Google Lens Search API

Google Lens Search API is a fast and simple image search tool that enables you to search the web using images. With this API, you can get visual matches, knowledge graph data, text results, and other information available through Google Lens. This API is a powerful tool for extracting information from images and making it easily searchable and accessible. Whether you're a developer, marketer, or researcher, the Google Lens Search API is an essential tool for uncovering new information and insights from images.

About the API: 

The Google Lens Search API is a fast and simple image search tool that enables you to search the web using images. With this API, you can get visual matches, knowledge graph data, text results, and other information available through Google Lens. This API provides an easy way to extract information from images, making it more accessible and searchable.

For developers, the API provides a way to add image-based search functionality to their applications. For marketers, it can help uncover new insights and information about their products and target audience. Researchers can also use the API to quickly find and analyze images related to their field of study.

The API is designed to be easy to use and integrate into existing applications. Simply submit an image to the API, and it will return relevant information, including a list of visually similar images, associated knowledge graph data, and text results. This makes the Google Lens Search API a powerful tool for extracting information from images and making it easily accessible and searchable.

 

What this API receives and what your API provides (input/output)?

Pass the image URL and receive its relevant information provided by Google Lens. 

 

What are the most common uses cases of this API?

  1. Image recognition: Use the API to recognize and extract information from images, such as objects, landmarks, and text.

  2. Object recognition: Use the API to recognize and classify objects within an image, such as identifying a product or a piece of artwork.

  3. Visual search: Use the API to search for visually similar images, such as finding more images of a particular product or landmark.

  4. Text extraction: Use the API to extract and analyze text from images, such as reading and translating text from foreign language signs and menus.

  5. Product recognition: Use the API to recognize and retrieve information about products, such as prices, specifications, and availability. This can be useful for e-commerce applications, price comparison websites, and more.



Are there any limitations to your plans?

Besides the number of API calls, there are no other limitations

API Documentation

Endpoints


Search Google Lens by URL and get knowledge graph entities, visual matches, products, text and other data available in Google Lens.

You can also indicate the country code, according to ISO 3166. For more details, please refer to the list of country codes at: https://en.wikipedia.org/wiki/List_of_ISO_639_language_codes

You can also indicate the country code, according to ISO 3166. For more details, please refer to the list of country codes at: https://en.wikipedia.org/wiki/List_of_ISO_3166_country_codes



                                                                            
GET https://zylalabs.com/api/1338/google+lens+search+api/1119/search
                                                                            
                                                                        

Search - Endpoint Features

Object Description
url [Required] URL of an image to perform Google Lens search.
country [Optional]
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"status":"OK","request_id":"e16060b7-ec2a-4a8d-8615-b2f1218adbf1","parameters":{"url":"https://i.imgur.com/HBrB8p0.png","language":"en","country":"us"},"data":{"visual_matches":[{"position":1,"title":"Danny DeVito - Simple English Wikipedia, the free encyclopedia","link":"https://simple.wikipedia.org/wiki/Danny_DeVito","source":"Wikipedia","source_icon":"https://encrypted-tbn3.gstatic.com/favicon-tbn?q=tbn:ANd9GcRUUbshUnin7ULaNODrg-lVcNBBMXFVfEUVbn_C-R6DJs51ANOoaJ90cg3hAt9FlHNrsWSlR0ODkNyjM15te9yLoYt4MoTFuNUPBNA33tYYl8mAb1r6uwwt4A","thumbnail":"https://encrypted-tbn2.gstatic.com/images?q=tbn:ANd9GcSCmF_Lnulfr0YI39HaDhPLcxBqs2e_E4CCx6u9sQJz0N5m7JE7"},{"position":2,"title":"Cameo critic: Danny DeVito digs 'The Bridge,' 'Homeland' and 'The Killing'","link":"https://www.startribune.com/cameo-critic-danny-devito-digs-the-bridge-homeland-and-the-killing/287245891","source":"Star Tribune","source_icon":"https://encrypted-tbn3.gstatic.com/favicon-tbn?q=tbn:ANd9GcQozWY2m3SDmxyWP43nTEV-qF_s0O4tpZzJ6E-TSSE2pvy4o02Dv_z-MdMUxDKSLJmax5EfZ154vPtpv5vwr4Nq6IHitvEItIItSPCO9dVWk1c6QIS04buR","thumbnail":"https://encrypted-tbn2.gstatic.com/images?q=tbn:ANd9GcRYFpNUrIJjSYxqsu37sy4LOvybl-VovvkVhSwdSLLdNRMaR3Iz"},{"position":3,"title":"Danny Devito desktop wallpapers - danny devito post - Imgur","link":"https://imgur.com/gallery/danny-devito-desktop-wallpapers-TgOHW","source":"Imgur","source_icon":"https://encrypted-tbn2.gstatic.com/favicon-tbn?q=tbn:ANd9GcT7l5l1tfiEpr6UVyH-PVZSaPFCkKU03ycf9YZSxdoW7sxql8fvC57lqgVvAPEg9aiGXYz73QoCx7OalpbCnSt7UFSJuk_cxEoaACRJscI","thumbnail":"https://encrypted-tbn1.gstatic.com/images?q=tbn:ANd9GcTHm0S1W59C5ZfUvbxzqDjsdCHkxYx37Vb4tTGKi1jYT0C6N9Zb"},{"position":4,"title":"Yuta Katsumi, PhD on X: \"First ever R21 submission as a PI. https://t.co/Ay2p5wpeFT\" / X","link":"https://twitter.com/yutakatsumi/status/1501635010507395080","source":"X","source_icon":"https://encrypted-tbn0.gstatic.com/favicon-tbn?q=tbn:ANd9GcTobhbt0ZKwS5VFQSzydvQt8vjhhiwervtw9rdJdbWu12RMXaoRjkTltT0aoTWQ6_jjnhnlkM8mMaX4wNSw065V_4Iu62Ljd402sY56ddVX_w","thumbnail":"https://encrypted-tbn3.gstatic.com/images?q=tbn:ANd9GcR-wNW1Gip5tdQ3ki_NBm_Mwk-T08Nvzs65QEJhp7n4PozkoGpu"},{"position":5,"title":"Γ‰ de espantar: Ator teve quase 90 anos de vida ativa no cinema; entenda","link":"https://www.em.com.br/webstories/flipar/2024/09/6949188-e-de-espantar-ator-teve-quase-90-anos-de-vida-ativa-no-cinema-entenda.html","source":"Estado de Minas","source_icon":"https://encrypted-tbn1.gstatic.com/favicon-tbn?q=tbn:ANd9GcQmo-aDr8FAJlqZSVAyaoNMmP2h-We1BWPcB1JOb_PgD-fJyniAKaXFfZxSEHXaJj12Omp9txvB6jxHQu4mZEbDiOsIqyNzh4PMaJSQkiynCLhj","thumbnail":"https://encrypted-tbn1.gstatic.com/images?q=tbn:ANd9GcTlPTFvVp7EnCOVio5yU9pHEZospxHlWYfSrPed5ThtzX33M1Kz"},{"position":6,"title":"Danny Devito Tank Top Man's Summer Round Neck Vest Classic Sport Sleeveless Tops","link":"https://www.amazon.com/Danny-Devito-Summer-Classic-Sleeveless/dp/B0D6Y1M9FS","source":"Amazon.com","source_icon":"https://encrypted-tbn1.gstatic.com/favicon-tbn?q=tbn:ANd9GcRm4oMDPHDSWBDQhB5-csYIdmVde_ZfnfUYnfzlJJ9w7zjXG34H4SL9TXI2H8XWInsqPagyhBQjtImrHgLv9Bwvw_d2JvfjMfz3ox9yR82MKQ7yrQ","thumbnail":"https://encrypted-tbn1.gstatic.com/images?q=tbn:ANd9GcR7p_Q3dn-myy3ls0X4IAXdyS5eI-DM87Ac79ISwxEvIPekhrn4","price":"$13.96","availability":"In stock"}],"knowledge_graph":[{"title":"Danny DeVito","link":"https://www.google.com/search?q=Danny+DeVito&kgmid=/m/0q9kd&hl=en&gl=US","images":[{"link":"https://encrypted-tbn1.gstatic.com/images?q=tbn:ANd9GcSEiibZoRKl9DXnou6b4ns6TlFP-v995UfEm0XpQZ2My4tWowpu","width":1200,"height":1427}]}],"detected_objects":[{"box":{"left":0.4964328,"top":0.533,"width":0.9904875,"height":0.934},"detections":[{"label":null,"type":"UNKNOWN","confidence":null},{"label":null,"type":"UNKNOWN","confidence":null}]},{"box":{"left":0.49821642,"top":0.742,"width":0.98692036,"height":0.5},"detections":[{"label":null,"type":"UNKNOWN","confidence":null}]},{"box":{"left":0.4411415,"top":0.305,"width":0.55410224,"height":0.16},"detections":[{"label":null,"type":"UNKNOWN","confidence":null}]}],"searched_object":{"box":{"left":0.4964328,"top":0.533,"width":0.9904875,"height":0.934},"detections":[{"label":null,"type":"UNKNOWN","confidence":null},{"label":null,"type":"UNKNOWN","confidence":null}]},"reverse_image_search_link":null}}
                                                                                                                                                                                                                    
                                                                                                    

Search - CODE SNIPPETS


curl --location --request GET 'https://zylalabs.com/api/1338/google+lens+search+api/1119/search?url=https://i.imgur.com/HBrB8p0.png' --header 'Authorization: Bearer YOUR_API_KEY' 


    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Google Lens Search API REST API, simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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Google Lens Search API FAQs

The API returns various types of data, including visual matches, knowledge graph entities, product information, and extracted text from images. This allows users to gain insights and context about the submitted images.

Key fields in the response include "status," "request_id," "parameters," and "data." Within "data," you can find "visual_matches," which contains details like "title," "link," and "thumbnail" for each match.

The response data is structured in a JSON format. It includes a top-level object with status and request details, followed by a "data" object that contains arrays of visual matches and associated information.

The endpoint accepts parameters such as "url" (the image URL), "language" (for text results), and "country" (to tailor results based on regional data). Users can customize their requests by specifying these parameters.

The endpoint provides information on visually similar images, knowledge graph entities, product details, and extracted text. This diverse data helps users understand and analyze the content of the submitted images.

Data accuracy is maintained through Google's extensive knowledge graph and image recognition algorithms. Continuous updates and machine learning techniques ensure that the information returned is relevant and reliable.

Typical use cases include image recognition for identifying objects or landmarks, visual search for finding similar products, and text extraction for translating or analyzing text from images, enhancing user experience in various applications.

Users can utilize the returned data by integrating it into applications for enhanced search functionality, creating visual catalogs, or providing contextual information about products and landmarks, thereby enriching user engagement.

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