Dataset Card for Dataset Name

  Dataset Summary

This dataset card aims to be a base template for new datasets. It has been generated using this raw template.

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  Dataset Structure





  Data Instances

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  Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/samp3209/logo-dataset.

Dataset Card for "logo-dataset-v4"

This dataset consists of 803 pairs (x,y) (x, y) (x,y), where x x x is the image and y y y is the description of the image.The data have been manually collected and labelled, so the dataset is fully representative and free of rubbish.The logos in the dataset are minimalist, meeting modern design requirements and reflecting the company's industry.

  Disclaimer

This dataset is made available for academic research purposes only. All the… See the full description on the dataset page: https://huggingface.co/datasets/logo-wizard/modern-logo-dataset.

Brands are based on corporate Trademark data which IPqwery aggregates across multiple Intellectual Property (IP) registries, including USPTO, CIPO, EUIPO and WIPO (USA, Canada, Europe). Brand data is updated weekly and can be delivered as a raw data feed, or customized feeds, or one-off reports. Full bibliographic data can be provided for each trademark record; such as filing date, registration date, NICE classification, Trademark name, type, etc. Ownership/entity relationships are mapped, as are stock tickers, ISIN, Crunchbase uuid, and Crunchbase domain. Logo/images are identified in the main record and compiled into a separate data file.

IPqwery's Brand data is available for public or private companies.

The Database Market is Segmented by Database Type (Relational (RDBMS), Nosql, and More), Deployment (Cloud, On-Premsies), Service Model (Database-As-A-Service (DBaaS), License and Maintenance Software), Enterprise (SMEs, Large Enterprises), Workload Type (Transactional (OLTP), Analytical (OLAP), and More), End-User Vertical (BFSI, Retail, and More), and by Geography. The Market Forecasts are Provided in Terms of Value (USD).

The global name logo market is experiencing robust growth, driven by the increasing need for brand identity among startups, small businesses, and large corporations alike. The market's expansion is fueled by the rising popularity of online business platforms and the accessibility of affordable logo design tools. While precise market sizing data is unavailable, considering the presence of prominent players like BrandCrowd, DesignEvo, Wix, and others, and factoring in a conservative Compound Annual Growth Rate (CAGR) of 15% (a reasonable estimate given the digital design market's dynamism), the market size in 2025 can be reasonably estimated to be around $500 million. This figure is likely to increase significantly over the forecast period (2025-2033), reaching potentially $1.5 billion to $2 billion by 2033. Several trends are shaping the market: a strong preference for minimalist designs, increasing demand for customized logos reflecting specific brand values, and a surge in the usage of AI-powered logo design tools which facilitate faster and more efficient creation processes. However, challenges remain, including competition from freelance designers offering bespoke services and the need to continuously innovate to maintain a competitive edge. Furthermore, maintaining brand consistency across diverse platforms and media remains a significant consideration impacting the market. The market is segmented by various factors, including logo type (text-based, icon-based, combination), industry, and pricing models (subscription-based, one-time purchase). Regional variations exist, with North America and Europe currently holding significant market shares, while emerging markets in Asia and Latin America are showing substantial growth potential. The presence of numerous players, ranging from established platforms to niche service providers, creates a highly competitive landscape. Companies are focusing on providing user-friendly platforms, incorporating AI capabilities, offering various customization options, and expanding their service portfolios to secure a larger market share. The continued evolution of design software and the growing trend of branding across numerous digital touchpoints suggest a long-term positive outlook for the name logo market, promising sustained and potentially accelerated growth in the coming years.

Is Logo Viet Nam Co Limited Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

PredictLeads Key Customers Data provides essential business intelligence by analyzing company relationships, uncovering vendor partnerships, client connections, and strategic affiliations through advanced web scraping and logo recognition. This dataset captures business interactions directly from company websites, offering valuable insights into market positioning, competitive landscapes, and growth opportunities.

Use Cases:

✅ Account Profiling – Gain a 360-degree customer view by mapping company relationships and partnerships. ✅ Competitive Intelligence – Track vendor-client connections and business affiliations to identify key industry players. ✅ B2B Lead Targeting – Prioritize leads based on their business relationships, improving sales and marketing efficiency. ✅ CRM Data Enrichment – Enhance company records with detailed key customer data, ensuring data accuracy. ✅ Market Research – Identify emerging trends and industry networks to optimize strategic planning.

Key API Attributes:

• id (string, UUID) – Unique identifier for the company connection.
• category (string) – Type of relationship (e.g., vendor, client, partner).
• source_category (string) – Where the connection was detected (e.g., partner page, case study).
• source_url (string, URL) – Website where the relationship was found.
• individual_source_url (string, URL) – Specific page confirming the connection.
• context (string) – Extracted description of the business relationship (e.g., "Company X - partners with Company Y to enhance payment processing").
• first_seen_at (ISO 8601 date-time) – Date the connection was first detected.
• last_seen_at (ISO 8601 date-time) – Most recent confirmation of the relationship.
• company1 & company2 (objects) – Details of the two connected companies, including:
• - domain (string) – Company website domain.
• - company_name (string) – Official company name.
• - ticker (string, nullable) – Stock ticker, if available.

📌 PredictLeads Key Customers Data is an indispensable tool for B2B sales, marketing, and market intelligence teams, providing actionable relationship insights to drive targeted outreach, competitor tracking, and strategic decision-making.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/connections_dataset

PredictLeads Key Customers Data provides real-time visibility into business relationships, partnerships, and vendor affiliations across industries. Using advanced web scraping and logo recognition technology, this dataset offers a competitive edge for B2B sales, lead scoring, and company data enrichment.

Use Cases: ✅ Lead Scoring – Prioritize leads based on their key customer network and market influence. ✅ Cold Outreach – Personalize outreach by referencing shared customers or partners. ✅ B2B Data Enrichment – Enhance CRM data with business relationship insights. ✅ B2B Sales – Understand company partnerships to craft tailored sales strategies. ✅ Competitive Analysis – Identify companies working with competitors to refine positioning.

Key API Attributes:

• id (string, UUID) – Unique identifier for the key customer relationship.
• category (string) – Type of relationship (e.g., vendor, partner, customer).
• source_url (string, URL) – Web page where the key customer was identified.
• context (string) – Extracted text describing the business relationship.
• first_seen_at (ISO 8601 date-time) – When the key customer was first detected.
• last_seen_at (ISO 8601 date-time) – Most recent detection of the key customer.
• company1 (object) – Primary company in the relationship, including domain and company name.
• company2 (object) – Associated key customer, vendor, or partner details.

PredictLeads Docs: https://docs.predictleads.com/v3/guide/connections_dataset

Context

Detecting logos from brands in images can help with targeted advertising. Try out this technique with a simple image classification task to classify English Premier League Football/Soccer Club Team Logos.

If you love watching soccer and computer vision tasks this is a good beginner dataset for you!

Content

The companion to this dataset is my Top 5 Football Leagues Club Logos Dataset, where I compiled the basic logo images. For this dataset, I just created 1000 augmented images for each of the 20 team logos.

Coming Soon!!! : Once you've trained your models with the images from '.../epl-logos-big/', test out if your models can go on to detect the logos in real world mages found in the '/test/' directory. Explore why this approach works or does not work and what could be changed about the dataset itself.

Summary of variables:

• list of the teams = ['arsenal', 'aston-villa', 'brentford', 'brighton', 'burnley', 'chelsea', 'crystal-palace', 'everton', 'leeds', 'leicester-city', 'liverpool', 'manchester-city', 'manchester-united', 'newcastle', 'norwich', 'southampton', 'tottenham', 'watford', 'west-ham', 'wolves']
• dictionary of the teams and corresponding class number =

Acknowledgements

I do not own the rights to the team logos, but they are publicly available and can be used in this context. It should go without saying, but do not use the logos from this dataset for your own business or commercial endeavors. Perfectly fine to use for this project though!

Inspiration

MNIST digit classifiers are overdone by now. Looking to provide simple image classification datasets here on Kaggle that use different and useful data. Also I love watching EPL - Go Man U!

Lucky Logo Inc Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

AutoTrain Dataset for project: logo-identifier-v3-medium

  Dataset Description

This dataset has been automatically processed by AutoTrain for project logo-identifier-v3-medium.

  Languages

The BCP-47 code for the dataset's language is unk.

  Dataset Structure





  Data Instances

A sample from this dataset looks as follows: [ { "image": "<100x72 RGB PIL image>", "target": 47 }, { "image": "<100x63 RGB PIL image>", "target": 82… See the full description on the dataset page: https://huggingface.co/datasets/fsuarez/autotrain-data-logo-identifier-v3-medium.

AutoTrain Dataset for project: logo-identifier-v2-short

  Dataset Description

This dataset has been automatically processed by AutoTrain for project logo-identifier-v2-short.

  Languages

The BCP-47 code for the dataset's language is unk.

  Dataset Structure





  Data Instances

A sample from this dataset looks as follows: [ { "image": "<100x100 RGB PIL image>", "target": 98 }, { "image": "<100x100 RGB PIL image>", "target": 3… See the full description on the dataset page: https://huggingface.co/datasets/fsuarez/autotrain-data-logo-identifier-v2-short.

Chile Data Center Cooling Market Report Segments the Industry Into by Cooling Technology (Air-Based Cooling, Liquid-Based Cooling), Data Center Type(Hyperscale (Owned and Leased), Colocation and More), and Tier Type(Tier 1 and 2, Tier 3 and More), Component(service, Equipment). The Market Sizes and Forecasts are Provided in Terms of Value (USD Million) for all the Above Segments.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Oracle Corporation offers products and services that address enterprise information technology environments worldwide. Its Oracle cloud software as a service offering include various cloud software applications, including Oracle Fusion cloud enterprise resource planning (ERP), Oracle Fusion cloud enterprise performance management, Oracle Fusion cloud supply chain and manufacturing management, Oracle Fusion cloud human capital management, Oracle Advertising, and NetSuite applications suite, as well as Oracle Fusion Sales, Service, and Marketing. The company also offers cloud-based industry solutions for various industries; Oracle application licenses; and Oracle license support services. In addition, it provides cloud and license business' infrastructure technologies, such as the Oracle Database, an enterprise database; Java, a software development language; and middleware, including development tools and others. The company's cloud and license business' infrastructure technologies also comprise cloud-based compute, storage, and networking capabilities; and Oracle autonomous database, MySQL HeatWave, Internet-of-Things, digital assistant, and blockchain. Further, it provides hardware products and other hardware-related software offerings, including Oracle engineered systems, enterprise servers, storage solutions, industry-specific hardware, virtualization software, operating systems, management software, and related hardware services; and consulting and customer services. The company markets and sells its cloud, license, hardware, support, and services offerings directly to businesses in various industries, government agencies, and educational institutions, as well as through indirect channels. Oracle Corporation was founded in 1977 and is headquartered in Austin, Texas.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Logo Brands Inc Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Moat provides intellectual property data for public and private companies and combines this data with product, litigation, and market data. The data is rolled up to an ultimate parent (and ticker symbol). Global coverage of companies, and all ownership data is fully time-aware.

Logo Advantage Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Automatic Data Processing, Inc. provides cloud-based human capital management solutions worldwide. It operates in two segments, Employer Services and Professional Employer Organization (PEO). The Employer Services segment offers strategic, cloud-based platforms, and human resources (HR) outsourcing solutions. Its offerings include payroll, benefits administration, talent management, HR management, workforce management, insurance, retirement, and compliance services, as well as integrated HCM solutions. The PEO Services segment provides HR outsourcing solutions to small and mid-sized businesses through a co-employment model. This segment offers benefits package, protection and compliance, talent engagement, expertise, comprehensive outsourcing, and recruitment process outsourcing services. The company was founded in 1949 and is headquartered in Roseland, New Jersey.