Vision API Product Search client libraries

  #include 
  
 "google/cloud/vision/v1/image_annotator_client.h" 
 #include <iostream> 
 int 
  
 main 
 ( 
 int 
  
 argc 
 , 
  
 char 
 * 
  
 argv 
 []) 
  
 try 
  
 { 
  
 auto 
  
 constexpr 
  
 kDefaultUri 
  
 = 
  
 "gs://cloud-samples-data/vision/label/wakeupcat.jpg" 
 ; 
  
 if 
  
 ( 
 argc 
 > 
 2 
 ) 
  
 { 
  
 std 
 :: 
 cerr 
 << 
 "Usage: " 
 << 
 argv 
 [ 
 0 
 ] 
 << 
 " [gcs-uri] 
 \n 
 " 
 << 
 "  The gcs-uri must be in gs://... format. It defaults to " 
 << 
 kDefaultUri 
 << 
 " 
 \n 
 " 
 ; 
  
 return 
  
 1 
 ; 
  
 } 
  
 auto 
  
 uri 
  
 = 
  
 std 
 :: 
 string 
 { 
 argc 
  
 == 
  
 2 
  
 ? 
  
 argv 
 [ 
 1 
 ] 
  
 : 
  
 kDefaultUri 
 }; 
  
 namespace 
  
 vision 
  
 = 
  
 :: 
 google 
 :: 
 cloud 
 :: 
 vision_v1 
 ; 
  
 auto 
  
 client 
  
 = 
  
 vision 
 :: 
 ImageAnnotatorClient 
 ( 
 vision 
 :: 
 MakeImageAnnotatorConnection 
 ()); 
  
 // Define the image we want to annotate 
  
 google 
 :: 
 cloud 
 :: 
 vision 
 :: 
 v1 
 :: 
 Image 
  
 image 
 ; 
  
 image 
 . 
 mutable_source 
 () 
 - 
> set_image_uri 
 ( 
 uri 
 ); 
  
 // Create a request to annotate this image with Request text annotations for a 
  
 // file stored in GCS. 
  
 google 
 :: 
 cloud 
 :: 
 vision 
 :: 
 v1 
 :: 
 AnnotateImageRequest 
  
 request 
 ; 
  
 * 
 request 
 . 
 mutable_image 
 () 
  
 = 
  
 std 
 :: 
 move 
 ( 
 image 
 ); 
  
 request 
 . 
 add_features 
 () 
 - 
> set_type 
 ( 
  
 google 
 :: 
 cloud 
 :: 
 vision 
 :: 
 v1 
 :: 
 Feature 
 :: 
 TEXT_DETECTION 
 ); 
  
 google 
 :: 
 cloud 
 :: 
 vision 
 :: 
 v1 
 :: 
 BatchAnnotateImagesRequest 
  
 batch_request 
 ; 
  
 * 
 batch_request 
 . 
 add_requests 
 () 
  
 = 
  
 std 
 :: 
 move 
 ( 
 request 
 ); 
  
 auto 
  
 batch 
  
 = 
  
 client 
 . 
 BatchAnnotateImages 
 ( 
 batch_request 
 ); 
  
 if 
  
 ( 
 ! 
 batch 
 ) 
  
 throw 
  
 std 
 :: 
 move 
 ( 
 batch 
 ). 
 status 
 (); 
  
 // Find the longest annotation and print it 
  
 auto 
  
 result 
  
 = 
  
 std 
 :: 
 string 
 {}; 
  
 for 
  
 ( 
 auto 
  
 const 
&  
 response 
  
 : 
  
 batch 
 - 
> responses 
 ()) 
  
 { 
  
 for 
  
 ( 
 auto 
  
 const 
&  
 annotation 
  
 : 
  
 response 
 . 
 text_annotations 
 ()) 
  
 { 
  
 if 
  
 ( 
 result 
 . 
 size 
 () 
 < 
 annotation 
 . 
 description 
 (). 
 size 
 ()) 
  
 { 
  
 result 
  
 = 
  
 annotation 
 . 
 description 
 (); 
  
 } 
  
 } 
  
 } 
  
 std 
 :: 
 cout 
 << 
 "The image contains this text: " 
 << 
 result 
 << 
 " 
 \n 
 " 
 ; 
  
 return 
  
 0 
 ; 
 } 
  
 catch 
  
 ( 
 google 
 :: 
 cloud 
 :: 
 Status 
  
 const 
&  
 status 
 ) 
  
 { 
  
 std 
 :: 
 cerr 
 << 
 "google::cloud::Status thrown: " 
 << 
 status 
 << 
 " 
 \n 
 " 
 ; 
  
 return 
  
 1 
 ; 
 } 
 

  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 
 } 
 

  /** 
 * 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 
 ())); 
  
 } 
  
 } 
 } 
 

  // 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 
 (); 
 

  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 
 " 
 )