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Summarize this article with:
Logo detection helps you find brand marks in images or video and identify which company they belong to. This guide compares the best logo detection and logo recognition APIs for 2026, including options for developers building automated workflows and marketers who need to monitor brand visibility.
You will also learn how to identify a logo from an image, what features to compare, and which tools fit use cases such as media monitoring, sponsorship analysis, content moderation, retail analytics, and visual search. Eden AI lets you test several of these providers through one API.
What is logo detection?
Logo detection is the process of finding a brand logo inside an image or video frame. A logo detection system uses computer vision and machine learning to scan visual content, locate brand marks, and return their position.
The output often includes a label for the detected brand and a bounding box showing where the logo appears. Some APIs also return a confidence score, but the exact response format depends on the provider.
Logo detection can work on product photos, social media posts, event footage, advertisements, storefront images, and broadcast video. Performance can vary based on image quality, logo size, rotation, partial visibility, background clutter, and whether the logo appears as text, a symbol, or both.
Logo detection vs. logo recognition
Logo detection and logo recognition are closely related, but they describe different steps. Logo detection answers the question: “Is there a logo in this image, and where is it?” Logo recognition answers: “Which brand does this logo represent?”
Many commercial APIs perform both tasks in one request. They locate the logo, then match it against a trained brand database. People often use the two terms interchangeably, so a tool described as a logo detection API may also provide logo recognition.
The Best Logo Detection & Recognition APIs in 2026
The best logo detection & recognition APIs in 2026 are Google Cloud Vision, AWS Rekognition, api4ai, Clarifai, Hive.ai, Visua, Smartclick, Microsoft Azure Computer Vision, and Roboflow.
1. Google Cloud Vision
Google Cloud Vision detects and recognizes common product logos within images. It returns the identified brand, a confidence score, and bounding-polygon coordinates that show where the logo appears. Logo detection is part of the broader Cloud Vision API, alongside OCR, label detection, landmark detection, and object localization. Video logo recognition is available through Google Cloud’s separate Video Intelligence API.
Key features
- Detects recognized brand logos in local images, web-hosted images, and files stored in Google Cloud Storage.
- Returns the logo description, confidence score, and location within the image.
- Supports asynchronous batch image annotation for larger offline workloads.
- Provides video logo detection and tracking through the separate Video Intelligence API.
Limitations
- Google describes the image feature as detecting “popular product logos” but does not publish the complete image-logo database, so you should test regional, niche, or less common brands with your own dataset.
- Image and video detection use separate Google Cloud APIs, integrations, and pricing models.
Best for
Developers already using Google Cloud and teams that want logo detection alongside other computer vision features such as OCR, image labeling, object localization, and SafeSearch analysis.
Pricing
For image logo detection, the first 1,000 units each month are free. Usage from 1,001 to 5,000,000 units costs $1.50 per 1,000 units, while usage above 5,000,000 units costs $0.60 per 1,000 units. Each feature applied to an image is billed as a separate unit.
Video logo detection is priced separately through the Video Intelligence API. The first 1,000 minutes are free, followed by $0.15 per minute.
2. Microsoft Azure Vision
Microsoft Azure Vision provides brand detection as a specialized form of object detection. It identifies commercial brand logos and returns the brand name, confidence score, and bounding-box coordinates.
Microsoft documents support for identifying brands in images and video, although video workflows may involve separate Azure services or processing components. It suits organizations already using Azure and teams that want logo detection alongside OCR, image analysis, and other computer vision capabilities.
Key features
- Returns the detected brand name, confidence score, and logo location.
- Uses a pre-trained database of global corporate logos.
- Fits into the broader Azure Vision environment for image analysis and OCR.
- Can support media-monitoring and product-placement analysis involving images or video.
Limitations
- Microsoft does not publish the complete list of supported brands, so regional and niche logo coverage requires testing.
- Azure’s product structure and regional availability can make it difficult to determine which service and API version should be used for each video workflow.
Best for
Enterprise teams using Microsoft Azure that need pre-trained brand detection together with OCR, image tagging, object detection, or other Azure AI services.
Pricing
5,000 free Image Analysis transactions per month on the F0 tier, with a limit of 20 transactions per minute. On Eden AI, Microsoft Azure logo detection costs start from $1 per 1,000 files.
3. Hive AI
Hive AI provides a pre-trained API that detects and recognizes logos in images and video. It can return the brand, confidence information, logo location, size, clarity, and details about the object on which the logo appears. The service is designed for workflows such as sponsorship measurement, brand monitoring, advertising analysis, and intellectual-property protection. You can request support for additional logos when a required brand is not already covered.
Key features
- Supports logo recognition and logo-location detection in both images and video.
- Returns information about the position, size, and visibility of each detected logo.
- Can identify multiple logos within the same visual asset.
- Allows customers to request coverage for additional brands or logo variations.
Limitations
- Hive does not publish its complete supported-logo list, so you need to confirm coverage for the brands relevant to your project.
- Advanced video analysis and custom logo requests may require direct coordination with the provider.
Best for
Media-monitoring platforms, sports and sponsorship analytics teams, advertisers, and brand-protection services that need detailed logo placement data across images and video.
Pricing: Hive lists image logo recognition at $5 per 1,000 requests.
4. api4ai
api4ai provides a ready-to-use Brand Recognition API that identifies brand marks and logos in images. It returns structured JSON describing the brands found in the submitted picture. Its main strength is its focus on logo and brand-mark recognition rather than general-purpose image analysis. It suits developers, media-monitoring teams, and marketers that want an image-based logo recognition service without training a model first.
Key features
- Detects multiple brand marks or logos within one image.
- Returns recognition results in a machine-readable JSON response.
- Accepts images through a production API and provides code examples in its documentation.
- Offers access through the api4ai Developer Portal and RapidAPI.
Limitations
- The provider does not clearly publish the complete list of supported brands on the main product page, so you should test coverage using your own logo set.
- The documented API focuses on images. Video workflows may require extracting frames before sending them for analysis.
Best for
Teams that need an off-the-shelf logo recognition API for brand monitoring, advertising analysis, social media images, or sponsorship measurement.
Pricing
On Eden AI, api4ai logo detection starts at $0.25 per 1,000 files for the default and v1 endpoints. The v2 endpoint costs $2.50 per 1,000 files. All listed api4ai logo detection models are available in the EU region.
5. Clarifai
Clarifai provides a pre-trained logo detection model for recognizing popular consumer brands in images and videos. The model locates detected logos rather than only assigning a label to the entire asset. Clarifai also supports custom visual detectors, allowing teams to train models for logos or brand marks that are not covered by the pre-trained option. It suits teams that want both an existing logo model and the ability to build more specialized computer vision workflows.
Key features
- Provides a pre-trained logo detection model for images and videos.
- Returns localized regions showing where detected logos appear.
- Supports custom visual detector training for company-specific or niche logos.
- Can combine models and processing steps within broader Clarifai workflows.
Limitations
- The current logo model page does not provide a complete public list of recognized brands, so coverage should be benchmarked against your own assets.
- Clarifai’s platform includes different models, workflows, and deployment options, which can make pricing and initial configuration less direct than a single-purpose logo API.
Best for
Teams that need logo detection across images and video, particularly when they may later add custom brand models or combine logo recognition with other computer vision tasks.
Pricing: starting from 2$ for 1k files.
6. SmartClick
SmartClick provides an API that detects logos in images or video and compares them with a logo database to return exact or similar matches. Customers can submit examples when they need the system to recognize a new logo. T
he provider states that new-logo onboarding can use a small set of reference images, but you should test performance with your own data. SmartClick suits teams that need straightforward logo recognition for social media monitoring, advertising analysis, or media processing.
Key features
- Supports logo detection and recognition in both images and video.
- Searches for exact and visually similar matches.
- Allows customers to add logos that are not already represented in the database.
- Can be accessed through Eden AI’s normalized logo-detection endpoint.
Limitations
- The public logo-detection page appears older, so current plan limits and product details should be confirmed directly.
- SmartClick does not publish its complete logo database or independently verified accuracy results.
Best for
Developers and marketing teams that need a hosted logo-recognition API for images or video and may need to add their own brand marks.
Pricing
SmartClick currently displays a free Basic plan with 1,000 requests per month, a Pro plan at $22.99 per month, and an Ultra plan at $85.99 per month. The page also lists overage fees and rate limits.
7. OpenAI
OpenAI’s multimodal models can analyze an image and identify visible logos or brand marks through natural-language instructions. Unlike dedicated logo detection services, OpenAI does not provide a fixed public database of supported brands or a specialized logo-detection endpoint.
Its main strength is contextual interpretation, since the model can describe the logo, read nearby text, and explain why it associates the image with a specific brand. It suits flexible image-analysis workflows where you need brand identification together with broader visual understanding. OpenAI’s current model catalog states that its latest models support image input and vision.
Key features
- Accepts images as input and returns a natural-language or structured text response.
- Can identify a visible brand and analyze nearby text, packaging, products, or scene context.
- Can process several visual instructions in one request, such as identifying the logo and describing where it appears.
- Supports structured output workflows, subject to the schema and model used.
Limitations
- OpenAI is not a dedicated logo-detection API and does not publish a complete list of recognizable logos.
- Do not assume that it returns calibrated confidence scores or precise bounding boxes. These outputs require testing and may not match the reliability of a specialized object-detection model.
Best for
Developers who need logo identification as part of a broader multimodal workflow, such as analyzing product images, reading surrounding text, classifying content, or generating a contextual description of a brand appearance.
Pricing
On Eden AI, OpenAI logo detection starts at $24 per 1,000 files for the default endpoint and GPT-4o. The GPT-4 Turbo endpoint costs $48 per 1,000 files. All listed OpenAI logo detection models are available in the US region.
8. AWS Rekognition
Amazon Rekognition can detect logos through Rekognition Custom Labels, which requires you to train a model using examples of the brands you want to recognize. The model can classify an entire image or return bounding boxes around detected logo instances. This approach gives you control over the supported logo set, but it is different from using a ready-made database of recognized global brands.
It suits teams already working with AWS that need to detect a defined set of company, product, or partner logos.
Key features
- Trains custom computer vision models for logos, objects, scenes, and other business-specific concepts.
- Supports image-level classification and bounding-box object detection.
- Lets you set a minimum confidence threshold when requesting predictions.
- Integrates with AWS services such as Amazon S3 and the wider Rekognition environment.
Limitations
- It does not provide a clearly documented, ready-made catalog for recognizing arbitrary consumer logos. You need training images for the logos relevant to your use case.
- Custom Labels is primarily designed around image training and inference. Native video logo recognition may require extracting video frames and analyzing them as images.
Best for
AWS-based teams that need to recognize a controlled list of logos, including internal brands, product marks, sponsor logos, or industry-specific symbols.
Pricing
Amazon Rekognition Custom Labels costs $1 per training hour and $4 per inference hour for each allocated resource. There is no fixed per-image logo detection price. Your total cost depends on training time, processing speed, the number of parallel resources, and how long the model remains available for inference. Eligible accounts may receive free training and inference allowances or AWS promotional credits.
9. Visua
Visua provides logo and mark detection technology for images and video. It focuses on detecting brand marks in difficult conditions, including altered, partially visible, or visually modified logos. The platform can combine logo detection with visual search, text detection, and object or scene analysis. It primarily suits enterprise monitoring, brand protection, sponsorship measurement, and authentication platforms.
Key features
- Processes both images and video, including real-time and delayed batch workflows.
- Returns information such as the detected brand, logo position, size, prominence, clarity, and time on screen.
- Can combine logo recognition with visual search to find matching or visually similar content.
- Supports workflows involving modified marks, counterfeits, phishing, and unauthorized brand use.
Limitations
- Visua does not publish a complete catalog of supported logos or standardized benchmark results.
- The platform targets enterprise integrations, so it may be less suitable for developers seeking an immediate self-service API with public pricing.
Best for
Brand-monitoring vendors, sponsorship analytics platforms, anti-counterfeit services, and cybersecurity teams that need logo detection as part of a broader visual-analysis workflow.
Pricing
Visua uses custom pricing based on processing volume, required speed, media type, and implementation requirements. The provider notes that real-time processing can cost differently from workloads completed over a longer period.
10. Roboflow
Roboflow is a computer vision platform that lets you create, train, and deploy a custom logo-detection model. Unlike providers with a ready-made catalog of commercial logos, Roboflow generally requires you to collect or select a dataset containing the logos you want to recognize.
A trained object-detection model can return the logo class, confidence score, and bounding box for each result. It suits teams that need control over their training data, supported brands, deployment environment, or model behavior.
Key features
- Supports dataset upload, annotation, augmentation, model training, evaluation, and deployment.
- Can train object-detection models for custom logos, symbols, packaging, or brand marks.
- Supports cloud-hosted inference and deployment through the open-source Roboflow Inference server.
- Can process images and video, including frame-based detection and object-tracking workflows.
Limitations
- Roboflow is not an off-the-shelf logo-recognition database. You usually need to source, label, and maintain your own training dataset.
- Model quality depends heavily on the quantity, diversity, and accuracy of the images and annotations you provide.
Best for
Computer vision teams that need to detect a specific set of logos, including private brands, regional marks, internal symbols, or visual identities not covered by pre-trained APIs.
Pricing
Roboflow offers a free Public plan for open datasets and models. Its Core plan starts at $99 per month when billed monthly or $79 per month when billed annually, with included credits. Additional usage follows a credit-based pricing system, while Enterprise pricing is custom.
How to identify a logo from an image
You can use a logo detection API to find a logo from an image without manually searching through brand databases. The API analyzes the photo, locates visible brand marks, and returns the most likely logo match.
This approach is useful for people searching for a logo by image, identifying an unknown logo from a photo, or processing large collections of product images, social posts, and marketing assets.
If you only need to identify a single logo occasionally, a hosted API is faster than building and training your own model.
Step-by-step: identify a logo using an API
- Get an API key. Create an account with a logo detection provider or a multi-provider platform such as Eden AI. Copy the API key used to authenticate your requests.
- Prepare the image. Use a public image URL or upload the image file, depending on the API. Choose the clearest version available. Small, blurred, rotated, or partially hidden logos can be harder to identify.
- Send the image to the API. Make a request to the logo detection endpoint. Include your API key, the image, and the provider or model you want to test.
- Read the response. A typical response includes the detected brand name, a confidence score, and a bounding box showing where the logo appears in the image.
- Handle uncertain results. Set a confidence threshold for your application and review low-confidence matches manually. You can also compare results from several providers when the logo is unclear.
Code example
The following example shows the general structure of an Eden AI logo detection request. Confirm the endpoint, authentication method, and request parameters against the current Eden AI documentation before publishing.
import requests
response = requests.post(
"https://api.edenai.run/v3/universal-ai",
headers={"Authorization": "Bearer YOUR_EDEN_AI_API_KEY"},
json={
"model": "image/logo_detection/api4ai",
"input": {"file": "https://example.com/image-with-logo.jpg"},
},
)
A normalized response could follow this structure:
# Mock response (shape per Eden AI docs):
mock_response = {
"items": [
{
"description": "Apple Inc.",
"score": 0.8422946,
"bounding_poly": {
"vertices": [
{"x": 635, "y": 562},
{"x": 719, "y": 562},
{"x": 719, "y": 695},
{"x": 635, "y": 695},
]
},
}
]
Logo detection use cases
Logo detection helps you turn brand visibility in images and video into structured data. You can use it to measure exposure, organize content, detect misuse, and automate visual workflows.
Advertising and sponsorship measurement
Brands, agencies, and rights holders use logo detection to measure how often a sponsor appears in event photos, livestreams, social posts, and broadcast footage. The system can identify the brand and record where the logo appears in each frame or image.
This data can support sponsorship reports and help teams compare visibility across campaigns, channels, teams, or events.
Brand monitoring and image-based infringement detection
Brand monitoring often focuses on text mentions, but logos can appear without any written reference to the company. Logo detection helps you find visual mentions across social media, marketplaces, websites, and user-generated content.
It can also support brand infringement detection by flagging images that use a protected logo without permission. A legal or moderation team can then review the context before taking action.
E-commerce and automated tagging
Marketplaces and retailers can use logo recognition to identify brands in product images and apply tags automatically. This can reduce manual catalog work and improve filters, search results, and product categorization.
Logo detection can also help identify incorrect brand labels, unbranded listings that contain a visible logo, or products listed under the wrong manufacturer.
Media, entertainment, and video
Media companies can scan images and video frames to detect logos in films, television, sports coverage, news content, and online clips. This makes it easier to index large media libraries and search for specific brand appearances.
For video workflows, the system can process selected frames or track a detected logo across a sequence. Teams can use the results for content analysis, placement review, or sponsorship reporting.
Retail
Retailers can use logo detection in shelf images, store photos, and customer-submitted pictures. The results can help identify which brands are present, check product placement, and review how products appear in physical locations.
It can also support competitive analysis by showing which brands appear across stores, promotional displays, or merchandising campaigns. The final workflow may combine logo detection with object detection, OCR, or product recognition for more detailed results.
How to choose a logo detection API
The best logo detection API depends on your workload, the types of images or videos you process, and how much control you need over cost and performance. Compare providers using real samples from your own use case rather than relying only on feature lists.
- Accuracy: Test the API on clear logos, small logos, rotated marks, partial logos, crowded scenes, and low-quality images to see how consistently it detects the correct brand.
- Number of logos and brands covered: Check whether the provider can recognize the brands that matter to your market, including regional companies, product sub-brands, and less common logos.
- Image and video support: Some APIs only analyze still images, while others support video files, streams, or frame-by-frame processing. Choose based on whether you need occasional image checks or continuous video analysis.
- Pricing model: Review how the provider bills for images, video minutes, API calls, or processing units. Also check minimum commitments, free tiers, and extra charges for advanced features.
- Latency: Response time matters for live moderation, mobile applications, retail systems, and interactive tools. Batch workloads may tolerate slower processing if the price is lower.
- Ease of integration: Look at the API documentation, authentication method, SDK support, response format, error handling, and webhook options. A clear schema can reduce development and maintenance work.
- Ability to switch providers: Your needs may change as pricing, coverage, or performance evolves. A flexible integration makes it easier to test alternatives and avoid depending on one vendor.
Eden AI lets you compare several logo detection providers through one API without rebuilding each integration.
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