generate_hyper3d_model_via_images
Convert images into 3D models with built-in materials using Hyper3D technology. Import the generated, normalized-size asset into Blender for further editing and scaling.
Instructions
Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender. The 3D asset has built-in materials. The generated model has a normalized size, so re-scaling after generation can be useful.
Parameters:
input_image_paths: The absolute paths of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in MAIN_SITE mode.
input_image_urls: The URLs of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in FAL_AI mode.
bbox_condition: Optional. If given, it has to be a list of ints of length 3. Controls the ratio between [Length, Width, Height] of the model.
Only one of {input_image_paths, input_image_urls} should be given at a time, depending on the Hyper3D Rodin's current mode. Returns a message indicating success or failure.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| bbox_condition | No | ||
| input_image_paths | No | ||
| input_image_urls | No |
Implementation Reference
- src/blender_mcp/server.py:770-825 (handler)Full handler function for 'generate_hyper3d_model_via_images' tool, including decorators for registration and telemetry. Processes input image paths or URLs, encodes images if needed, normalizes bbox_condition, sends 'create_rodin_job' command to Blender addon via socket, and returns JSON with task details or error.@telemetry_tool("generate_hyper3d_model_via_images") @mcp.tool() def generate_hyper3d_model_via_images( ctx: Context, input_image_paths: list[str]=None, input_image_urls: list[str]=None, bbox_condition: list[float]=None ) -> str: """ Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender. The 3D asset has built-in materials. The generated model has a normalized size, so re-scaling after generation can be useful. Parameters: - input_image_paths: The **absolute** paths of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in MAIN_SITE mode. - input_image_urls: The URLs of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in FAL_AI mode. - bbox_condition: Optional. If given, it has to be a list of ints of length 3. Controls the ratio between [Length, Width, Height] of the model. Only one of {input_image_paths, input_image_urls} should be given at a time, depending on the Hyper3D Rodin's current mode. Returns a message indicating success or failure. """ if input_image_paths is not None and input_image_urls is not None: return f"Error: Conflict parameters given!" if input_image_paths is None and input_image_urls is None: return f"Error: No image given!" if input_image_paths is not None: if not all(os.path.exists(i) for i in input_image_paths): return "Error: not all image paths are valid!" images = [] for path in input_image_paths: with open(path, "rb") as f: images.append( (Path(path).suffix, base64.b64encode(f.read()).decode("ascii")) ) elif input_image_urls is not None: if not all(urlparse(i) for i in input_image_paths): return "Error: not all image URLs are valid!" images = input_image_urls.copy() try: blender = get_blender_connection() result = blender.send_command("create_rodin_job", { "text_prompt": None, "images": images, "bbox_condition": _process_bbox(bbox_condition), }) succeed = result.get("submit_time", False) if succeed: return json.dumps({ "task_uuid": result["uuid"], "subscription_key": result["jobs"]["subscription_key"], }) else: return json.dumps(result) except Exception as e: logger.error(f"Error generating Hyper3D task: {str(e)}") return f"Error generating Hyper3D task: {str(e)}"
- src/blender_mcp/server.py:724-731 (helper)Helper function used by the tool to process and normalize the bbox_condition parameter into a list of integers representing relative dimensions.def _process_bbox(original_bbox: list[float] | list[int] | None) -> list[int] | None: if original_bbox is None: return None if all(isinstance(i, int) for i in original_bbox): return original_bbox if any(i<=0 for i in original_bbox): raise ValueError("Incorrect number range: bbox must be bigger than zero!") return [int(float(i) / max(original_bbox) * 100) for i in original_bbox] if original_bbox else None
- src/blender_mcp/server.py:778-790 (schema)Tool schema and parameter descriptions defined in the docstring, used by MCP framework for input validation and tool description.""" Generate 3D asset using Hyper3D by giving images of the wanted asset, and import the generated asset into Blender. The 3D asset has built-in materials. The generated model has a normalized size, so re-scaling after generation can be useful. Parameters: - input_image_paths: The **absolute** paths of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in MAIN_SITE mode. - input_image_urls: The URLs of input images. Even if only one image is provided, wrap it into a list. Required if Hyper3D Rodin in FAL_AI mode. - bbox_condition: Optional. If given, it has to be a list of ints of length 3. Controls the ratio between [Length, Width, Height] of the model. Only one of {input_image_paths, input_image_urls} should be given at a time, depending on the Hyper3D Rodin's current mode. Returns a message indicating success or failure. """
- src/blender_mcp/server.py:770-771 (registration)Decorators registering the function as an MCP tool and adding telemetry.@telemetry_tool("generate_hyper3d_model_via_images") @mcp.tool()