AI Product Photography Prompts
Studio-quality product photography from a single reference still — without booking a tabletop shoot. These recipes are organized by category (white seamless, lifestyle, flat-lay, hero, packshot) and pair each with the model that handles it best. Multi-anchor wiring is the differentiator: product reference, brand-color script, and scene reference live as separate canvas nodes rather than being stuffed into the prompt. Nano Banana 2 carries product-detail fidelity; Flux Kontext drops the product into new scenes; Imagen 4 and Flux deliver photoreal heroes; Seedream covers the editorial range; GPT Image 2 cleans up.
When to use this prompt
- Producing 40 SKU variants per quarter without a studio shoot.
- Generating PDP photography for an Amazon or Shopify launch.
- Refreshing legacy product photography across new lifestyle scenes.
- Creating brand-color hero placements for a campaign without compositing time.
- Producing flat-lays and macro details to round out a category page.
Required inputs
- A clean product reference still — ideally background-removed and high-resolution.
- A brand-color script (hex codes or a color reference image) wired as a separate anchor.
- Aspect ratio target — 1:1 for ecommerce and Amazon, 4:5 for paid social, 16:9 for hero web.
- Scene reference image when working on lifestyle treatments (counter, vanity, gym, kitchen).
- Optional: typography or label-detail closeup if your packaging has fine type that must stay legible.
Prompt recipes
Hero on white seamless (ecommerce default)
The PDP and Amazon-listing default. Nano Banana 2 holds product detail and label fidelity better than generative-only models.
Referenced product centered on infinite white seamless backdrop, soft front-key plus subtle bounce fill, no harsh shadow, label sharp and legible, photoreal rendering, product fully in frame with clean negative space, 1:1 framing.
Best output for marketplace listings.
Lifestyle scene (in-context)
Drops the product into a real-world scene. Flux Kontext handles edit-aware placement without product distortion.
Referenced product placed on referenced lifestyle scene (e.g., morning kitchen counter), soft daylight from camera left, natural environmental context, locked product detail, gentle depth of field, product remains the focal point, 4:5 framing.
Variations
- Swap kitchen for bathroom vanity, gym floor, or work desk per category.
- Shift daylight to warm tungsten for evening positioning.
Macro material detail
Texture-forward detail shot for skincare, beverages, premium packaging. Pairs with hero on white for a 2-shot category set.
Macro close-up of textured surface of referenced product, soft top light, shallow depth of field, surface detail in sharp focus, surrounding context falls into bokeh, photoreal rendering, 1:1 framing.
Brand-color backdrop hero
High-saturation paid-social hero. Use brand-color script as a separate canvas reference rather than naming hex codes inline.
Referenced product centered on solid brand-color backdrop (color matched to referenced brand-color script), soft front-key plus subtle rim, locked product detail, clean shadow under product, premium editorial mood, 1:1 framing.
Wire your brand-color script in as a reference node alongside the product image.
Lifestyle with talent holding product
Talent-holding-product variant for skincare, beauty, and food categories. Imagen 4 holds photoreal natural light cleanly.
Hands of model holding referenced product at chest height, soft window light from camera left, kitchen or vanity environment matching referenced scene, locked product label and detail, talent partially in frame, photoreal rendering, 4:5 framing.
Top-down flat-lay composition
Flat-lay for category pages, social feeds, and mood boards. Seedream handles editorial composition naturally.
Top-down flat-lay arrangement of referenced product alongside complementary props (e.g., linen cloth, fresh herbs, accessory items), soft northern daylight, no harsh shadow, balanced negative space, locked product detail, 1:1 framing.
Variations
- Substitute prop set per category (skincare, food, fashion, electronics).
Marketplace packshot
Marketplace-compliant packshot for Amazon, eBay, Walmart. Strict no-shadow, white-background output.
Referenced product alone on pure white background, even soft lighting, no shadow, product fully in frame with margin per Amazon listing requirements, label legible, sharp focus across product, 1:1 framing.
Run through GPT Image 2 cleanup if shadow leaks into the white.
Mood-lit editorial hero
Premium hero for fragrance, spirits, electronics. Flux holds high-fidelity rendering with dramatic light.
Referenced product on minimal plinth, dramatic side rim light, deep shadow on opposing side, atmosphere haze, premium editorial mood, locked product detail, soft floor reflection, 16:9 framing.
On-set lifestyle (kitchen / vanity / desk)
On-set lifestyle composition without commissioning a real shoot. Seedream handles editorial range across categories.
Referenced product placed on referenced surface (kitchen counter, bathroom vanity, work desk) within a lived-in environment, soft window daylight, natural props in soft focus around product, locked product detail and label, photoreal rendering, 4:5 framing.
Detail and label cleanup pass
Cleanup pass for label and packaging detail. Run as a final node after a generative model produces the hero composition.
Refine referenced product image — sharpen label typography, clarify edge detail, balance color across surface, remove minor artifacts, retain original composition and lighting, photoreal output.
Use sparingly — it is a polish, not a re-generation.
Martini canvas workflow
Set up the multi-anchor wiring before generating: product reference, brand-color script, and scene reference each live as separate nodes on the canvas. This is the differentiator vs single-prompt tools — the prompt only directs composition and light, while the anchors carry product identity, palette, and environment.
For face-and-label-fidelity work (hero on white, marketplace packshot, brand-color hero), wire the product reference into Nano Banana 2 or Imagen 4. For scene placement (lifestyle, on-set, in-context), wire the product reference plus the scene reference into Flux Kontext — its edit-awareness handles placement without product distortion.
Run a parallel fan-out: hero on white, brand-color backdrop, lifestyle, flat-lay all generate at the same time from the same product anchor. One canvas, four outputs, picked from the strongest variant per category.
Pass the strongest hero through a GPT Image 2 cleanup node when you need label typography or fine packaging detail crisp. Treat this as polish, not re-generation — small artifact cleanup, not composition change.
Chain into the video phase by wiring the chosen product still into a Seedance 2 or Runway Gen-4 video node — see /prompts/video/product-ad-prompts for the motion library. The image deliverable becomes campaign motion on the same canvas.
Variations
White seamless (catalog)
Default ecommerce / marketplace style — clean white, soft front-key, no environmental cues. PDP and Amazon use this by default.
Brand-color hero
High-saturation backdrop matched to brand color script. Paid-social heroes, campaign launches.
Lifestyle (in-context)
Real-world scene — kitchen, bathroom, gym, desk, outdoor. Editorial / lifestyle / brand storytelling.
Flat-lay (top-down)
Overhead arrangement with props. Mood boards, category pages, Pinterest, social feeds.
Macro detail
Close-up texture / material / label. Texture-forward category pages and detail page modules.
Mood-lit editorial
Dramatic rim light, deep shadow, atmosphere. Fragrance, spirits, premium electronics, fashion.
Related features
Related how-tos
Related models
Related blog posts
Related docs
Frequently asked questions
- Why use multi-anchor wiring instead of one big prompt?
- Stuffing product detail, brand color, and scene context into one prompt is how single-tool generators ship — and it is also how palette drifts and label fidelity collapses. Wiring product, color, and scene as separate canvas anchors lets each reference carry its own role; the prompt only directs composition and light. The output holds detail because the references hold detail.
- When do I use Nano Banana 2 vs Flux Kontext?
- Nano Banana 2 for product-detail fidelity — hero on white, marketplace packshots, label-critical work. Flux Kontext for placement-into-scene — lifestyle, in-context, scene swaps where the product needs to integrate naturally with a referenced environment. Use both: Nano Banana for the hero, Flux Kontext for the lifestyle variations.
- How do I keep label typography legible?
- Start with a high-resolution product reference; soft inputs become soft outputs. Use Nano Banana 2 or Imagen 4 for label-critical work rather than purely generative models. Run a GPT Image 2 cleanup pass at the end to sharpen label typography. Watch for label drift on packaging — it is the most common failure mode and worth a manual review before delivery.
- Can I get instant studio quality from one click?
- No, and any tool that promises that is overselling. The chain typically needs an upscale + cleanup pass after the generative step, plus careful multi-anchor wiring upstream. The win is that the chain on Martini is reusable — your second SKU is 4× faster than your first because the canvas template is locked.
- How do I turn the product photo into a video ad?
- Wire the chosen still into a Seedance 2 or Runway Gen-4 video node on the same canvas. The motion library lives at /prompts/video/product-ad-prompts. The deliverable goes from PDP photo to PDP motion to paid-social ad without leaving the canvas.
- Which aspect ratios should I generate?
- 1:1 for ecommerce / marketplace / Amazon. 4:5 for paid social and Pinterest. 16:9 for web hero / YouTube / TV. Generate 1:1 first as the master, then re-frame to other aspect ratios on the canvas with the same anchor stack — much faster than re-generating from scratch.
Try this prompt on Martini
Copy a recipe above, drop it into a node, and run it inside a full canvas workflow.