Generate custom image samples from text descriptions. Build balanced visual datasets, fill category gaps, and create varied training examples.
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An AI image generator can create synthetic image samples from text descriptions, helping you build or supplement visual datasets for machine learning, classification, or analysis. Describe each sample with consistent formatting, generate variations to capture natural diversity, and review every output to confirm it meets your dataset criteria before inclusion.
Input
A ceramic white mug on a wooden table, natural daylight from the left, minimal shadows, product photography style
Expected output
A clean product photo of a white mug on warm wood grain, soft light from the left side, subtle shadow on the right
Input
A wide-angle view of a dense pine forest with a dirt path running through the middle, overcast sky, summer
Expected output
A forest scene dominated by tall green pine trees, a brown dirt path leading into the distance, greyish sky above
Input
A domestic shorthair orange cat sitting on a red brick windowsill, green ivy leaves around the frame, afternoon light
Expected output
A cat in a seated pose on a brick surface, orange fur visible against green leaves, warm golden lighting
Generate images tailored to your dataset needs by describing exactly what you need in each sample.
Adjust prompts to produce diverse examples within the same category, helping balance your dataset.
Fill gaps in your current dataset with targeted new examples described in plain text.
Describe the desired image.
Choose the available generation settings.
Generate, review, and download a suitable result.
Get consistent and useful results for dataset building.
Copy a structure, then adjust the subject, lighting, camera, and output details for your own result.
A stainless steel water bottle standing upright on a marble countertop, diffused natural light from the right, soft shadow to the left, white background, product photography
Specifies object, material, surface, lighting direction, and photography style, producing consistent product samples suitable for object recognition or e-commerce training datasets.
A suburban street lined with deciduous trees in full autumn color, fallen leaves on the sidewalk, clear blue sky, midday sunlight, wide-angle perspective
Describes scene type, seasonal markers, lighting, and perspective, allowing you to generate varied outdoor scenes for environmental classification datasets.
A golden retriever sitting on green grass in a backyard, tongue out, looking at the camera, natural daylight, shallow depth of field
Combines animal subject, pose, environment, and camera style to produce realistic pet images for animal detection or breed classification datasets.
A modern minimalist living room with a grey sofa, white walls, large window with sheer curtains, wooden coffee table, potted plant on the left, soft natural light
Details room type, furniture, layout, and lighting to generate interior scenes for room classification, style recognition, or furniture detection datasets.
A close-up view of a fresh blueberry muffin on a white ceramic plate, visible texture of muffin top, scattered blueberries around, soft overhead lighting, shallow focus
Focuses on food subject, presentation, texture, and lighting to create food images for culinary classification or visual quality assessment datasets.
A red sedan car photographed from a 45-degree front angle on a grey asphalt surface, overcast daylight, urban background slightly blurred
Standardizes vehicle angle, color, surface, and background for automotive datasets requiring consistent perspective and environmental context.
Match the workflow to the input you have and the result you need before opening the generator.
Input: Isolated objects with controlled lighting, consistent backgrounds, multiple angles
Result: Clean product-style images with clear object visibility
Tool: Text to Image with product photography prompt style
Input: Descriptive environment prompts with location type, season, weather, time of day
Result: Varied outdoor or indoor scenes representing distinct categories
Tool: Text to Image with environmental and lighting descriptors
Input: Variations on existing dataset prompts with adjusted colors, angles, or contexts
Result: Additional samples that increase dataset diversity
Tool: Text to Image with systematic prompt variation
Input: Clear subject descriptions for categories lacking real images
Result: Reference images to guide human annotation or labeling
Tool: Text to Image with precise subject and context descriptions
Power up your creative workflow with our AI-driven tools. Generate stunning videos, create images, and apply custom adjustments - our AI Video Generator and AI Image Generator offer a complete solution for all your creative needs.
Choose the credit package that works best for you.
No hidden fees • Cancel anytime • Unused credits roll over
Perfect for trying out AI creation.
Credits
2,400 credits per year
$59.99/year billed yearly
You save $60 · the equivalent of 6 months free
What's included
Perfect for light creators.
Credits
6,000 credits per year
$119.99/year billed yearly
You save $120 · the equivalent of 6 months free
What's included
Best value for creators.
Credits
14,400 credits per year
$399.99/year billed yearly.
Save $80 compared to monthly
What's included
For video creators and power users.
Credits
60,000 credits per year
$999.99/year billed yearly.
Save $200 compared to monthly
What's included
Questions? Contact us at support@domer.io
Describe the first image for your collection, adjust the settings, and generate a sample to add to your dataset.
