Nano Banana 2 Workflow: Converting Solid Renders to Exploded Views
Creating an exploded view from a standard solid render is a powerful technique for technical documentation, marketing materials, and engineering presentations. This workflow leverages the capabilities of Nano Banana 2 to interpret internal structures and separate components through guided text descriptions rather than direct data extraction. By following this structured process, users can visualize how individual parts fit together within a generic product assembly.
Preparing Your Inputs and Selecting the Right Model
The foundation of a successful conversion lies in selecting the appropriate model and preparing high-quality input assets. For this specific task, which requires interpreting complex spatial relationships and potentially multiple reference points, the choice of engine matters significantly.
Model Selection: According to Google's documentation, Nano Banana 2 operates on the Gemini 3.1 Flash Image model. While Nano Banana 2 Lite (Gemini 3.1 Flash Lite) is optimized for speed and cost, it is explicitly not optimized for multiple reference inputs or multi-turn sequential editing. Therefore, for a robust exploded view workflow that may require iterative refinement, the standard Nano Banana 2 model is the recommended starting point.
Input Requirements: You will need a clear, high-resolution image of your solid product render. The image should ideally show the object from an angle that hints at its depth, though the AI will generate the separation based on your prompt. Ensure the background is clean or neutral to minimize distractions during the generation phase. Do not expect the tool to preserve specific brand labels or typography with guaranteed accuracy; prompt instructions describe desired outcomes but do not guarantee identity preservation.
Crafting the Descriptive Prompt Strategy
Unlike simple filters, generating an exploded view requires a nuanced approach where you guide the AI to "see" inside the object. You must use descriptive text to instruct the model on how to separate layers without losing the structural integrity of the original design.
Prompt Construction: Your prompt should focus on the action of separation and the visibility of internal mechanisms. Since the AI does not have access to CAD files or blueprints, you must describe the intended result vividly.
Example Prompt Structure: "Explode the [product type] by separating the outer casing, revealing the internal circuit board, battery pack, and lens assembly. Maintain realistic lighting and shadows for each floating component. Show the screws and connectors clearly detached from the main body."
It is crucial to remember that these are examples of how to structure your request. The AI interprets these instructions to create a new visual interpretation rather than performing a mechanical disassembly. If the initial output lacks clarity, you can engage in a multi-turn conversation to refine the separation distance or highlight specific internal parts. However, be aware that while Nano Banana 2 supports this interaction, the Lite version does not handle such sequential editing well.
Execution Checkpoints and Iterative Refinement
Once you have entered your image and prompt, the generation process begins. To ensure the best results, follow these checkpoints during the workflow:
- Initial Generation Review: Check if the components appear separated logically. Does the image look like a cohesive exploded diagram, or are the parts just scattered randomly? The goal is a structured layout that implies assembly order.
- Internal Detail Verification: Inspect whether the internal structures mentioned in your prompt are visible. If the AI missed a specific layer, you may need to re-run the generation with more specific descriptors regarding that missing part.
- Lighting and Shadow Consistency: A common issue in generated exploded views is inconsistent lighting across separated parts. Verify that shadows fall naturally as if the pieces were floating in the same environment.
- Iterative Adjustment: If the first attempt is close but imperfect, use the chat interface to ask for adjustments. For instance, "Increase the gap between the top cover and the chassis" or "Make the internal gears more visible." This iterative approach is where the full power of the Nano Banana 2 model shines compared to single-shot generators.
Exporting and Using Your Exploded View
After achieving a satisfactory result, the final step involves exporting the image for your intended use. The generated image can be downloaded directly from the interface. Once saved, you can integrate the file into technical manuals, presentation slides, or e-commerce product pages to enhance user understanding of the product's construction.
Remember that the resulting image is an artistic interpretation based on your prompt and the original input. It serves as a visual aid rather than a precise engineering schematic. For professional applications, always verify critical dimensions against actual product specifications.
To begin this transformation process yourself, visit the official generator page and start uploading your solid renders today. Try Nano Banana
By adhering to this workflow, you can effectively utilize AI to bridge the gap between static product photography and dynamic technical visualization, making complex assemblies easier to understand for your audience.