Fixing Warped Buildings: Nano Banana Troubleshooting for Distorted Perspective

When generating architectural scenes or editing photos of cityscapes using Nano Banana, users may occasionally encounter results where buildings appear unnaturally curved, leaning, or melted. This distortion often manifests as vertical lines that should be straight instead bowing inward or outward, or horizontal lines that fail to align with the horizon. The structure might look like it is melting into the ground or twisting like a spiral. This specific symptom indicates that the AI model has struggled to interpret the geometric constraints of the scene, resulting in a loss of structural integrity. While the texture and lighting might remain high-quality, the fundamental geometry fails to mimic real-world physics, making the image look surreal rather than realistic.

Separating Plausible Causes from Known Facts

It is crucial to distinguish between what the tool can do and what might be causing the error. A common misconception is that the software itself is broken or that the version lacks advanced architectural rendering capabilities. However, based on verified product information, Nano Banana supports both text-to-image and image-to-image workflows designed to generate diverse visual content. The tool does not guarantee identity, label, object, or typography preservation, which means complex structural elements are subject to the same probabilistic generation rules as any other visual feature.

The primary cause of distorted perspective is often found in the prompt instructions rather than a system failure. Prompt instructions describe desired outcomes but do not enforce strict geometric laws automatically. If a user requests a "modern skyscraper" without specifying orientation, the AI may prioritize artistic flair over architectural accuracy. Another plausible factor is the input image quality in image-to-image mode; if the source photo already has extreme lens distortion, the AI might amplify these errors unless explicitly corrected. It is important to note that there are no known statistics or dates regarding specific bug fixes for this issue, as the tool relies on general generative principles. Users should avoid assuming the tool will inherently understand spatial relationships without explicit guidance.

Diagnosing the Issue Through Prompt Engineering

To diagnose why your buildings are warping, review the text you entered into the generator. The core issue usually stems from a lack of directional cues. Without specific instructions, the AI treats the scene as a collection of shapes rather than a structured environment. The diagnosis points to missing vanishing point references in the prompt. For example, asking for a "city view" is too vague. The AI needs to know where the eye should focus and how the lines should converge. If the prompt mentions "curved streets" or "twisted towers," the AI will literally follow those instructions, creating the exact distortion you are trying to avoid. Therefore, the problem is rarely the tool's inability to render straight lines, but rather the absence of commands telling it to maintain them.

Fixing Perspective with Strong Vanishing Point Cues

The most effective solution involves refining your prompt to include strong vanishing point cues. You must explicitly state the desired geometric behavior. Instead of simply describing the building, instruct the AI on the alignment of the lines. Use phrases such as "straight vertical lines," "parallel edges," or "strong one-point perspective." By defining the vanishing point, you provide the AI with a mathematical framework to organize the pixels correctly. For instance, a prompt like "a modern office building with straight vertical columns converging at a central vanishing point" gives the model clear boundaries to work within.

If you are using image-to-image mode, ensure the original image does not have severe distortion before uploading. If the source is fine-tuned, adding descriptive keywords about "architectural precision" or "orthogonal projection" can further reinforce the correction. Remember that prompt instructions do not guarantee perfect results every time, but they significantly increase the probability of accurate geometry. You can explore the prompt library available on the platform to see how other users structure their requests for architectural subjects. These examples serve as templates for crafting more precise instructions. Try Nano Banana to experiment with these new phrasing strategies in a live environment.

Verifying Your Results

After adjusting your prompts, regenerate the image to verify the fix. Look specifically for the convergence of lines toward a single point or parallel alignment where appropriate. Check if the vertical lines of windows and walls remain straight from top to bottom. If the distortion persists, try increasing the specificity of the perspective description. Add terms like "symmetrical facade" or "grid-aligned structure." It is also helpful to test different variations of the prompt to see which phrasing yields the most stable geometry. Since the tool does not preserve objects with absolute fidelity, you may need to iterate several times to achieve the desired architectural look. Once the lines appear consistent and the building stands upright without warping, the troubleshooting process is complete. This method ensures that your generated images maintain the structural realism expected in professional architectural visualization.