INNER CODE UNIT · Python

image

Shilin-LU/TF-ICON · scripts/app.py:79

    image = np.array(image).astype(np.float32) / 255.0
    image = image[None].transpose(0, 3, 1, 2)
    image = torch.from_numpy(image)
    
    if pad or seg_map:
        return 2. * image - 1., new_w, new_h, padded_segmentation_map
    
    return 2. * image - 1., w, h 


def load_model_and_get_prompt_embedding(model, scale, device, prompts, inv=False):
           
    if inv:
        inv_emb = model.get_learned_conditioning(prompts, inv)
        c = uc = inv_emb
    else:
        inv_emb = None
        

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