torch 中各種影象格式轉換的實現方法
阿新 • • 發佈:2020-01-09
- PIL:使用python自帶影象處理庫讀取出來的圖片格式
- numpy:使用python-opencv庫讀取出來的圖片格式
- tensor:pytorch中訓練時所採取的向量格式(當然也可以說圖片)
PIL與Tensor相互轉換
import torch from PIL import Image import matplotlib.pyplot as plt # loader使用torchvision中自帶的transforms函式 loader = transforms.Compose([ transforms.ToTensor()]) unloader = transforms.ToPILImage() # 輸入圖片地址 # 返回tensor變數 def image_loader(image_name): image = Image.open(image_name).convert('RGB') image = loader(image).unsqueeze(0) return image.to(device,torch.float) # 輸入PIL格式圖片 # 返回tensor變數 def PIL_to_tensor(image): image = loader(image).unsqueeze(0) return image.to(device,torch.float) # 輸入tensor變數 # 輸出PIL格式圖片 def tensor_to_PIL(tensor): image = tensor.cpu().clone() image = image.squeeze(0) image = unloader(image) return image #直接展示tensor格式圖片 def imshow(tensor,title=None): image = tensor.cpu().clone() # we clone the tensor to not do changes on it image = image.squeeze(0) # remove the fake batch dimension image = unloader(image) plt.imshow(image) if title is not None: plt.title(title) plt.pause(0.001) # pause a bit so that plots are updated #直接儲存tensor格式圖片 def save_image(tensor,**para): dir = 'results' image = tensor.cpu().clone() # we clone the tensor to not do changes on it image = image.squeeze(0) # remove the fake batch dimension image = unloader(image) if not osp.exists(dir): os.makedirs(dir) image.save('results_{}/s{}-c{}-l{}-e{}-sl{:4f}-cl{:4f}.jpg' .format(num,para['style_weight'],para['content_weight'],para['lr'],para['epoch'],para['style_loss'],para['content_loss']))
numpy 與 tensor相互轉換
import cv2 import torch import matplotlib.pyplot as plt def toTensor(img): assert type(img) == np.ndarray,'the img type is {},but ndarry expected'.format(type(img)) img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) img = torch.from_numpy(img.transpose((2,1))) return img.float().div(255).unsqueeze(0) # 255也可以改為256 def tensor_to_np(tensor): img = tensor.mul(255).byte() img = img.cpu().numpy().squeeze(0).transpose((1,2,0)) return img def show_from_cv(img,title=None): img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB) plt.figure() plt.imshow(img) if title is not None: plt.title(title) plt.pause(0.001) def show_from_tensor(tensor,title=None): img = tensor.clone() img = tensor_to_np(img) plt.figure() plt.imshow(img) if title is not None: plt.title(title) plt.pause(0.001)
N張圖片一起轉換.
# 將 N x H x W X C 的numpy格式圖片轉化為相應的tensor格式 def toTensor(img): img = torch.from_numpy(img.transpose((0,3,1,2))) return img.float().div(255).unsqueeze(0)
參考:https://www.jb51.net/article/177291.htm
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