27 lines
900 B
Python
27 lines
900 B
Python
import torch
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import torch.nn.functional as F
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import numpy as np
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from PIL import Image
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def prepare_torch_img(img, size_H, size_W, device="cuda", keep_shape=False):
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# [N, H, W, C] -> [N, C, H, W]
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img_new = img.permute(0, 3, 1, 2).to(device)
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img_new = F.interpolate(img_new, (size_H, size_W), mode="bilinear", align_corners=False).contiguous()
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if keep_shape:
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img_new = img_new.permute(0, 2, 3, 1)
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return img_new
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def torch_img_to_pil_rgba(img, mask):
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"""
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img (torch): [1, H, W, C] or [H, W, C]
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mask (torch): [1, H, W] or [H, W]
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"""
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if len(img.shape) == 4:
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img = img.squeeze(0)
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if len(mask.shape) == 3:
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mask = mask.squeeze(0).unsqueeze(2)
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single_image = torch.cat((img, mask), dim=2).detach().cpu().numpy()
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single_image = Image.fromarray((single_image * 255).astype(np.uint8), mode="RGBA")
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return single_image |