Representative examples reviewed September 3, 2026 — actual output adapts to your image.
Every generation starts from verified visual facts extracted from your image, then adapts the wording to the model you target. These four worked examples show what that looks like in practice across the most common use cases. Upload your own reference on the image to prompt tool to get a result built from your image, or read how the pipeline works.
Studio product photo
Target model: Midjourney
A matte black insulated water bottle standing on a pale stone pedestal. Soft studio light from the left, light gray seamless background, gentle shadow to the right. Centered, eye-level product shot.
Primary prompt
Matte black insulated water bottle on a pale stone pedestal, centered eye-level product shot, soft studio lighting from the left, gentle shadow falling right, light gray seamless background, subtle metallic rim highlight, minimalist commercial photography, clean reflections --ar 4:5 --style raw
Compact descriptive clauses lead with the subject; the aspect ratio matches the portrait product framing, and no lighting or material claims go beyond what the photo shows.
Travel street photo
Target model: Flux
A red scooter parked on a narrow cobblestone street in Lisbon at golden hour. Tram tracks curve into the background, laundry hangs from a balcony above, long warm shadows cross the frame.
Primary prompt
A red vintage scooter is parked on a narrow cobblestone street in Lisbon during golden hour. Tram tracks curve from the foreground into the soft-focus background, and laundry hangs from a tiled balcony above the scene. Long warm shadows stretch across the street, with the low sun behind the buildings creating a gentle rim light on the scooter's chrome details.
Flux responds to complete natural-language sentences with explicit spatial relationships — foreground tracks, mid-frame scooter, background balcony — instead of comma-separated tag spam.
Character sticker illustration
Target model: Stable Diffusion
A sticker-style illustration of a sleepy orange cat curled on a stack of books. Thick white outline, flat warm colors, tiny steam lines rising from a mug beside the cat.
Primary prompt
sticker illustration, sleepy orange cat curled on a stack of hardcover books, thick white die-cut outline, flat warm color palette, tiny steam lines rising from a mug beside the cat, cozy mood, clean vector shapes, plain background
Negative prompt
photorealistic, gradient shading, cluttered background, extra limbs, text, watermark
Stable Diffusion pipelines benefit from concise comma-separated concepts plus a real negative prompt that excludes the most common failure modes for this style.
Café food photography
Target model: DALL·E
An overhead shot of a matcha latte with tulip latte art and a slice of strawberry shortcake on a white marble café table. A linen napkin and a fork sit at the lower left; soft window daylight from the top.
Primary prompt
Overhead food photograph of a matcha latte with tulip latte art beside a slice of strawberry shortcake with visible cream layers, arranged on a white marble café table. Place a folded linen napkin and a small fork in the lower-left corner. Soft diffused daylight comes from the top of the frame, producing gentle, natural shadows. The composition leaves quiet negative space in the upper right and contains no text.
DALL·E works best with complete art direction: composition, lighting direction, materials, and an explicit instruction about text placement — here, that no text should appear.
The free tier includes daily generations with no account. Your image is prepared in your browser, analyzed in memory, and never stored.