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.

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.

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.

Line item details from purchase orders in the accounts payable subledger for Current Fiscal YearYou can view this data on the Boroughs Online Checkbook. https://msb.maps.arcgis.com/apps/opsdashboard/index.html#/12734a1be92a4a999c2349ce9dc13a2b

Cite the source of the dataset as:

List, Johann-Mattis, Thomas Mayer, Anselm Terhalle, and Matthias Urban (2014). CLICS: Database of Cross-Linguistic Colexifications. Marburg: Forschungszentrum Deutscher Sprachatlas (Version 1.0).

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>"… See the full description on the dataset page: https://huggingface.co/datasets/fsuarez/autotrain-data-logo-identifier-v2-short.

Logo-2K+:A Large-Scale Logo Dataset for Scalable Logo Classification The Logo-2K+ dataset contains a diverse range of logo classes from real-world logo images. It contains 167,140 images with 10 root categories and 2,341 leaf categories. The 10 different root categories are: Food, Clothes, Institution, Accessories, Transportation, Electronic, Necessities, Cosmetic, Leisure and Medical.

Dataset

This dataset was created by Amir Sanjani

Released under Database: Open Database, Contents: Database Contents

Contents

0 Active Shipment Data Global Of logo buyers list and Shipment Data Global Of logo importers directory compiled from actual Shipment Data Global import shipments of Of logo.

Dataset

This dataset was created by Jacek Pardyak

Released under Database: Open Database, Contents: Database Contents

Contents

Open Checkbook BR logo in standard colors

22504 Global import shipment records of Logo Mat with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

50px height white Open Checkbook BR logo for used on dark blue areas of site.

This dataset includes the identification and characterisation of sustainability related logos in food products in the EU market (though not limited to the region). The dataset was primarily produced based on the identification of logos present in food products in the Mintel Global New Products Database for the available EU countries (n=24) between January and December 2021. Other logos inventories were also included and duplicated excluded. Online verification for sustainability relevance and logos' characterisation conducted in logo owners' websites.

Logo used for Open Data BR websites where background is dark blue

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

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).

Data item of the type homologous_superfamily from the database cathgene3d with accession G3DSA:1.10.10.1000 and name Type III secretion system virulence factor YopR, core domain

Logo for the City of Austin's Financial Services Department.

1564 Global import shipment records of Logo backpack with prices, volume & current Buyer’s suppliers relationships based on actual Global import trade database.