ShapEImg2ImgPipeline  
Pipeline for generating latent representation of a 3D asset and rendering with the NeRF method from an image.  
This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods
implemented for all pipelines (downloading, saving, running on a particular device, etc.).  
Args:
prior ([`PriorTransformer`]):
The canonical unCLIP prior to approximate the image embedding from the text embedding.
image_encoder ([`~transformers.CLIPVisionModel`]):
Frozen image-encoder.
image_processor ([`~transformers.CLIPImageProcessor`]):
A `CLIPImageProcessor` to process images.
scheduler ([`HeunDiscreteScheduler`]):
A scheduler to be used in combination with the `prior` model to generate image embedding.
shap_e_renderer ([`ShapERenderer`]):
Shap-E renderer projects the generated latents into parameters of a MLP to create 3D objects with the NeRF
rendering method.  
- all
- __call__
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/shap_e.md