Have several products in one picture but need each one separately? Upload your image and let AI identify individual products and separate them into transparent layers you can reuse.
Choose an image containing two or more products. AI will attempt to identify the separate items and turn them into independent visual layers.
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One product, one layer
The AI is guided to keep each product intact while separating it from neighboring products, props and the background. Product caps, labels, handles and attached components are intended to stay with their original item.
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Private File Handling
Uploaded files are associated with your account and delivered through signed URLs. You can delete completed jobs manually.
Transparent PNG Output
Detailed Layers returns each detected element as its own layer on a transparent background.
See the credit cost in the upload workspace before starting.
What images work best?
Real result
You do not need a separate photo of every item to start working with them independently. See how an image containing multiple electronics products can be separated into reusable product and scene layers.
Headphones, a phone, a laptop, a smartwatch, earbuds, a camera and other products, with their boxes and decorative props, are arranged together in one studio photograph. The products look great as a collection, but you cannot easily move one item without affecting the rest of the image.
AI separates the visible products into individual layers, along with major styling elements and the background. Select the extracted elements to see how the original image is divided into reusable parts.
In this example test, the AI returned 17 layers, including a background layer. Product and prop extraction results vary by image. This is a real AI-generated separation example, so minor visual differences, reconstructed details or alignment adjustments may occur.
Start here
Upload your image and let AI identify individual products, separate them into transparent layers, and make them easier to reuse. No need to manually trace every bottle, box, device or accessory.
Whether you are preparing product listings, building advertisements or organizing images for a design project, start with the photo you already have.
Common problem
Imagine you have a picture showing six products. Now you need a separate image of the second product. Or you want to remove one item and keep the rest. Or your designer asks for individual product PNGs, but all you have is the finished photo.
The products are visible, but they are locked together in one flat image. Separating them manually means selecting edges, handling overlaps, cleaning backgrounds and repeating the process for every item.
With Image to Layers, you can start by separating the image into individual visual elements instead.
Typical problems this helps with:
Turn a single image containing several products into a more flexible set of editing assets.
How it works
1
Choose the photo containing the products you want to separate. You can start with a collection photo, product bundle image, studio arrangement, or another picture where multiple items appear together. No original layered design file is required.
2
The AI examines the visible products and attempts to give each distinct item its own layer. It also identifies supporting props and background elements where possible. You do not need to type the names of all the products.
3
Inspect the separated results, select the products you need, and use the available editing or download options to continue your work. Check the edges, printed labels and object positions before using the extracted products in a final design.
Independent extraction
A regular image treats every visible item as part of one canvas. That is inconvenient when you only need a single product.
For example, you may have a photo containing headphones, a phone, a camera and a laptop, and you want to reuse just the camera in a promotional graphic. Instead of cutting around it manually, the separation attempts to create an independent layer for the camera. The same idea applies to bottles, boxes, jars, accessories and other merchandise.
What you can do with independent layers:
Make a group photograph more useful when you need to work with the products one at a time.
Complete products
When separating a photo, more layers are not always better. You probably do not want a bottle cap, bottle body and printed label to become three unrelated pieces. You want one complete bottle that you can move or reuse.
Image to Layers uses product-oriented instructions intended to preserve each individual item as a complete object.
Examples:
Distinct objects, such as a product and a separate retail box, may be extracted independently when the image allows. The goal is practical product cutouts that are easier to use, not unnecessary fragmentation.
Complex arrangements
In professional product photography, objects often overlap. A jar may sit in front of a bottle. A package may partially cover another item. Several products might share shadows or reflections. These compositions look natural, but they make manual extraction more difficult.
AI can attempt to separate overlapping products and estimate parts that were previously hidden. However, the original photograph does not contain the actual appearance of fully obscured areas. Reconstructed regions are AI-generated approximations, not recovered original pixels.
What to expect:
You can start from a more editable image without assuming that every hidden detail can be recovered perfectly.
Multi-object extraction
Most basic background removers are designed to separate the foreground from the background. If your photo contains five products touching or overlapping, they may still appear together as one cutout. That works when you want the entire group. It does not solve the problem when you need each product independently.
| Background removal | Separate multiple products |
|---|---|
| Best for extracting one subject or one combined group | Designed to identify distinct products |
| Usually provides a foreground cutout | Attempts to create one layer for each product |
| Does not necessarily separate neighboring objects | Can also separate major props and background elements, which helps when you need to work with individual items |
Choose object-level separation when you need the pieces inside the picture, not just the picture without its background.
Any product type
Your products do not have to be skincare bottles. The workflow is intended for photos containing different types of physical products and merchandise.
Separate bottles, jars, tubes and packaged skincare products from collection photos.
Extract devices, headphones, cameras, phones and accessories from group arrangements.
Work with individual items from a gift hamper, subscription box or bundled product photo.
Separate candles, containers, kitchen accessories, decor and other household merchandise.
Try extracting bags, watches, eyewear, footwear and other individual accessories.
Separate packaged items or distinct products from a group arrangement where their boundaries are visible.
Important: skincare and electronics have been tested with this workflow. Results for other categories can vary.
Next design
Once your products are separated, they can become more flexible assets for a range of creative tasks.
Prepare product elements for Shopify store banners, promotional images and product collection layouts.
Use extracted products as a starting point for secondary listing graphics, product comparisons and promotional visuals. Follow each marketplace's content requirements.
Feature selected products from a collection in social posts, advertisements and announcements.
Work with a flattened client photograph even when the original layered source file is unavailable.
Organize separate products into a new arrangement or combine selected items for a different collection image.
Create product-focused graphics using existing photographs instead of rebuilding every asset from scratch.
One photo can become a useful source of independent product images for your next project.
Props too
Sometimes you only need the products. Other times, the objects around them are useful too. Your original photograph might include display stands, flowers, fabric, stones, packaging or other styling elements.
The AI can attempt to identify major props separately so you can keep, move or remove them during editing.
Potential scene elements:
Small decorative details may be grouped with other elements, particularly in very dense scenes. Keep more of the original photograph available for creative editing.
Logos and packaging
A product cutout is only useful when it accurately represents the item you are selling. AI-assisted layer separation can subtly change fine details, even when the overall result looks good. Before using the extracted image in advertising or listings, compare it with the original photograph.
Check these details:
You may notice slight changes to lettering, reflections, shapes or partially hidden parts. For product-critical details, verify the result before publishing. AI separation is an editing aid, not a guarantee of pixel-perfect reproduction.
Know the limits
A photo containing three clearly separated products is different from a tightly packed collection of twenty products and accessories. The AI has a practical output-layer limit, and the result can vary based on scene complexity.
In the tested examples, the model returned 16 foreground layers plus a background layer. Some of those foreground layers represented props rather than products. If an image has many more distinct objects, the model may combine some elements or leave smaller objects attached to the background.
For better results:
The number of products successfully separated depends on the image, not just the number visible in the photograph.
Better results
High-quality images make it easier to distinguish product shapes, packaging edges and small details.
If two products blend into each other, they may be harder to separate reliably.
Motion blur and strong depth-of-field blur can make object boundaries less predictable.
Clear glass, plastic and reflective surfaces may need extra review after separation.
AI cannot reliably restore wording that is too small, obscured or illegible in the original photograph.
A reconstructed image can look convincing while individual layers still contain slight shifts, altered textures or background fragments.
A good source image and a careful review can make the resulting layers much more useful.
Before reusing
The tool works from a flattened photograph. It does not recover the original Photoshop document, original camera layers or hidden source assets. Instead, AI generates a new set of visual layers based on the image.
This makes many editing tasks easier, but results may contain reconstructed details or small visual changes.
Common differences to review:
Use the available tools to inspect the output, then make any necessary adjustments before commercial delivery. The value is a faster starting point for individual product editing, with room for final human review.
Upload an image containing several products, then start the AI separation process. Image to Layers attempts to identify each distinct product and create independent visual layers so you can inspect and reuse the items separately.
The workflow creates separate image layers that can be used with transparency. Use the result workspace to review and download the supported outputs. Check that each required product appears independently before relying on the files.
No. The AI is guided to identify distinct products in the image automatically. You do not have to draw a selection around every object or type out all the product names.
It can attempt to separate touching and partially overlapping products. Heavily overlapping objects are more challenging, and areas hidden behind other products may need AI reconstruction.
You can try, but identical or very similar neighboring products may be harder to distinguish. Clear boundaries and visible spacing can improve the chances of separating them correctly.
The workflow aims to provide independent layers with transparency outside the extracted objects. Complex shadows, glass and partially transparent packaging may require additional review or cleanup.
There is no guaranteed product count. The model has a practical limit on the number of layers it can generate. Our example tests reached 16 foreground layers plus a background, including props as well as products. Crowded images may produce grouped or missing objects.
Yes. The workflow can help by separating multiple products into independent layers, allowing you to select the particular product you need from the generated result.
Yes. Standard background removal often gives you one foreground cutout containing all the products together. This workflow attempts to separate individual products from one another, not just from the background.
The separation instructions prioritize keeping each product intact, including attached caps, lids, handles, labels and other integral components. However, inspect the results to confirm the grouping is correct.
Yes. The workflow has been tested on a photograph containing multiple electronic devices and accessories. Details such as controls, screens, branding and reflective surfaces should still be reviewed after processing.
Yes. The workflow has also been tested on a skincare collection containing bottles, tubes, jars, a facial roller and styling props. Individual products were separated, although the output still required visual review.
You can try separating visible items inside a bundle or gift arrangement. Items that are completely hidden, tightly packed or visually indistinguishable may not be recoverable as independent products.
It aims to preserve visible text and logos, but it cannot guarantee exact reproduction. Small packaging text and fine artwork may be modified during AI processing. Always check critical branding against the original.
They may work, but glass, reflective metal and translucent plastic can be difficult because their appearance depends on the surrounding scene. Inspect edges, reflections and transparency before using the results.
Yes. Downloaded transparent product images can be imported into Photoshop as separate layers. You can download the layers as a ZIP, and a PSD download is available on paid plans.
You can use extracted assets when preparing ecommerce graphics, provided you have the necessary rights and follow each platform's current image requirements. Review image accuracy before publishing commercial listings.
The AI can attempt to separate products from other visual elements, but text overlays and decorations may obscure parts of the product. Hidden details may be reconstructed inaccurately, so careful review is important.
AI-generated layers may involve reconstruction or redrawing, particularly around edges, reflections, overlapping objects and text. Small changes in position, texture or packaging details can occur.
This is a credit-based AI processing tool. The workspace shows the required credit cost before you start a generation. You can review the current pricing and available credits before proceeding.
Best for extracting individual items from an image containing several products. Use this page when the important question is: how do I get each product separately?
Best for rebuilding a product collection or bundle photograph into reusable scene elements for ecommerce layouts.
Best for working with one main product and its surrounding scene.
Best for general-purpose image separation across a wide variety of subjects.
Do not spend your next design session cutting around every item by hand. Upload the photo you already have and turn multiple visible products into separate, reusable image layers. Whether you are preparing a product listing, an advertisement or a new visual layout, start with the individual items you need.
Extract individual productsUpload your image, review the credit cost, and start separating your products.
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