AI photo editing works from a written instruction rather than layers and brushes. Good edits come from naming one change clearly, listing what must stay exactly as it is, and checking the result at full size.
Capabilities reviewed 2026-09-26
Most photo edits in Vizify are semantic: the model regenerates the image following your instruction, which suits background swaps, object removal, relighting, and restyling. A masked edit changes only a marked region and needs a mask image. Extending the canvas to a new aspect ratio is a third operation, reframing.
Use the sharpest, largest original available, as PNG, JPEG, or WebP up to 10 MB. The edit cannot recover detail the source does not contain, and a heavily compressed screenshot gives the model less to preserve.
Say exactly what should be different: "replace the overcast sky with late-afternoon golden light", "remove the trash can on the right of the doorway". One change per request keeps the rest of the photo more stable than a list of five.
Name the protected details: the person's face and hairline, the product's shape and label, the existing text, the shadow under the object. Protected details written into the prompt are the strongest control you have over a semantic edit.
If only one region may change, prepare a mask the same size as the photo that marks that region and attach it with the source. Without a matching mask, Vizify asks for one or performs a semantic edit and tells you the change may reach beyond the area you described.
Compare the edit with the original side by side. Identity, hands, jewelry, product geometry, logos, and small text drift first, and lighting changes can spread across the whole frame.
For a second change, download the edited image and upload it as the new source, then describe only the next change. Vizify does not automatically carry a generated image into a later request.
Replace the office background with a softly blurred city park in late-afternoon light. Keep the person's face, hairline, glasses, clothing, and pose exactly as they are. Match the new background's light direction to the existing light on the face.Why it works: It names the new scene, protects the identity details that drift first, and asks for consistent lighting so the subject does not look pasted in.
Remove the orange traffic cone to the right of the doorway and fill the area with the same brick wall and pavement that surround it. Do not change the door, the window reflections, or the person on the left.Why it works: It says what to remove, what should replace it, and which nearby elements must stay, which limits how much of the scene the model rebuilds.
Clean up this product shot: remove the dust specks and the price sticker on the base, and replace the cluttered desk behind the bottle with a plain light-gray seamless background. Keep the bottle shape, label artwork, cap color, and contact shadow unchanged.Why it works: Product edits fail when the label or silhouette shifts, so those are listed explicitly as protected.
Make this living-room photo look like it was taken on a bright morning: warmer sunlight through the left window, soft shadows on the floor, brighter walls. Keep all furniture, artwork, and the room layout exactly where they are.Why it works: A lighting change touches every pixel, so fixing the furniture and layout in place is what keeps the room recognizable.
Change the jacket from navy to deep forest green, keeping the fabric texture, folds, buttons, and fit. Do not change the person's face, skin tone, hair, or the background.Why it works: A narrow attribute change with texture and fit preserved is one of the most reliable semantic edits.
Vizify’s image-editing capability separates three operations, and knowing which one you are asking for sets the right expectation.
Semantic edits take your photo as a reference and regenerate it following the instruction. They handle background swaps, object removal, relighting, recoloring, and restyling well, and they are what the AI Photo Editor prepares by default. Because the whole image is regenerated, nearby pixels can change, which is why protected details belong in the prompt.
Masked edits change only a region you mark. They need two images: the source photo and a mask of the same dimensions that marks the area to change. Vizify matches the mask to the source by size before running the edit. When no matching mask is attached, it either asks for one or performs a semantic edit and says that the change may not stay inside the region.
Reframing extends the canvas to a new aspect ratio, for example turning a square product shot into a wide banner. It is a recomposition, not a lossless resize, so check the newly generated edges.
You do not have to choose a model to edit a photo; Vizify picks one suited to the change. If you want to steer it: Qwen Image 2.1 is the default direction for a one-image instruction edit and supports masked edits; Nano Banana (Gemini 3.1 Flash Image) is suited to preserving several references at once and to complex cutout edges; Ideogram V3 handles masked edits and typography-led remixes. Qwen2 Image Edit remains available as the earlier single-image editor.
Requests to sharpen, denoise, restore, or upscale are handled by the same generative models. They can produce a cleaner, larger image, but they may invent or simplify texture, faces, and small text. Treat the result as a new rendering of the photo, not a forensic recovery, and keep the original.
No. You describe the change in words instead of working with layers, selections, and brushes. That is faster for many edits, but it cannot promise that untouched areas stay pixel-for-pixel identical.
Name it as a protected detail in the prompt, such as keep the face, hairline, and expression exactly as they are, and make only one change per request. Then compare the face with the original at full size.
Yes, with a masked edit: attach a mask the same size as the photo that marks the region to change. Without a mask, describe the region precisely and expect some change around it.
Yes, but use the Transparent Image Maker rather than a general edit. Not every image model returns real transparency — GPT Image 2 cannot — so that tool asks for PNG alpha on a model that supports it. Check the edges and make sure the background is actually transparent rather than white or a checkerboard pattern.
Nano Banana Image Editing accepts up to eight source images in one request and returns one edited image. The AI Photo Editor takes one source photo at a time.
A semantic edit regenerates the image, and lighting or style changes can spread. List every detail that must stay, keep to one change, and use a mask when the boundary matters.
Download the edited image and upload it again as the new source for the next change. Vizify does not automatically reuse a generated image as the input to a later edit.
Accounts get two image generations or edits in total without Pro or a credit pack. After that, editing needs Vizify Pro or a credit pack.
Upload one photo and describe the retouch you want.
OpenPut a new scene behind the subject while keeping identity and pose.
OpenDescribe an unwanted object and fill the area to match the scene.
OpenFill or replace a region, with a masked edit when a mask is available.
OpenEdit with up to eight source images in one request.
Open