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    Searching for Products

    Once you have created your product set and the product set has been indexed, you can query the product set using the Cloud Vision API.

    You can find similar products to a given image by passing the image's Google Cloud Storage URI, web URL, or base64 encoded string to Vision API Product Search. Refer to the Usage Limits for maximum request size and quota information.

    See the Understanding search responses & multi-detection topic for an example of single product detection and multi-detection of products in an image.

    Search using a local image

    The following samples read a local file and query the API by including inline the raw image bytes (base64 encoded image) in the request.

    REST

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

    • BASE64_ENCODED_IMAGE : The base64 representation (ASCII string) of your binary image data. This string should look similar to the following string:
      • /9j/4QAYRXhpZgAA...9tAVx/zDQDlGxn//2Q==
      Visit the base64 encode topic for more information.
    • 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_SET_ID : The ID for the product set you want to run the operation on.

    Field-specific considerations:

    • features.maxResults - The maximum number of results to be returned.
    • imageContext.productCategories - The product category to search in. Currently you can only specify one product category (homegoods, apparel, toys, packaged goods, and general ).
    • imageContext.filter - (Optional) A key-value filtering expression (or multiple expressions) for product label. Format: " key = value ". Filtering key-value pairs can be linked with AND or OR expressions: " color = blue AND style = mens ", or " color = blue OR color = black ". If using the OR expression all keys in the expression must be the same .

    HTTP method and URL:

    POST https://vision.googleapis.com/v1/images:annotate

    Request JSON body:

    {
  "requests": [
    {
      "image": {
        "content": base64-encoded-image 
},
      "features": [
        {
          "type": "PRODUCT_SEARCH",
          "maxResults": 5
        }
      ],
      "imageContext": {
        "productSearchParams": {
          "productSet": "projects/ project-id 
/locations/ location-id 
/productSets/ product-set-id 
",
          "productCategories": [
               "apparel"
          ],
          "filter": "style = womens"
        }
      }
    }
  ]
}

    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/images:annotate"

    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/images:annotate" | Select-Object -Expand Content

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

    The response JSON includes the two following result types:

    • productSearchResults - Contains a list of matching products for the entire image. In the sample response the matching products are: product_id65, product_id35, product_id34, product_id62, product_id32.
    • productGroupedResults - Contains bounding box coordinates and matching items for each product identified in the image. In the following response there is only one product identified, followed by matching products in the sample product set: product_id65, product_id35, product_id34, product_id93, product_id62.

    Note that while there is overlap in the two result types, there may also be differences (for example, product_id32 and product_id93 in the response).

    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" 
  
 "os" 
  
 vision 
  
 "cloud.google.com/go/vision/apiv1" 
  
 "cloud.google.com/go/vision/v2/apiv1/visionpb" 
 ) 
 // getSimilarProducts searches for products from a product set similar to products in an image file. 
 func 
  
 getSimilarProducts 
 ( 
 w 
  
 io 
 . 
 Writer 
 , 
  
 projectID 
  
 string 
 , 
  
 location 
  
 string 
 , 
  
 productSetID 
  
 string 
 , 
  
 productCategory 
  
 string 
 , 
  
 file 
  
 string 
 , 
  
 filter 
  
 string 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 c 
 , 
  
 err 
  
 := 
  
 vision 
 . 
 NewImageAnnotatorClient 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewImageAnnotatorClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 c 
 . 
 Close 
 () 
  
 f 
 , 
  
 err 
  
 := 
  
 os 
 . 
 Open 
 ( 
 file 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "Open: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 f 
 . 
 Close 
 () 
  
 image 
 , 
  
 err 
  
 := 
  
 vision 
 . 
  NewImageFromReader 
 
 ( 
 f 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewImageFromReader: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 ictx 
  
 := 
  
& visionpb 
 . 
  ImageContext 
 
 { 
  
 ProductSearchParams 
 : 
  
& visionpb 
 . 
  ProductSearchParams 
 
 { 
  
 ProductSet 
 : 
  
 fmt 
 . 
 Sprintf 
 ( 
 "projects/%s/locations/%s/productSets/%s" 
 , 
  
 projectID 
 , 
  
 location 
 , 
  
 productSetID 
 ), 
  
 ProductCategories 
 : 
  
 [] 
 string 
 { 
 productCategory 
 }, 
  
 Filter 
 : 
  
 filter 
 , 
  
 }, 
  
 } 
  
 response 
 , 
  
 err 
  
 := 
  
 c 
 . 
  ProductSearch 
 
 ( 
 ctx 
 , 
  
 image 
 , 
  
 ictx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "ProductSearch: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Product set index time:\n" 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "seconds: %d\n" 
 , 
  
 response 
 . 
 IndexTime 
 . 
 Seconds 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "nanos: %d\n" 
 , 
  
 response 
 . 
 IndexTime 
 . 
 Nanos 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Search results:\n" 
 ) 
  
 for 
  
 _ 
 , 
  
 result 
  
 := 
  
 range 
  
 response 
 . 
 Results 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Score(Confidence): %f\n" 
 , 
  
 result 
 . 
 Score 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Image name: %s\n" 
 , 
  
 result 
 . 
  Image 
 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Prodcut name: %s\n" 
 , 
  
 result 
 . 
  Product 
 
 . 
 Name 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Product display name: %s\n" 
 , 
  
 result 
 . 
  Product 
 
 . 
 DisplayName 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Product labels: %s\n" 
 , 
  
 result 
 . 
  Product 
 
 . 
 ProductLabels 
 ) 
  
 } 
  
 return 
  
 nil 
 }

    Java

    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 Java 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 .

      /** 
 * Search similar products to image in local file. 
 * 
 * @param projectId - Id of the project. 
 * @param computeRegion - Region name. 
 * @param productSetId - Id of the product set. 
 * @param productCategory - Category of the product. 
 * @param filePath - Local file path of the image to be searched 
 * @param filter - Condition to be applied on the labels. Example for filter: (color = red OR 
 *     color = blue) AND style = kids It will search on all products with the following labels: 
 *     color:red AND style:kids color:blue AND style:kids 
 * @throws IOException - on I/O errors. 
 */ 
 public 
  
 static 
  
 void 
  
 getSimilarProductsFile 
 ( 
  
 String 
  
 projectId 
 , 
  
 String 
  
 computeRegion 
 , 
  
 String 
  
 productSetId 
 , 
  
 String 
  
 productCategory 
 , 
  
 String 
  
 filePath 
 , 
  
 String 
  
 filter 
 ) 
  
 throws 
  
 IOException 
  
 { 
  
 try 
  
 ( 
 ImageAnnotatorClient 
  
 queryImageClient 
  
 = 
  
 ImageAnnotatorClient 
 . 
 create 
 ()) 
  
 { 
  
 // Get the full path of the product set. 
  
 String 
  
 productSetPath 
  
 = 
  
 ProductSetName 
 . 
 format 
 ( 
 projectId 
 , 
  
 computeRegion 
 , 
  
 productSetId 
 ); 
  
 // Read the image as a stream of bytes. 
  
 File 
  
 imgPath 
  
 = 
  
 new 
  
 File 
 ( 
 filePath 
 ); 
  
 byte 
 [] 
  
 content 
  
 = 
  
 Files 
 . 
 readAllBytes 
 ( 
 imgPath 
 . 
 toPath 
 ()); 
  
 // Create annotate image request along with product search feature. 
  
 Feature 
  
 featuresElement 
  
 = 
  
 Feature 
 . 
 newBuilder 
 (). 
 setType 
 ( 
 Type 
 . 
 PRODUCT_SEARCH 
 ). 
 build 
 (); 
  
 // The input image can be a HTTPS link or Raw image bytes. 
  
 // Example: 
  
 // To use HTTP link replace with below code 
  
 //  ImageSource source = ImageSource.newBuilder().setImageUri(imageUri).build(); 
  
 //  Image image = Image.newBuilder().setSource(source).build(); 
  
 Image 
  
 image 
  
 = 
  
 Image 
 . 
 newBuilder 
 (). 
 setContent 
 ( 
 ByteString 
 . 
 copyFrom 
 ( 
 content 
 )). 
 build 
 (); 
  
 ImageContext 
  
 imageContext 
  
 = 
  
 ImageContext 
 . 
 newBuilder 
 () 
  
 . 
 setProductSearchParams 
 ( 
  
 ProductSearchParams 
 . 
 newBuilder 
 () 
  
 . 
 setProductSet 
 ( 
 productSetPath 
 ) 
  
 . 
 addProductCategories 
 ( 
 productCategory 
 ) 
  
 . 
 setFilter 
 ( 
 filter 
 )) 
  
 . 
 build 
 (); 
  
 AnnotateImageRequest 
  
 annotateImageRequest 
  
 = 
  
 AnnotateImageRequest 
 . 
 newBuilder 
 () 
  
 . 
 addFeatures 
 ( 
 featuresElement 
 ) 
  
 . 
 setImage 
 ( 
 image 
 ) 
  
 . 
 setImageContext 
 ( 
 imageContext 
 ) 
  
 . 
 build 
 (); 
  
 List<AnnotateImageRequest> 
  
 requests 
  
 = 
  
 Arrays 
 . 
 asList 
 ( 
 annotateImageRequest 
 ); 
  
 // Search products similar to the image. 
  
 BatchAnnotateImagesResponse 
  
 response 
  
 = 
  
 queryImageClient 
 . 
 batchAnnotateImages 
 ( 
 requests 
 ); 
  
 List<Result> 
  
 similarProducts 
  
 = 
  
 response 
 . 
 getResponses 
 ( 
 0 
 ). 
 getProductSearchResults 
 (). 
 getResultsList 
 (); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Similar Products: " 
 ); 
  
 for 
  
 ( 
 Result 
  
 product 
  
 : 
  
 similarProducts 
 ) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "\nProduct name: %s" 
 , 
  
 product 
 . 
 getProduct 
 (). 
 getName 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
  
 String 
 . 
 format 
 ( 
 "Product display name: %s" 
 , 
  
 product 
 . 
 getProduct 
 (). 
 getDisplayName 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
  
 String 
 . 
 format 
 ( 
 "Product description: %s" 
 , 
  
 product 
 . 
 getProduct 
 (). 
 getDescription 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Score(Confidence): %s" 
 , 
  
 product 
 . 
 getScore 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Image name: %s" 
 , 
  
 product 
 . 
 getImage 
 ())); 
  
 } 
  
 } 
 }

    Node.js

    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 Node.js 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 .

      // Imports the Google Cloud client library 
 const 
  
 vision 
  
 = 
  
 require 
 ( 
 ' @google-cloud/vision 
' 
 ); 
 const 
  
 fs 
  
 = 
  
 require 
 ( 
 'fs' 
 ); 
 // Creates a client 
 const 
  
 productSearchClient 
  
 = 
  
 new 
  
 vision 
 . 
  ProductSearchClient 
 
 (); 
 const 
  
 imageAnnotatorClient 
  
 = 
  
 new 
  
 vision 
 . 
  ImageAnnotatorClient 
 
 (); 
 async 
  
 function 
  
 getSimilarProductsFile 
 () 
  
 { 
  
 /** 
 * TODO(developer): Uncomment the following line before running the sample. 
 */ 
  
 // const projectId = 'nodejs-docs-samples'; 
  
 // const location = 'us-west1'; 
  
 // const productSetId = 'indexed_product_set_id_for_testing'; 
  
 // const productCategory = 'apparel'; 
  
 // const filePath = './resources/shoes_1.jpg'; 
  
 // const filter = ''; 
  
 const 
  
 productSetPath 
  
 = 
  
 productSearchClient 
 . 
 productSetPath 
 ( 
  
 projectId 
 , 
  
 location 
 , 
  
 productSetId 
  
 ); 
  
 const 
  
 content 
  
 = 
  
 fs 
 . 
 readFileSync 
 ( 
 filePath 
 , 
  
 'base64' 
 ); 
  
 const 
  
 request 
  
 = 
  
 { 
  
 // The input image can be a GCS link or HTTPS link or Raw image bytes. 
  
 // Example: 
  
 // To use GCS link replace with below code 
  
 // image: {source: {gcsImageUri: filePath}} 
  
 // To use HTTP link replace with below code 
  
 // image: {source: {imageUri: filePath}} 
  
 image 
 : 
  
 { 
 content 
 : 
  
 content 
 }, 
  
 features 
 : 
  
 [{ 
 type 
 : 
  
 'PRODUCT_SEARCH' 
 }], 
  
 imageContext 
 : 
  
 { 
  
 productSearchParams 
 : 
  
 { 
  
 productSet 
 : 
  
 productSetPath 
 , 
  
 productCategories 
 : 
  
 [ 
 productCategory 
 ], 
  
 filter 
 : 
  
 filter 
 , 
  
 }, 
  
 }, 
  
 }; 
  
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 imageAnnotatorClient 
 . 
 batchAnnotateImages 
 ({ 
  
 requests 
 : 
  
 [ 
 request 
 ], 
  
 }); 
  
 console 
 . 
 log 
 ( 
 'Search Image:' 
 , 
  
 filePath 
 ); 
  
 const 
  
 results 
  
 = 
  
 response 
 [ 
 'responses' 
 ][ 
 0 
 ][ 
 'productSearchResults' 
 ][ 
 'results' 
 ]; 
  
 console 
 . 
 log 
 ( 
 '\nSimilar product information:' 
 ); 
  
 results 
 . 
 forEach 
 ( 
 result 
  
 = 
>  
 { 
  
 console 
 . 
 log 
 ( 
 'Product id:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 name 
 . 
 split 
 ( 
 '/' 
 ). 
 pop 
 ( 
 - 
 1 
 )); 
  
 console 
 . 
 log 
 ( 
 'Product display name:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 displayName 
 ); 
  
 console 
 . 
 log 
 ( 
 'Product description:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 description 
 ); 
  
 console 
 . 
 log 
 ( 
 'Product category:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 productCategory 
 ); 
  
 }); 
 } 
 getSimilarProductsFile 
 ();

    Python

    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 Python 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 .

      from 
  
 google.cloud 
  
 import 
 vision 
 def 
  
 get_similar_products_file 
 ( 
 project_id 
 , 
 location 
 , 
 product_set_id 
 , 
 product_category 
 , 
 file_path 
 , 
 filter 
 , 
 max_results 
 , 
 ): 
  
 """Search similar products to image. 
 Args: 
 project_id: Id of the project. 
 location: A compute region name. 
 product_set_id: Id of the product set. 
 product_category: Category of the product. 
 file_path: Local file path of the image to be searched. 
 filter: Condition to be applied on the labels. 
 Example for filter: (color = red OR color = blue) AND style = kids 
 It will search on all products with the following labels: 
 color:red AND style:kids 
 color:blue AND style:kids 
 max_results: The maximum number of results (matches) to return. If omitted, all results are returned. 
 """ 
 # product_search_client is needed only for its helper methods. 
 product_search_client 
 = 
 vision 
 . 
  ProductSearchClient 
 
 () 
 image_annotator_client 
 = 
 vision 
 . 
  ImageAnnotatorClient 
 
 () 
 # Read the image as a stream of bytes. 
 with 
 open 
 ( 
 file_path 
 , 
 "rb" 
 ) 
 as 
 image_file 
 : 
 content 
 = 
 image_file 
 . 
 read 
 () 
 # Create annotate image request along with product search feature. 
 image 
 = 
 vision 
 . 
  Image 
 
 ( 
 content 
 = 
 content 
 ) 
 # product search specific parameters 
 product_set_path 
 = 
 product_search_client 
 . 
  product_set_path 
 
 ( 
 project 
 = 
 project_id 
 , 
 location 
 = 
 location 
 , 
 product_set 
 = 
 product_set_id 
 ) 
 product_search_params 
 = 
 vision 
 . 
  ProductSearchParams 
 
 ( 
 product_set 
 = 
 product_set_path 
 , 
 product_categories 
 = 
 [ 
 product_category 
 ], 
 filter 
 = 
 filter 
 , 
 ) 
 image_context 
 = 
 vision 
 . 
  ImageContext 
 
 ( 
 product_search_params 
 = 
 product_search_params 
 ) 
 # Search products similar to the image. 
 response 
 = 
 image_annotator_client 
 . 
  product_search 
 
 ( 
 image 
 , 
 image_context 
 = 
 image_context 
 , 
 max_results 
 = 
 max_results 
 ) 
 index_time 
 = 
 response 
 . 
 product_search_results 
 . 
 index_time 
 print 
 ( 
 "Product set index time: " 
 ) 
 print 
 ( 
 index_time 
 ) 
 results 
 = 
 response 
 . 
 product_search_results 
 . 
 results 
 print 
 ( 
 "Search results:" 
 ) 
 for 
 result 
 in 
 results 
 : 
 product 
 = 
 result 
 . 
 product 
 print 
 ( 
 f 
 "Score(Confidence): 
 { 
 result 
 . 
 score 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Image name: 
 { 
 result 
 . 
 image 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Product name: 
 { 
 product 
 . 
 name 
 } 
 " 
 ) 
 print 
 ( 
 "Product display name: 
 {} 
 " 
 . 
 format 
 ( 
 product 
 . 
 display_name 
 )) 
 print 
 ( 
 f 
 "Product description: 
 { 
 product 
 . 
 description 
 } 
 \n 
 " 
 ) 
 print 
 ( 
 f 
 "Product labels: 
 { 
 product 
 . 
 product_labels 
 } 
 \n 
 " 
 )

    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.

    Search using a remote image

    You also have the option of finding similar products to a given image by specifying the Cloud Storage URI to the image.

    REST

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

    • 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
    • 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_SET_ID : The ID for the product set you want to run the operation on.

    Field-specific considerations:

    • features.maxResults - The maximum number of results to be returned.
    • imageContext.productCategories - The product category to search in. Currently you can only specify one product category (homegoods, apparel, toys, packaged goods, and general ).
    • imageContext.filter - (Optional) A key-value filtering expression (or multiple expressions) for product label. Format: " key = value ". Filtering key-value pairs can be linked with AND or OR expressions: " color = blue AND style = mens ", or " color = blue OR color = black ". If using the OR expression all keys in the expression must be the same .

    HTTP method and URL:

    POST https://vision.googleapis.com/v1/images:annotate

    Request JSON body:

    {
  "requests": [
    {
      "image": {
        "source": {
          "gcsImageUri": " cloud-storage-image-uri 
"
        }
      },
      "features": [
        {
          "type": "PRODUCT_SEARCH",
          "maxResults": 5
        }
      ],
      "imageContext": {
        "productSearchParams": {
          "productSet": "projects/ project-id 
/locations/ location-id 
/productSets/ product-set-id 
",
          "productCategories": [
               "apparel"
          ],
          "filter": "style = womens"
        }
      }
    }
  ]
}

    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/images:annotate"

    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/images:annotate" | Select-Object -Expand Content

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

    The response JSON includes the two following result types:

    • productSearchResults - Contains a list of matching products for the entire image. In the sample response the matching products are: product_id65, product_id35, product_id34, product_id62, product_id32.
    • productGroupedResults - Contains bounding box coordinates and matching items for each product identified in the image. In the following response there is only one product identified, followed by matching products in the sample product set: product_id65, product_id35, product_id34, product_id93, product_id62.

    Note that while there is overlap in the two result types, there may also be differences (for example, product_id32 and product_id93 in the response).

    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" 
 ) 
 // getSimilarProductsURI searches for products from a product set similar to products in an image file on GCS. 
 func 
  
 getSimilarProductsURI 
 ( 
 w 
  
 io 
 . 
 Writer 
 , 
  
 projectID 
  
 string 
 , 
  
 location 
  
 string 
 , 
  
 productSetID 
  
 string 
 , 
  
 productCategory 
  
 string 
 , 
  
 imageURI 
  
 string 
 , 
  
 filter 
  
 string 
 ) 
  
 error 
  
 { 
  
 ctx 
  
 := 
  
 context 
 . 
 Background 
 () 
  
 c 
 , 
  
 err 
  
 := 
  
 vision 
 . 
 NewImageAnnotatorClient 
 ( 
 ctx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "NewImageAnnotatorClient: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 defer 
  
 c 
 . 
 Close 
 () 
  
 image 
  
 := 
  
 vision 
 . 
  NewImageFromURI 
 
 ( 
 imageURI 
 ) 
  
 ictx 
  
 := 
  
& visionpb 
 . 
  ImageContext 
 
 { 
  
 ProductSearchParams 
 : 
  
& visionpb 
 . 
  ProductSearchParams 
 
 { 
  
 ProductSet 
 : 
  
 fmt 
 . 
 Sprintf 
 ( 
 "projects/%s/locations/%s/productSets/%s" 
 , 
  
 projectID 
 , 
  
 location 
 , 
  
 productSetID 
 ), 
  
 ProductCategories 
 : 
  
 [] 
 string 
 { 
 productCategory 
 }, 
  
 Filter 
 : 
  
 filter 
 , 
  
 }, 
  
 } 
  
 response 
 , 
  
 err 
  
 := 
  
 c 
 . 
  ProductSearch 
 
 ( 
 ctx 
 , 
  
 image 
 , 
  
 ictx 
 ) 
  
 if 
  
 err 
  
 != 
  
 nil 
  
 { 
  
 return 
  
 fmt 
 . 
 Errorf 
 ( 
 "ProductSearch: %w" 
 , 
  
 err 
 ) 
  
 } 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Product set index time:\n" 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "seconds: %d\n" 
 , 
  
 response 
 . 
 IndexTime 
 . 
 Seconds 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "nanos: %d\n" 
 , 
  
 response 
 . 
 IndexTime 
 . 
 Nanos 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Search results:\n" 
 ) 
  
 for 
  
 _ 
 , 
  
 result 
  
 := 
  
 range 
  
 response 
 . 
 Results 
  
 { 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Score(Confidence): %f\n" 
 , 
  
 result 
 . 
 Score 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Image name: %s\n" 
 , 
  
 result 
 . 
  Image 
 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Prodcut name: %s\n" 
 , 
  
 result 
 . 
  Product 
 
 . 
 Name 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Product display name: %s\n" 
 , 
  
 result 
 . 
  Product 
 
 . 
 DisplayName 
 ) 
  
 fmt 
 . 
 Fprintf 
 ( 
 w 
 , 
  
 "Product labels: %s\n" 
 , 
  
 result 
 . 
  Product 
 
 . 
 ProductLabels 
 ) 
  
 } 
  
 return 
  
 nil 
 }

    Java

    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 Java 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 .

      /** 
 * Search similar products to image in Google Cloud Storage. 
 * 
 * @param projectId - Id of the project. 
 * @param computeRegion - Region name. 
 * @param productSetId - Id of the product set. 
 * @param productCategory - Category of the product. 
 * @param gcsUri - GCS file path of the image to be searched 
 * @param filter - Condition to be applied on the labels. Example for filter: (color = red OR 
 *     color = blue) AND style = kids It will search on all products with the following labels: 
 *     color:red AND style:kids color:blue AND style:kids 
 * @throws Exception - on errors. 
 */ 
 public 
  
 static 
  
 void 
  
 getSimilarProductsGcs 
 ( 
  
 String 
  
 projectId 
 , 
  
 String 
  
 computeRegion 
 , 
  
 String 
  
 productSetId 
 , 
  
 String 
  
 productCategory 
 , 
  
 String 
  
 gcsUri 
 , 
  
 String 
  
 filter 
 ) 
  
 throws 
  
 Exception 
  
 { 
  
 try 
  
 ( 
 ImageAnnotatorClient 
  
 queryImageClient 
  
 = 
  
 ImageAnnotatorClient 
 . 
 create 
 ()) 
  
 { 
  
 // Get the full path of the product set. 
  
 String 
  
 productSetPath 
  
 = 
  
 ProductSetName 
 . 
 of 
 ( 
 projectId 
 , 
  
 computeRegion 
 , 
  
 productSetId 
 ). 
 toString 
 (); 
  
 // Get the image from Google Cloud Storage 
  
 ImageSource 
  
 source 
  
 = 
  
 ImageSource 
 . 
 newBuilder 
 (). 
 setGcsImageUri 
 ( 
 gcsUri 
 ). 
 build 
 (); 
  
 // Create annotate image request along with product search feature. 
  
 Feature 
  
 featuresElement 
  
 = 
  
 Feature 
 . 
 newBuilder 
 (). 
 setType 
 ( 
 Type 
 . 
 PRODUCT_SEARCH 
 ). 
 build 
 (); 
  
 Image 
  
 image 
  
 = 
  
 Image 
 . 
 newBuilder 
 (). 
 setSource 
 ( 
 source 
 ). 
 build 
 (); 
  
 ImageContext 
  
 imageContext 
  
 = 
  
 ImageContext 
 . 
 newBuilder 
 () 
  
 . 
 setProductSearchParams 
 ( 
  
 ProductSearchParams 
 . 
 newBuilder 
 () 
  
 . 
 setProductSet 
 ( 
 productSetPath 
 ) 
  
 . 
 addProductCategories 
 ( 
 productCategory 
 ) 
  
 . 
 setFilter 
 ( 
 filter 
 )) 
  
 . 
 build 
 (); 
  
 AnnotateImageRequest 
  
 annotateImageRequest 
  
 = 
  
 AnnotateImageRequest 
 . 
 newBuilder 
 () 
  
 . 
 addFeatures 
 ( 
 featuresElement 
 ) 
  
 . 
 setImage 
 ( 
 image 
 ) 
  
 . 
 setImageContext 
 ( 
 imageContext 
 ) 
  
 . 
 build 
 (); 
  
 List<AnnotateImageRequest> 
  
 requests 
  
 = 
  
 Arrays 
 . 
 asList 
 ( 
 annotateImageRequest 
 ); 
  
 // Search products similar to the image. 
  
 BatchAnnotateImagesResponse 
  
 response 
  
 = 
  
 queryImageClient 
 . 
 batchAnnotateImages 
 ( 
 requests 
 ); 
  
 List<Result> 
  
 similarProducts 
  
 = 
  
 response 
 . 
 getResponses 
 ( 
 0 
 ). 
 getProductSearchResults 
 (). 
 getResultsList 
 (); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 "Similar Products: " 
 ); 
  
 for 
  
 ( 
 Result 
  
 product 
  
 : 
  
 similarProducts 
 ) 
  
 { 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "\nProduct name: %s" 
 , 
  
 product 
 . 
 getProduct 
 (). 
 getName 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
  
 String 
 . 
 format 
 ( 
 "Product display name: %s" 
 , 
  
 product 
 . 
 getProduct 
 (). 
 getDisplayName 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
  
 String 
 . 
 format 
 ( 
 "Product description: %s" 
 , 
  
 product 
 . 
 getProduct 
 (). 
 getDescription 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Score(Confidence): %s" 
 , 
  
 product 
 . 
 getScore 
 ())); 
  
 System 
 . 
 out 
 . 
 println 
 ( 
 String 
 . 
 format 
 ( 
 "Image name: %s" 
 , 
  
 product 
 . 
 getImage 
 ())); 
  
 } 
  
 } 
 }

    Node.js

    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 Node.js 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 .

      // Imports the Google Cloud client library 
 const 
  
 vision 
  
 = 
  
 require 
 ( 
 ' @google-cloud/vision 
' 
 ); 
 // Creates a client 
 const 
  
 productSearchClient 
  
 = 
  
 new 
  
 vision 
 . 
  ProductSearchClient 
 
 (); 
 const 
  
 imageAnnotatorClient 
  
 = 
  
 new 
  
 vision 
 . 
  ImageAnnotatorClient 
 
 (); 
 async 
  
 function 
  
 getSimilarProductsGcs 
 ( 
  
 projectId 
 , 
  
 location 
 , 
  
 productSetId 
 , 
  
 productCategory 
 , 
  
 filePath 
 , 
  
 filter 
 ) 
  
 { 
  
 /** 
 * TODO(developer): Uncomment the following line before running the sample. 
 */ 
  
 // const projectId = 'Your Google Cloud project Id'; 
  
 // const location = 'A compute region name'; 
  
 // const productSetId = 'Id of the product set'; 
  
 // const productCategory = 'Category of the product'; 
  
 // const filePath = 'Local file path of the image to be searched'; 
  
 // const filter = 'Condition to be applied on the labels'; 
  
 const 
  
 productSetPath 
  
 = 
  
 productSearchClient 
 . 
 productSetPath 
 ( 
  
 projectId 
 , 
  
 location 
 , 
  
 productSetId 
  
 ); 
  
 const 
  
 request 
  
 = 
  
 { 
  
 // The input image can be a GCS link or HTTPS link or Raw image bytes. 
  
 // Example: 
  
 // To use GCS link replace with below code 
  
 // image: {source: {gcsImageUri: filePath}} 
  
 // To use HTTP link replace with below code 
  
 // image: {source: {imageUri: filePath}} 
  
 image 
 : 
  
 { 
 source 
 : 
  
 { 
 gcsImageUri 
 : 
  
 filePath 
 }}, 
  
 features 
 : 
  
 [{ 
 type 
 : 
  
 'PRODUCT_SEARCH' 
 }], 
  
 imageContext 
 : 
  
 { 
  
 productSearchParams 
 : 
  
 { 
  
 productSet 
 : 
  
 productSetPath 
 , 
  
 productCategories 
 : 
  
 [ 
 productCategory 
 ], 
  
 filter 
 : 
  
 filter 
 , 
  
 }, 
  
 }, 
  
 }; 
  
 console 
 . 
 log 
 ( 
 request 
 . 
 image 
 ); 
  
 const 
  
 [ 
 response 
 ] 
  
 = 
  
 await 
  
 imageAnnotatorClient 
 . 
 batchAnnotateImages 
 ({ 
  
 requests 
 : 
  
 [ 
 request 
 ], 
  
 }); 
  
 console 
 . 
 log 
 ( 
 'Search Image:' 
 , 
  
 filePath 
 ); 
  
 console 
 . 
 log 
 ( 
 '\nSimilar product information:' 
 ); 
  
 const 
  
 results 
  
 = 
  
 response 
 [ 
 'responses' 
 ][ 
 0 
 ][ 
 'productSearchResults' 
 ][ 
 'results' 
 ]; 
  
 results 
 . 
 forEach 
 ( 
 result 
  
 = 
>  
 { 
  
 console 
 . 
 log 
 ( 
 'Product id:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 name 
 . 
 split 
 ( 
 '/' 
 ). 
 pop 
 ( 
 - 
 1 
 )); 
  
 console 
 . 
 log 
 ( 
 'Product display name:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 displayName 
 ); 
  
 console 
 . 
 log 
 ( 
 'Product description:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 description 
 ); 
  
 console 
 . 
 log 
 ( 
 'Product category:' 
 , 
  
  result 
 
 [ 
 'product' 
 ]. 
 productCategory 
 ); 
  
 }); 
 } 
 getSimilarProductsGcs 
 ();

    Python

    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 Python 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 .

      from 
  
 google.cloud 
  
 import 
 vision 
 def 
  
 get_similar_products_uri 
 ( 
 project_id 
 , 
 location 
 , 
 product_set_id 
 , 
 product_category 
 , 
 image_uri 
 , 
 filter 
 ): 
  
 """Search similar products to image. 
 Args: 
 project_id: Id of the project. 
 location: A compute region name. 
 product_set_id: Id of the product set. 
 product_category: Category of the product. 
 image_uri: Cloud Storage location of image to be searched. 
 filter: Condition to be applied on the labels. 
 Example for filter: (color = red OR color = blue) AND style = kids 
 It will search on all products with the following labels: 
 color:red AND style:kids 
 color:blue AND style:kids 
 """ 
 # product_search_client is needed only for its helper methods. 
 product_search_client 
 = 
 vision 
 . 
  ProductSearchClient 
 
 () 
 image_annotator_client 
 = 
 vision 
 . 
  ImageAnnotatorClient 
 
 () 
 # Create annotate image request along with product search feature. 
 image_source 
 = 
 vision 
 . 
  ImageSource 
 
 ( 
 image_uri 
 = 
 image_uri 
 ) 
 image 
 = 
 vision 
 . 
  Image 
 
 ( 
 source 
 = 
 image_source 
 ) 
 # product search specific parameters 
 product_set_path 
 = 
 product_search_client 
 . 
  product_set_path 
 
 ( 
 project 
 = 
 project_id 
 , 
 location 
 = 
 location 
 , 
 product_set 
 = 
 product_set_id 
 ) 
 product_search_params 
 = 
 vision 
 . 
  ProductSearchParams 
 
 ( 
 product_set 
 = 
 product_set_path 
 , 
 product_categories 
 = 
 [ 
 product_category 
 ], 
 filter 
 = 
 filter 
 , 
 ) 
 image_context 
 = 
 vision 
 . 
  ImageContext 
 
 ( 
 product_search_params 
 = 
 product_search_params 
 ) 
 # Search products similar to the image. 
 response 
 = 
 image_annotator_client 
 . 
  product_search 
 
 ( 
 image 
 , 
 image_context 
 = 
 image_context 
 ) 
 index_time 
 = 
 response 
 . 
 product_search_results 
 . 
 index_time 
 print 
 ( 
 "Product set index time: " 
 ) 
 print 
 ( 
 index_time 
 ) 
 results 
 = 
 response 
 . 
 product_search_results 
 . 
 results 
 print 
 ( 
 "Search results:" 
 ) 
 for 
 result 
 in 
 results 
 : 
 product 
 = 
 result 
 . 
 product 
 print 
 ( 
 f 
 "Score(Confidence): 
 { 
 result 
 . 
 score 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Image name: 
 { 
 result 
 . 
 image 
 } 
 " 
 ) 
 print 
 ( 
 f 
 "Product name: 
 { 
 product 
 . 
 name 
 } 
 " 
 ) 
 print 
 ( 
 "Product display name: 
 {} 
 " 
 . 
 format 
 ( 
 product 
 . 
 display_name 
 )) 
 print 
 ( 
 f 
 "Product description: 
 { 
 product 
 . 
 description 
 } 
 \n 
 " 
 ) 
 print 
 ( 
 f 
 "Product labels: 
 { 
 product 
 . 
 product_labels 
 } 
 \n 
 " 
 )

    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.

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