prajwalkothwal/ai-generated-ecommerce-images

AI-Generated E-Commerce Images

Overview

This dataset contains 6,031 AI-generated images depicting common e-commerce after-sales scenarios across 12 categories. The dataset also ships with companion annotations (annotations_ai.jsonl) describing each image in chat-completion format.

Dataset Structure

Category	Description
damaged_electronics	Damaged electronics (keyboards, laptops, headphones, etc.)
damaged_phone_screen	Smartphones with cracked or broken screens
damaged_product	General products with surface damage or breakage
fake_logistics_screenshot	Logistics / tracking page screenshots
fragile_broken	Broken fragile items (ceramics, glassware, decor)
measurement_mismatch	Apparel / footwear photographed alongside rulers
missing_parts	Product kits with missing components
package_damage	Damaged shipping packages
quality_issue	Apparel with visible quality defects
skin_allergy	Skin reactions next to accessories
supplement_spill	Spilled or leaked supplement / liquid products
wrong_item	Side-by-side comparisons of differing items

Data Source

Images were generated using:

• Google Gemini (gemini-3.1-flash-image-portrait)
• OpenAI gpt-image-2

No real user photos or personally identifiable information are included.

Annotations

annotations_ai.jsonl contains 6,031 entries (one per image) in OpenAI chat-completion format. Image paths inside the JSONL are relative to the dataset root and match the on-disk layout (e.g. damaged_electronics/00003.png).

License

CC0 1.0 Universal (Creative Commons Zero)

To the extent possible under law, the creator waives all copyright and related rights to this dataset via CC0. Where copyright does not exist (e.g., purely AI-generated works), this dataset is dedicated to the Public Domain.

See CC0 1.0 for details.

Creator

Martin (JoyCN)