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Home > All Category Datasets > LLM Datasets > 50,000 Image Editing Datasets – Object Removal, Addition & Modification Dataset for AI Training

50,000 Image Editing Datasets – Object Removal, Addition & Modification Dataset for AI Training

image editing dataset

image synthesis data

object removal dataset

object addition data

AI image generation dataset

virtual scene dataset

annotated image editing data

inpainting dataset

AI training data for image manipulation

generative image dataset

50,000 Sets - Image Editing Dataset includes high-quality image pairs and annotations for object removal, addition, modification, and replacement. Editing targets span people, animals, products, plants, and landscapes across diverse real-world scenes. Each set includes clearly labeled annotations marking the regions and changes required based on editing instructions. This dataset is ideal for tasks such as image synthesis, AI-based photo editing, virtual scene generation, data augmentation, inpainting, and training image manipulation models. All data has been quality tested and complies with global privacy standards, including GDPR, CCPA, and PIPL.

This is a paid datasets for commercial use, research purpose and more. Licensed ready made datasets help jump-start AI projects.

Specifications

Specifications

Data size

50,000 sets

Object types

person, animals, products, plants, landscapes, etc.

Editing types

object Removal, object Addition, object Modification, object Replacement

Resolution

no less than 1024*1024

Data parameters

image formats include .jpg, .jpeg, .png, and other common formats; editing text format is .txt

Annotation content

according to editing instructions, perform cropping and removal of targets in the image, as well as addition, modification, and replacement of targets

Accuracy rate

the edited image data must comply with the data requirements, with no significant mismatches with the original image; the accuracy rate must not be lower than 95%. The mask edges should be within a 5-

Sample

Sample

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