 
 reference_image 
 , 
 reference_image_id 
 = 
 reference_image_id 
 , 
 ) 
 # Display the reference image information. 
 print 
 ( 
 f 
 "Reference image name: 
 { 
 image 
 . 
 name 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Reference image uri: 
 { 
 image 
 . 
 uri 
 } 
 " 
 )

Additional languages

C#: Please follow the C# setup instructions on the client libraries page and then visit the Vision API Product Search reference documentation for .NET.

PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Vision API Product Search reference documentation for PHP.

Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Vision API Product Search reference documentation for Ruby.

Creating multiple reference images with bulk import

You can also create reference images at the same time you create a product set and multiple products.

Create reference images in bulk by passing the Cloud Storage location of a CSV file to the import method. Thus, the CSV file and the images it points to must both be in a Cloud Storage bucket.

If you're authenticating your bulk import call with an API key, this CSV source file must be public.

If you're authenticating with a service account, that service account must have read access on the CSV source file.

CSV format

 image-uri,[image-id],product-set-id,product-id,product-category,[product-display-name],[label(s)],[bounding-poly]

See the CSV format how-to topic for more detailed information about formatting your CSV.

Bulk creation request

REST

Before using any of the request data, make the following replacements:

PROJECT_ID : Your Google Cloud project ID.
LOCATION_ID : A valid location identifier. Valid location identifiers are: us-west1 , us-east1 , europe-west1 , and asia-east1 .
STORAGE_PATH : A Cloud Storage bucket/directory where your input CSV file is stored. The requesting user must have at least read permission to the bucket.

HTTP method and URL:

POST https://vision.googleapis.com/v1/projects/ project-id 
/locations/ location-id 
/productSets:import

Request JSON body:

{
  "inputConfig": {
    "gcsSource": {
      "csvFileUri": " storage-path 
"
    }
  }
}

To send your request, choose one of these options:

curl

Save the request body in a file named request.json , and execute the following command:

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "x-goog-user-project: project-id 
" \
-H "Content-Type: application/json; charset=utf-8" \
-d @request.json \
"https://vision.googleapis.com/v1/projects/ project-id 
/locations/ location-id 
/productSets:import"

PowerShell

Save the request body in a file named request.json , and execute the following command:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = " project-id 
" }

Invoke-WebRequest `
-Method POST `
-Headers $headers `
-ContentType: "application/json; charset=utf-8" `
-InFile request.json `
-Uri "https://vision.googleapis.com/v1/projects/ project-id 
/locations/ location-id 
/productSets:import" | Select-Object -Expand Content

You should see output similar to the following. You can use the operation ID ( f10f34e32c40a710 , in this case) to get the status of the task. For an example, see Getting an operation's status :

{
  "name": "projects/ project-id 
/locations/ location-id 
/operations/ f10f34e32c40a710 
"
}

After the long-running operation completes you can get the details of the import operation. The response should look similar to the following:

{
  "name": "locations/ location-id 
/operations/f10f34e32c40a710",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.vision.v1.BatchOperationMetadata",
    "state": "SUCCESSFUL",
    "submitTime": "2019-12-06T21:16:04.476466873Z",
    "endTime": "2019-12-06T21:16:40.594258084Z"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.cloud.vision.v1.ImportProductSetsResponse",
    "referenceImages": [
      {
        "name": "projects/ project-id 
/locations/ location-id 
/products/product_id0/referenceImages/image0",
        "uri": "gs:// my-storage-bucket 
/img_039.jpg"
      },
      {
        "name": "projects/ project-id 
/locations/ location-id 
/products/product_id1/referenceImages/image1",
        "uri": "gs:// my-storage-bucket 
/img_105.jpg"
      },
      {
        "name": "projects/ project-id 
/locations/ location-id 
/products/product_id2/referenceImages/image2",
        "uri": "gs:// my-storage-bucket 
/img_224.jpg"
      },
      {
        "name": "projects/ project-id 
/locations/ location-id 
/products/product_id3/referenceImages/image3",
        "uri": "gs:// my-storage-bucket 
/img_385.jpg"
      }
    ],
    "statuses": [
      {},
      {},
      {},
      {}
    ]
  }
}

Go

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  import 
  
 ( 
  
 "context" 
  
 "fmt" 
  
 "io" 
  
 vision 
  
 "cloud.google.com/go/vision/apiv1" 
  
 "cloud.google.com/go/vision/v2/apiv1/visionpb" 
 ) 
 // importProductSets creates a product set using information in a csv file on GCS. 
 func 
  
 importProductSets 
 ( 
 w 
  
 io 
 . 
 Writer 
 , 
  
 projectID 
  
 string 
 , 
  
 location 
  
 string 
 , 
  
 gcsURI 
  
 string 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 c 
 , 
  
 err 
  
 := 
  
 vision 
 . 
 NewProductSearchClient 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewProductSearchClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 c 
 . 
 Close 
 () 
  
 req 
  
 := 
  
& visionpb 
 . 
  ImportProductSetsRequest 
 
 { 
  
 Parent 
 : 
  
 fmt 
 . 
 Sprintf 
 ( 
 "projects/%s/locations/%s" 
 , 
  
 projectID 
 , 
  
 location 
 ), 
  
 InputConfig 
 : 
  
& visionpb 
 . 
  ImportProductSetsInputConfig 
 
 { 
  
 Source 
 : 
  
& visionpb 
 . 
  ImportProductSetsInputConfig_GcsSource 
 
 { 
  
 GcsSource 
 : 
  
& visionpb 
 . 
  ImportProductSetsGcsSource 
 
 { 
  
 CsvFileUri 
 : 
  
 gcsURI 
 , 
  
 }, 
  
 }, 
  
 }, 
  
 } 
  
 op 
 , 
  
 err 
  
 := 
  
 c 
 . 
 ImportProductSets 
 ( 
 ctx 
 , 
  
 req 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "ImportProductSets: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Processing operation name: %s\n" 
 , 
  
 op 
 . 
 Name 
 ()) 
  
 resp 
 , 
  
 err 
  
 := 
  
 op 
 . 
 Wait 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "Wait: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "processing done.\n" 
 ) 
  
 for 
  
 i 
 , 
  
 status 
  
 := 
  
 range 
  
 resp 
 . 
 Statuses 
  
 { 
  
 // `0` is the coee for OK in google.rpc.code 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Status of processing line %d of the csv: %d\n" 
 , 
  
 i 
 , 
  
 status 
 . 
 Code 
 ) 
  
 if 
  
 status 
 . 
 Code 
  
 == 
  
 0 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Reference image name: %s\n" 
 , 
  
 resp 
 . 
 ReferenceImages 
 [ 
 i 
 ]. 
 Name 
 ) 
  
 } 
  
 else 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Status code not OK: %s\n" 
 , 
  
 status 
 . 
 Message 
 ) 
  
 } 
  
 } 
  
 return 
  
 nil 
 }

Java

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  /** 
 * Import images of different products in the product set. 
 * 
 * @param projectId - Id of the project. 
 * @param computeRegion - Region name. 
 * @param gcsUri - Google Cloud Storage URI.Target files must be in Product Search CSV format. 
 * @throws Exception - on client errors. 
 */ 
 public 
  
 static 
  
 void 
  
 importProductSets 
 ( 
 String 
  
 projectId 
 , 
  
 String 
  
 computeRegion 
 , 
  
 String 
  
 gcsUri 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 try 
  
 ( 
 ProductSearchClient 
  
 client 
  
 = 
  
 ProductSearchClient 
 . 
 create 
 ()) 
  
 { 
  
 // A resource that represents Google Cloud Platform location. 
  
 String 
  
 formattedParent 
  
 = 
  
 LocationName 
 . 
 format 
 ( 
 projectId 
 , 
  
 computeRegion 
 ); 
  
 Builder 
  
 gcsSource 
  
 = 
  
 ImportProductSetsGcsSource 
 . 
 newBuilder 
 (). 
 setCsvFileUri 
 ( 
 gcsUri 
 ); 
  
 // Set the input configuration along with Google Cloud Storage URI 
  
 ImportProductSetsInputConfig 
  
 inputConfig 
  
 = 
  
 ImportProductSetsInputConfig 
 . 
 newBuilder 
 (). 
 setGcsSource 
 ( 
 gcsSource 
 ). 
 build 
 (); 
  
 // Import the product sets from the input URI. 
  
 OperationFuture<ImportProductSetsResponse 
 , 
  
 BatchOperationMetadata 
>  
 response 
  
 = 
  
 client 
 . 
 importProductSetsAsync 
 ( 
 formattedParent 
 , 
  
 inputConfig 
 ); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Processing operation name: %s" 
 , 
  
 response 
 . 
 getName 
 ())); 
  
 ImportProductSetsResponse 
  
 results 
  
 = 
  
 response 
 . 
 get 
 (); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Processing done." 
 ); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Results of the processing:" 
 ); 
  
 for 
  
 ( 
 int 
  
 i 
  
 = 
  
 0 
 ; 
  
 i 
 < 
 results 
 . 
 getStatusesCount 
 (); 
  
 i 
 ++ 
 ) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
  
 String 
 . 
 format 
 ( 
  
 "Status of processing line %s of the csv: %s" 
 , 
  
 i 
 , 
  
 results 
 . 
 getStatuses 
 ( 
 i 
 ))); 
  
 // Check the status of reference image. 
  
 if 
  
 ( 
 results 
 . 
 getStatuses 
 ( 
 i 
 ). 
 getCode 
 () 
  
 == 
  
 0 
 ) 
  
 { 
  
 ReferenceImage 
  
 referenceImage 
  
 = 
  
 results 
 . 
 getReferenceImages 
 ( 
 i 
 ); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 referenceImage 
 ); 
  
 } 
  
 else 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "No reference image." 
 ); 
  
 } 
  
 } 
  
 } 
 }

Node.js

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  // Imports the Google Cloud client library 
 const 
  
 vision 
  
 = 
  
 require 
 ( 
 ' @google-cloud/vision 
' 
 ); 
 // Creates a client 
 const 
  
 client 
  
 = 
  
 new 
  
 vision 
 . 
  ProductSearchClient 
 
 (); 
 async 
  
 function 
  
 importProductSets 
 () 
  
 { 
  
 /** 
 * TODO(developer): Uncomment the following line before running the sample. 
 */ 
  
 // const projectId = 'Your Google Cloud project Id'; 
  
 // const location = 'A compute region name'; 
  
 // const gcsUri = 'Google Cloud Storage URI. Target files must be in Product Search CSV format'; 
  
 // A resource that represents Google Cloud Platform location. 
  
 const 
  
 projectLocation 
  
 = 
  
 client 
 . 
 locationPath 
 ( 
 projectId 
 , 
  
 location 
 ); 
  
 // Set the input configuration along with Google Cloud Storage URI 
  
 const 
  
 inputConfig 
  
 = 
  
 { 
  
 gcsSource 
 : 
  
 { 
  
 csvFileUri 
 : 
  
 gcsUri 
 , 
  
 }, 
  
 }; 
  
 // Import the product sets from the input URI. 
  
 const 
  
 [ 
 response 
 , 
  
 operation 
 ] 
  
 = 
  
 await 
  
 client 
 . 
 importProductSets 
 ({ 
  
 parent 
 : 
  
 projectLocation 
 , 
  
 inputConfig 
 : 
  
 inputConfig 
 , 
  
 }); 
  
 console 
 . 
 log 
 ( 
 'Processing operation name: ' 
 , 
  
 operation 
 . 
 name 
 ); 
  
 // synchronous check of operation status 
  
 const 
  
 [ 
 result 
 ] 
  
 = 
  
 await 
  
 response 
 . 
 promise 
 (); 
  
 console 
 . 
 log 
 ( 
 'Processing done.' 
 ); 
  
 console 
 . 
 log 
 ( 
 'Results of the processing:' 
 ); 
  
 for 
  
 ( 
 const 
  
 i 
  
 in 
  
  result 
 
 . 
 statuses 
 ) 
  
 { 
  
 console 
 . 
 log 
 ( 
  
 'Status of processing ' 
 , 
  
 i 
 , 
  
 'of the csv:' 
 , 
  
  result 
 
 . 
 statuses 
 [ 
 i 
 ] 
  
 ); 
  
 // Check the status of reference image 
  
 if 
  
 ( 
  result 
 
 . 
 statuses 
 [ 
 i 
 ]. 
 code 
  
 === 
  
 0 
 ) 
  
 { 
  
 console 
 . 
 log 
 ( 
  result 
 
 . 
 referenceImages 
 [ 
 i 
 ]); 
  
 } 
  
 else 
  
 { 
  
 console 
 . 
 log 
 ( 
 'No reference image.' 
 ); 
  
 } 
  
 } 
 } 
 importProductSets 
 ();

Python

To authenticate to Vision API Product Search, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  def 
  
 import_product_sets 
 ( 
 project_id 
 , 
 location 
 , 
 gcs_uri 
 ): 
  
 """Import images of different products in the product set. 
 Args: 
 project_id: Id of the project. 
 location: A compute region name. 
 gcs_uri: Google Cloud Storage URI. 
 Target files must be in Product Search CSV format. 
 """ 
 client 
 = 
 vision 
 . 
 ProductSearchClient 
 () 
 # A resource that represents Google Cloud Platform location. 
 location_path 
 = 
 f 
 "projects/ 
 { 
 project_id 
 } 
 /locations/ 
 { 
 location 
 } 
 " 
 # Set the input configuration along with Google Cloud Storage URI 
 gcs_source 
 = 
 vision 
 . 
 ImportProductSetsGcsSource 
 ( 
 csv_file_uri 
 = 
 gcs_uri 
 ) 
 input_config 
 = 
 vision 
 . 
 ImportProductSetsInputConfig 
 ( 
 gcs_source 
 = 
 gcs_source 
 ) 
 # Import the product sets from the input URI. 
 response 
 = 
 client 
 . 
 import_product_sets 
 ( 
 parent 
 = 
 location_path 
 , 
 input_config 
 = 
 input_config 
 ) 
 print 
 ( 
 f 
 "Processing operation name: 
 { 
 response 
 . 
 operation 
 . 
 name 
 } 
 " 
 ) 
 # synchronous check of operation status 
 result 
 = 
 response 
 . 
 result 
 () 
 print 
 ( 
 "Processing done." 
 ) 
 for 
 i 
 , 
 status 
 in 
 enumerate 
 ( 
 result 
 . 
 statuses 
 ): 
 print 
 ( 
 "Status of processing line 
 {} 
 of the csv: 
 {} 
 " 
 . 
 format 
 ( 
 i 
 , 
 status 
 )) 
 # Check the status of reference image 
 # `0` is the code for OK in google.rpc.Code. 
 if 
 status 
 . 
 code 
 == 
 0 
 : 
 reference_image 
 = 
 result 
 . 
 reference_images 
 [ 
 i 
 ] 
 print 
 ( 
 reference_image 
 ) 
 else 
 : 
 print 
 ( 
 f 
 "Status code not OK: 
 { 
 status 
 . 
 message 
 } 
 " 
 )

Additional languages

C#: Please follow the C# setup instructions on the client libraries page and then visit the Vision API Product Search reference documentation for .NET.

PHP: Please follow the PHP setup instructions on the client libraries page and then visit the Vision API Product Search reference documentation for PHP.

Ruby: Please follow the Ruby setup instructions on the client libraries page and then visit the Vision API Product Search reference documentation for Ruby.

Indexing

The Product Search index of products is updated approximately every 30 minutes. When images are added or deleted, the change won't be reflected in your Product Search responses until the index is next updated.

To make sure that indexing has completed successfully, check the indexTime field of a product set.

Creating your reference images & indexing Stay organized with collections Save and categorize content based on your preferences.

Creating a single reference image

REST

curl

PowerShell

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Java

Node.js

Python

Additional languages

Creating multiple reference images with bulk import

CSV format

Bulk creation request

REST

curl

PowerShell

Go

Java

Node.js

Python

Additional languages

Indexing

Creating your reference images & indexing