Clothes Recognition API

Clothes Recognition API

Unveil the attire within images with the Clothes Recognition API. Seamlessly integrating technology and fashion, this API decodes visuals, delivering a virtual wardrobe analysis. Discover a spectrum of garments and accessories, each accompanied by likelihood scores. Revolutionize image interpretation, from stylish snapshots to e-commerce excellence.

API description

About the API:

The Clothes Recognition API introduces a groundbreaking solution that bridges the gap between imagery and fashion insight. With its advanced image analysis capabilities, this API revolutionizes the way we perceive and interact with visual content.

Designed to cater to a wide range of applications, from personal styling and e-commerce to trend analysis, the Clothes Recognition API empowers developers to extract comprehensive information from images. By simply submitting a picture, the API undertakes a sophisticated process of identification and probability assessment.

Upon analysis, the API generates a detailed inventory of potential clothing items and accessories featured in the image. Each item is accompanied by a probability score, offering a nuanced understanding of its presence. This feature not only facilitates accurate categorization but also presents users with the likelihood of each element being correctly identified.

Behind the scenes, the API employs state-of-the-art machine learning techniques, leveraging deep neural networks that have been meticulously trained on vast datasets encompassing diverse clothing styles, fabrics, and patterns. This ensures a high degree of accuracy and versatility in recognizing items across various cultural and fashion contexts.

The applications of the Clothes Recognition API are far-reaching. Fashion enthusiasts can harness its potential to curate outfits, while e-commerce platforms can enhance user experiences by suggesting related products. Trend analysts and market researchers can gain insights into consumer preferences and emerging fashion patterns.

In essence, the Clothes Recognition API transcends the limitations of conventional image analysis, opening doors to a new realm of possibilities where visuals and fashion seamlessly converge. Its robust performance, scalability, and potential to reshape industries make it an indispensable tool for anyone seeking to unlock the potential of visual content in the world of fashion and beyond.

 

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

 

Pass the image URL that you want to analyze and receive all the possible clothes recognized within the image. 

 

What are the most common use cases of this API?

 

 

  1. Personal Styling Apps: Integrate the API into mobile apps that offer personalized styling recommendations. Users can upload pictures of their outfits, and the API will identify each clothing item and accessory along with their probabilities. The app can then suggest complementary pieces and create stylish ensembles, making the process of getting dressed both fun and efficient.

  2. E-Commerce Platforms: Enhance the shopping experience on e-commerce websites by implementing the API. When users upload images of fashion items they like, the API can identify similar products available for purchase. This enables users to find matching items effortlessly, boosting sales and customer satisfaction.

  3. Wardrobe Management Apps: Create apps that help users organize their wardrobes digitally. Users can upload pictures of their clothes and accessories, and the API can categorize and list them with probabilities. This simplifies inventory management, outfit planning, and packing for trips.

  4. Fashion Trend Analysis: Trend analysts and fashion researchers can utilize the API to gather insights into popular clothing items and styles. By analyzing social media posts, street fashion, and event photos, they can track trends, identify emerging fashion movements, and make data-driven predictions about the next big thing in fashion.

  5. Virtual Fitting Rooms: Integrate the API into virtual fitting room applications used by online clothing retailers. Customers can upload pictures of themselves, and the API can identify their clothing and accessories. This allows the virtual fitting room to accurately overlay virtual garments onto the customer's image, providing a realistic preview of how different items will look.

 

Are there any limitations to your plans?

 

Besides the number of API calls allowed per plan, there are no other limitations. 

API Documentation

Endpoints


Performs actual image analysis and responds with results.

The image must be a regular JPEG or PNG image (with or without transparency).

The size of the image file must be less than 16Mb.



                                                                            
POST https://zylalabs.com/api/2501/clothes+recognition+api/2482/analyze
                                                                            
                                                                        

Analyze - Endpoint Features
Object Description
url [Required]
Test Endpoint

API EXAMPLE RESPONSE

       
                                                                                                        
                                                                                                                                                                                                                            {"results":[{"status":{"code":"ok","message":"Success"},"name":"https://storage.googleapis.com/api4ai-static/samples/fashion-1.jpg","md5":"873e9651b2e744d7310fd650a599838c","width":1500,"height":1000,"entities":[{"kind":"classes","name":"fashion-classes","classes":{"top, t-shirt, sweatshirt":0.8659043312072754,"outwear":0.22291582822799683,"vest":0.048274993896484375,"shorts":0.15788260102272034,"trousers":0.6151089072227478,"skirt":0.05556100606918335,"dress":0.11960658431053162,"glasses":0.20614215731620789,"hat":0.14154693484306335,"headband, head covering, hair accessory":0.06355646252632141,"tie":0.031345516443252563,"watch":0.10718181729316711,"belt":0.29583993554115295,"tights, stockings":0.09592151641845703,"sock":0.09212785959243774,"footwear":0.7198589444160461,"bag, wallet":0.44054579734802246,"scarf":0.06652951240539551}}]}]}
                                                                                                                                                                                                                    
                                                                                                    

Analyze - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/2501/clothes+recognition+api/2482/analyze?url=https://storage.googleapis.com/api4ai-static/samples/fashion-1.jpg' --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 Clothes Recognition 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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The Clothes Recognition API is a software interface that utilizes advanced computer vision techniques and machine learning algorithms to analyze images and identify potential clothing items and accessories present within them, along with associated probabilities.

The API employs deep neural networks that have been trained on vast and diverse datasets of clothing images. These networks learn intricate features and patterns in clothing and accessories, allowing them to make informed predictions about the items' presence in the input image.

The API performs optimally with images that contain well-lit and clear representations of clothing and accessories. Images with cluttered backgrounds, poor lighting, or occlusions may affect the accuracy of the recognition process.

Yes, the API's neural networks are trained on a diverse range of clothing styles from various cultures, enabling it to recognize clothing and accessories across different fashion contexts and global styles.

The API's processing speed depends on the complexity of the input image and the computational resources available. While it can be integrated into real-time systems, the processing time may vary and could range from a few seconds to longer durations for highly detailed images.

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 Service Level
100%
 Response Time
4,048ms

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