Nano Banana 2 Tutorial: Softening Harsh Edge Reflections on Glass Labels

Understanding the Challenge of Glass Label Glare

When photographing products with transparent glass labels, harsh edge reflections often appear as bright, jagged white lines. These artifacts can distract viewers and reduce the perceived quality of the image. The goal is to soften or eliminate these sharp highlights without making the glass look opaque or losing the delicate details of the label design. This tutorial guides you through using Nano Banana 2 to address this specific visual noise.

Nano Banana refers to the AI image generation and editing tool used here. It is not a skincare brand, bottle, jar, or physical subject. Example products discussed are generic and unbranded to focus on the technique rather than specific commercial items. When working with glass, the challenge lies in balancing light removal with the preservation of transparency. You want the glass to still look like glass, not plastic or frosted material.

Step-by-Step Editing Workflow for Edge Glare Removal

To achieve the best results when removing edge glare, follow these structured steps within the Nano Banana 2 interface. This process leverages the text-to-image and image-to-image workflows supported by the platform.

1. Prepare Your Input Image: Upload a clear photo of the glass label where the harsh white edges are visible. Ensure the lighting conditions in the original shot are stable to help the AI understand the context of the reflection.
2. Select the Correct Model: Navigate to the generator settings. For this task, ensure you are using the standard Nano Banana 2 model (Gemini 3.1 Flash Image). Avoid using Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) for this specific workflow. Google documents Nano Banana 2 Lite as focused on speed and cost. It is not optimized for multiple reference inputs or multi-turn sequential editing. Using it for complex edits like glare removal may yield inconsistent results.
3. Craft Your Prompt: Enter a descriptive prompt that explicitly asks for the removal of edge reflections while maintaining transparency. Do not assume the AI will automatically know to preserve the exact typography or label identity without instruction. Prompt instructions describe desired outcomes; they do not guarantee identity, label, object or typography preservation.
4. Generate and Review: Run the generation. If the first result is too soft or alters the label text, refine the prompt or try a second iteration.
5. Iterate if Necessary: If the glare remains, adjust the prompt to be more specific about the "softening" of the white lines rather than just "removing" them. This subtle difference can sometimes yield better texture retention.

Crafting an Effective Prompt for Glare Reduction

Writing a precise prompt is crucial for success. Since the tool does not guarantee identity preservation, your wording must be descriptive yet flexible. Below is an example prompt structure you can adapt. Note that these are examples of how to phrase requests; they do not guarantee a perfect outcome on every image.

Example Prompt: "Edit this image of a transparent glass bottle label. Remove the harsh, jagged white edge reflections caused by direct lighting. Soften the glare into natural ambient light transitions. Preserve the transparency of the glass so it does not look frosted or opaque. Keep the label text and logo intact but allow for slight adjustments if necessary to blend the edges smoothly."

You can copy this text directly into the Nano Banana 2 prompt library or type it manually. Remember that the tool supports text-to-image and image-to-image workflows, so uploading the image alongside this prompt is essential for targeted editing.

How to Judge Results and Fix Common Issues

After generating the image, evaluate the output based on three criteria: glare reduction, transparency retention, and label integrity.

• Glare Reduction: Check if the sharp white lines are gone or significantly softened. They should blend naturally with the background or the rest of the glass surface.
• Transparency Retention: Ensure the glass still looks see-through. If the area looks cloudy or painted over, the prompt was likely too aggressive in asking for "removal" rather than "softening."
• Label Integrity: Verify that the text and logo are recognizable. While the AI strives to keep them, some distortion is possible.

If the results are unsatisfactory, try these fixes:

• Adjust the Prompt: Change "remove" to "diffuse" or "blend." This often yields softer, more realistic transitions.
• Change the Model: If you accidentally used Nano Banana 2 Lite, switch back to the standard Nano Banana 2 model for better control over complex lighting scenarios.
• Refine the Input: If the original photo has extreme contrast, consider adjusting the brightness before uploading, though the AI should handle moderate variations.

For more advanced features or different model options, you can explore the Try Nano Banana page. Always remember that prompt instructions describe desired outcomes; they do not guarantee identity, label, object or typography preservation. By following these steps and understanding the limitations of the models, you can effectively manage edge glare on transparent glass labels.

Google describes Nano Banana 2 as Gemini 3.1 Flash Image, Nano Banana Pro as Gemini 3 Pro Image, and Nano Banana 2 Lite as Gemini 3.1 Flash Lite Image. These are distinct Google image models. Be sure to select the one that matches your needs for precision versus speed.