An Image Recognition System for commerce applications

Facebook is one of data richest companies in the world. Facebook’s Groknet is a state-of-art product recognition system. This model is trained on 7 datasets across several commerce verticals.

Facebook’s Marketplace has became a great platform for selling and buying products across the globe. When user uploads about a product, description of product includes colour, price, location, brand , year of production etc. Users may not feel good when description is missing completely or partially. So, Facebook decided to use image uploaded by user to augment missing information.

Groknet can analyze image and predict :

  1. Object category : “bar stool,” “scarf,” “area rug,” …
  2. Home attributes: object color, material, decor style,
  3. Fashion attributes: style, color, material, sleeve length, …
  4. Vehicle attributes: make, model, external color, decade,
  5. Search queries: text phrases likely used by users to find the product on Marketplace Search,
  6. Image embedding: 256-bit hash used to recognize exact products, find and rank similar products, improve search quality.

Groknet recognizing all products on image

Groknet is trained on human annotations, user-generated tags, and noisy search engine interaction data.

Data Preparation

GrokNet aimed to solve a large number of computer vision tasks. Dataset consists of 89 million Facebook Marketplace images from 7 different datasets. It uses 80 categorical loss functions and 3 embedding losses.

Training data of 89 million images

Object Categories

object categories are from an internal human-annotated dataset of Marketplace images, with one of 566 labels such as “chair”, “bracelet”, and “bicycle” .

Attributes (Fashion, Home, and Vehicles)

Multi label annotations for attributes of fashion, human and vehicles are used in training.

For home products, colour and material are some attributes.

Product Identities (Fashion, Home, and Vehicles)

Different images of same product are going to have same id in dataset.

#image-classification #image-recognition #facebook-algorithm #facebookai #augmentation #algorithms

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An Image Recognition System for commerce applications
Fredy  Larson

Fredy Larson

1593144300

How to convert your e-commerce into a mobile application?

There comes a lot of benefits that bring more advantages to your business. Some of the top advantages of converting your online eCommerce store into a mobile App are given as follows.

  1. Customer engagement
  2. Personalized user experience
  3. Cost-effective marketing
  4. Enhanced conversion
  5. Broader audience
  6. Fast loading and high performance

Before building a customer mCommerce mobile application for your business, you will need to know the important steps or decisions that you need to make on the process. From choosing the right innovative technology to finding the right mobile development company, here is everything you need to know about mCommerce development.

Choosing the right platform and technology for your business application

The success of the business depends largely on the user experience that your application delivers to your customers. It is no secret that mobile applications provide you with the best features and opportunities than anything else. You can provide the best user experience that is exclusively customized to the needs of your users.

If you want to attain the most out of the benefits of mobile application, it is crucial to choose the right technology for your mobile application development. There are two well-known platforms that are android and iOS When you are building a mobile application, you will have to develop 2 native applications that cater to both platforms separately or you can invest in a cross-platform mobile application.

Picking out the perfect eCommerce technology and tools

For a start-up, you can better go for cross-platform applications that are affordable, helps you in saving time and money. Because building native applications are a time-consuming process and also you will need to spend on two different mobile applications for two different platforms. Building native applications can bring you extensive user experience and features but it is expensive at the same time. There is another option that comes in the line. The Progressive Web Application is the technology that can bring all the benefits of mobile applications and also works in a browser as a web application.

You can better talk to our technology solutions experts to find the best solution for your business application.

#enterprise application #advantages of mobile commerce #different players in m commerce #features of m commerce #m commerce examples #m commerce wikipedia #m-commerce development #mobile commerce applications #mobile commerce statistics 2019 #mobile commerce trends

Lane  Sanford

Lane Sanford

1591903440

Preprocessing your images for machine learning (image recognition)

During my studies at JKU there was a task for preprocessing images for a machine learning project. It is necessary to clean the raw images before using them in a learning algorithm, so thats why we create a pre-processing function. I think it can be quite useful for others as well so I want to share a bit of my approach. The file is structured in a way that it is easy to understand and also should have a tutorial-like effect.

#image-recognition #image #image-classification #machine-learning #image-processing

Ruth  Nabimanya

Ruth Nabimanya

1620633584

System Databases in SQL Server

Introduction

In SSMS, we many of may noticed System Databases under the Database Folder. But how many of us knows its purpose?. In this article lets discuss about the System Databases in SQL Server.

System Database

Fig. 1 System Databases

There are five system databases, these databases are created while installing SQL Server.

  • Master
  • Model
  • MSDB
  • Tempdb
  • Resource
Master
  • This database contains all the System level Information in SQL Server. The Information in form of Meta data.
  • Because of this master database, we are able to access the SQL Server (On premise SQL Server)
Model
  • This database is used as a template for new databases.
  • Whenever a new database is created, initially a copy of model database is what created as new database.
MSDB
  • This database is where a service called SQL Server Agent stores its data.
  • SQL server Agent is in charge of automation, which includes entities such as jobs, schedules, and alerts.
TempDB
  • The Tempdb is where SQL Server stores temporary data such as work tables, sort space, row versioning information and etc.
  • User can create their own version of temporary tables and those are stored in Tempdb.
  • But this database is destroyed and recreated every time when we restart the instance of SQL Server.
Resource
  • The resource database is a hidden, read only database that holds the definitions of all system objects.
  • When we query system object in a database, they appear to reside in the sys schema of the local database, but in actually their definitions reside in the resource db.

#sql server #master system database #model system database #msdb system database #sql server system databases #ssms #system database #system databases in sql server #tempdb system database

An Image Recognition System for commerce applications

Facebook is one of data richest companies in the world. Facebook’s Groknet is a state-of-art product recognition system. This model is trained on 7 datasets across several commerce verticals.

Facebook’s Marketplace has became a great platform for selling and buying products across the globe. When user uploads about a product, description of product includes colour, price, location, brand , year of production etc. Users may not feel good when description is missing completely or partially. So, Facebook decided to use image uploaded by user to augment missing information.

Groknet can analyze image and predict :

  1. Object category : “bar stool,” “scarf,” “area rug,” …
  2. Home attributes: object color, material, decor style,
  3. Fashion attributes: style, color, material, sleeve length, …
  4. Vehicle attributes: make, model, external color, decade,
  5. Search queries: text phrases likely used by users to find the product on Marketplace Search,
  6. Image embedding: 256-bit hash used to recognize exact products, find and rank similar products, improve search quality.

Groknet recognizing all products on image

Groknet is trained on human annotations, user-generated tags, and noisy search engine interaction data.

Data Preparation

GrokNet aimed to solve a large number of computer vision tasks. Dataset consists of 89 million Facebook Marketplace images from 7 different datasets. It uses 80 categorical loss functions and 3 embedding losses.

Training data of 89 million images

Object Categories

object categories are from an internal human-annotated dataset of Marketplace images, with one of 566 labels such as “chair”, “bracelet”, and “bicycle” .

Attributes (Fashion, Home, and Vehicles)

Multi label annotations for attributes of fashion, human and vehicles are used in training.

For home products, colour and material are some attributes.

Product Identities (Fashion, Home, and Vehicles)

Different images of same product are going to have same id in dataset.

#image-classification #image-recognition #facebook-algorithm #facebookai #augmentation #algorithms

Roger Max

Roger Max

1613115839

Best Image Annotation Services for Machine Learning AI Companies

Image Annotation with Best Quality
Excellence remains the prime focus of our dedicated team working 24X7. We follow a strict quality process while image annotating and pictures to ensure no compromise with quality at any level. Thereby, enabling our clients to possess unique, secure and high ended data.

Security of Data at Each Level
Maintaining full data security and confidentiality is our priority. The dedicated team ensures no breach of data at any given point. Your data remains safe with us before, during and after delivery of the requisites.

Content Moderation Services
Easily accessible online social platforms are allowing audiences to freely express their feelings and words towards a particular product, company, service or any specific community. Such good or bad content needs to be monitored before it becomes live on your website. Content moderation service protects websites from inappropriate content that may affect the reputation of your company.

#image annotation #image annotation services #image annotation pricing #annotate images #image recognition services #content moderation services