Elevate your AI and machine learning projects with our comprehensive fashion image dataset, carefully curated to meet the needs of cutting-edge applications in e-commerce, product recommendation systems, and fashion trend analysis.

Our fashion product images dataset includes over 111,000+ high-resolution JPG images featuring labeled data for clothing, accessories, styles, and more. These images have been sourced from multiple platforms, ensuring diverse and representative content for your projects.

Why Choose Our Fashion Dataset?

• Extensive Image Collection: Gain access to a vast library of 111K+ fashion images, perfect for training machine learning models with precision.
• Detailed Labels: The dataset includes annotated images for garments, accessories, and various fashion styles to enhance model accuracy.
• Versatile Applications: Ideal for e-commerce platforms, AI-based fashion assistants, trend analysis, and product personalization.
• Quality You Can Trust: Download a sample dataset to evaluate the quality and compatibility before diving into the complete collection.

Whether you're building a product recommendation engine, a virtual stylist, or conducting advanced research in fashion AI, this dataset is your go-to resource.

Download and Explore the Fashion Dataset Today!

Get started now and unlock the potential of your AI projects with our reliable and diverse fashion images dataset. Perfect for professionals and researchers alike.

Description: 👉 Download the dataset here This dataset is specifically designed for the classification of e-commerce products based on their images, forming a critical part of an experimental study aimed at improving product categorization using computer vision techniques. Accurate categorization is essential for e-commerce platforms as it directly influences customer satisfaction, enhances user experience, and optimizes sales by ensuring that products are presented in the correct categories.… See the full description on the dataset page: https://huggingface.co/datasets/gtsaidata/E-commerce-Product-Image-Classification-Dataset.

What’s Included

Introducing the Bengali Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the Bengali language.

Containing a total of 2000 images, this Bengali OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible Bengali text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native Bengali people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Bengali text recognition models.

We're committed to expanding this dataset by continuously adding more images with the assistance of our native Bengali crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the Bengali language. Your journey to enhanced language understanding and processing starts here.

What’s Included

Introducing the Finnish Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the Finnish language.

Containing a total of 2000 images, this Finnish OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible Finnish text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native Finnish people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Finnish text recognition models.

We're committed to expanding this dataset by continuously adding more images with the assistance of our native Finnish crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the Finnish language. Your journey to enhanced language understanding and processing starts here.

So my professor wanted me to do something unique instead of using datasets already available on internet. We planned on doing a retail product recognition and classification and to collect data, we noted down all the big super markets in my city. But my team mates chickened out at the last minute and I had to get the job done. DMart wasn't kind to me when I asked for permission to take pictures of their products(they literally laughed as soon as I turned my back towards exit...how mortifying!) so I went to Modern super market(I'm not kidding, that's the name) and captured all these images with my Mi A2 phone with a lens glass that is broken after I dropped it perhaps fifty times or is it hundred?

And the cherry on the top is that we didn't even use this dataset for our project.

Each product image downloaded and stored in locally and attached local image path to each record.

Total records: 99K+

Images count: 493K+

What’s Included

Introducing the Bahasa Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the Bahasa language.

Containing a total of 2000 images, this Bahasa OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible Bahasa text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native Bahasa people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Bahasa text recognition models.

We're committed to expanding this dataset by continuously adding more images with the assistance of our native Bahasa crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the Bahasa language. Your journey to enhanced language understanding and processing starts here.

Shopping Queries Image Dataset (SQID 🦑): An Image-Enriched ESCI Dataset for Exploring Multimodal Learning in Product Search

  Introduction

The Shopping Queries Image Dataset (SQID) is a dataset that includes image information for over 190,000 products. This dataset is an augmented version of the Amazon Shopping Queries Dataset, which includes a large number of product search queries from real Amazon users, along with a list of up to 40 potentially relevant results and… See the full description on the dataset page: https://huggingface.co/datasets/crossingminds/shopping-queries-image-dataset.

Product recognition is a task that receives continuous attention by the computer vision/deep learning community mainly with the scope of providing robust solutions for automatic checkout supermarkets. One of the main challenges is the lack of images that illustrate in realistic conditions a high number of products. Here the product recognition task is perceived slightly differently compared to the automatic checkout paradigm but the challenges encountered are the same. The setting under which this dataset is captured is with the aim to help individuals with visual impairment in doing their daily grocery in order to increase their autonomy. In particular, we propose a large-scale dataset utilized to tackle the product recognition problem in a supermarket environment. The dataset is characterized by (a) large scale in terms of unique products associated with one or more photos from different viewpoints, (b) rich textual descriptions linked to different levels of annotation and, (c) images acquired both in laboratory conditions and in a realistic supermarket scenario portrayed in various clutter and lighting conditions. A direct comparison with existing datasets of this category demonstrates the significantly higher number of the available unique products, as well as the richness of its annotation enabling different recognition scenarios. Finally, the dataset is also benchmarked using various approaches based both on visual and textual descriptors.

Wirestock's AI/ML Image Training Data, 4.5M Files with Metadata: This data product is a unique offering in the realm of AI/ML training data. What sets it apart is the sheer volume and diversity of the dataset, which includes 4.5 million files spanning across 20 different categories. These categories range from Animals/Wildlife and The Arts to Technology and Transportation, providing a rich and varied dataset for AI/ML applications.

The data is sourced from Wirestock's platform, where creators upload and sell their photos, videos, and AI art online. This means that the data is not only vast but also constantly updated, ensuring a fresh and relevant dataset for your AI/ML needs. The data is collected in a GDPR-compliant manner, ensuring the privacy and rights of the creators are respected.

The primary use-cases for this data product are numerous. It is ideal for training machine learning models for image recognition, improving computer vision algorithms, and enhancing AI applications in various industries such as retail, healthcare, and transportation. The diversity of the dataset also means it can be used for more niche applications, such as training AI to recognize specific objects or scenes.

This data product fits into Wirestock's broader data offering as a key resource for AI/ML training. Wirestock is a platform for creators to sell their work, and this dataset is a collection of that work. It represents the breadth and depth of content available on Wirestock, making it a valuable resource for any company working with AI/ML.

The core benefits of this dataset are its volume, diversity, and quality. With 4.5 million files, it provides a vast resource for AI training. The diversity of the dataset, spanning 20 categories, ensures a wide range of images for training purposes. The quality of the images is also high, as they are sourced from creators selling their work on Wirestock.

In terms of how the data is collected, creators upload their work to Wirestock, where it is then sold on various marketplaces. This means the data is sourced directly from creators, ensuring a diverse and unique dataset. The data includes both the images themselves and associated metadata, providing additional context for each image.

The different image categories included in this dataset are Animals/Wildlife, The Arts, Backgrounds/Textures, Beauty/Fashion, Buildings/Landmarks, Business/Finance, Celebrities, Education, Emotions, Food Drinks, Holidays, Industrial, Interiors, Nature Parks/Outdoor, People, Religion, Science, Signs/Symbols, Sports/Recreation, Technology, Transportation, Vintage, Healthcare/Medical, Objects, and Miscellaneous. This wide range of categories ensures a diverse dataset that can cater to a variety of AI/ML applications.

Myntra is a major Indian fashion e-commerce company. The crawl Feeds team extracted more than 110K+ records along with images for research and analysis purposes.

Total images count: 120K+

Dataset included JSON file and long with images in JPG format.

Clothes image dataset having a product schema which included path of a image file so it helps to gather product related images.

Supplementary Data for Product Recognition using Image Rectification. The dataset provided is part of a bigger dataset currently being worked on in different studies. The complete dataset shall be released later.

What’s Included

Introducing the German Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the German language.

Containing a total of 2000 images, this German OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible German text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native German people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of German text recognition models.

We're committed to expanding this dataset by continuously adding more images with the assistance of our native German crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the German language. Your journey to enhanced language understanding and processing starts here.

Get access to the Walmart Basic Product Details Dataset, which includes essential information on a wide range of products available at Walmart.

This comprehensive dataset features product names, categories, descriptions, prices, and more. Ideal for market analysis, competitive research, and e-commerce applications.

Download now to enhance your data-driven strategies and insights with detailed Walmart product information.

The dataset having basic details of a dataset like title, id, image, price and descripton.

Records count: 2.5 million +

What’s Included

Introducing the Filipino Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the Filipino language.

Containing a total of 2000 images, this Filipino OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible Filipino text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native Filipino people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Filipino text recognition models.

We're committed to expanding this dataset by continuously adding more images with the assistance of our native Filipino crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the Filipino language. Your journey to enhanced language understanding and processing starts here.

SHAPE - SHelf mAnagement Product datasEtSHAPE (SHelf mAnagement Product datasEt) contains ~46K images of ~16K different SKU (Stock Keeping Unit) belonging to 62 different categories, fine-grained labeled with their category and European Article Number (EAN). Category and EAN are anonymized, real values could be released under commercial agreement.Dataset is structured as follow:First level folders are categories (anonymized with numbers 1,2,3...), second level folders are SKU (EANs are anonymized with numbers 1,2,3).Please refer to the original publication for any detail. Also when using the data, please cite the original paper:https://doi.org/10.1016/j.eswa.2024.124635

1) Data Introduction • The Egg Image Dataset is constructed by collecting images of eggs captured in real-world environments, classified based on whether the eggs are damaged or not damaged.

2) Data Utilization (1) Characteristics of the Egg Image Dataset: • It includes images collected from various real-world settings such as kitchens, farms, and markets, making it highly effective for model training and improving data generalization. • The dataset provides a clear distinction between damaged and undamaged eggs, making it suitable for solving problems related to object recognition and quality inspection.

(2) Applications of the Egg Image Dataset: • Development of Object Recognition and Quality Classification Models: It can be used to train AI models to automatically detect and classify eggs based on their damage status. • Utilization in Research and Development (R&D): The dataset can be applied to various R&D projects, including product quality management and the development of automated inspection systems.

Product Label

## Overview

Product Label is a dataset for object detection tasks - it contains Products LjCv annotations for 211 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

1) Data Introduction ? The Food-101 dataset contains subsets of the original Food-101 data, featuring multiple food categories and intended to serve as a richer alternative to classic image datasets like CIFAR-10 or MNIST.

2) Data Utilization (1) Characteristics of the Food-101 Dataset: ? The dataset consists of 49 food categories, with data files indicating the number of images and their respective resolutions. ? Includes both color (RGB) and grayscale images with labels.

(2) Applications of the Food-101 Dataset: ? Food image classification: Useful for developing and evaluating models that can automatically recognize and classify various food items. ? Model interpretability and explainability: Can be used to study which regions or components of food images are most important for classification decisions. ? Advanced food analysis: Provides opportunities to identify new food types as combinations of existing tags or to build detectors for food items in complex scenes.

What’s Included

Introducing the Spanish Product Image Dataset - a diverse and comprehensive collection of images meticulously curated to propel the advancement of text recognition and optical character recognition (OCR) models designed specifically for the Spanish language.

Containing a total of 2000 images, this Spanish OCR dataset offers diverse distribution across different types of front images of Products. In this dataset, you'll find a variety of text that includes product names, taglines, logos, company names, addresses, product content, etc. Images in this dataset showcase distinct fonts, writing formats, colors, designs, and layouts.

To ensure the diversity of the dataset and to build a robust text recognition model we allow limited (less than five) unique images from a single resource. Stringent measures have been taken to exclude any personally identifiable information (PII) and to ensure that in each image a minimum of 80% of space contains visible Spanish text.

Images have been captured under varying lighting conditions – both day and night – along with different capture angles and backgrounds, to build a balanced OCR dataset. The collection features images in portrait and landscape modes.

All these images were captured by native Spanish people to ensure the text quality, avoid toxic content and PII text. We used the latest iOS and Android mobile devices above 5MP cameras to click all these images to maintain the image quality. In this training dataset images are available in both JPEG and HEIC formats.

Along with the image data, you will also receive detailed structured metadata in CSV format. For each image, it includes metadata like image orientation, county, language, and device information. Each image is properly renamed corresponding to the metadata.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Spanish text recognition models.

We're committed to expanding this dataset by continuously adding more images with the assistance of our native Spanish crowd community.

If you require a custom product image OCR dataset tailored to your guidelines or specific device distribution, feel free to contact us. We're equipped to curate specialized data to meet your unique needs.

Furthermore, we can annotate or label the images with bounding box or transcribe the text in the image to align with your specific project requirements using our crowd community.

This Image dataset, created by FutureBeeAI, is now available for commercial use.

Leverage the power of this product image OCR dataset to elevate the training and performance of text recognition, text detection, and optical character recognition models within the realm of the Spanish language. Your journey to enhanced language understanding and processing starts here.