如果图像已经加载为NumPy数组(形状为(H,W,C)(H, W, C)(H,W,C)),可以通过以下两种方式转换为Tensor: 直接使用ToTensor(): python import numpy as np from torchvision import transforms img_np = np.array(img) # 假设img是PIL.Image对象 img_tensor = transforms.ToTensor()(img_np) 手动转置维度后...
img_PIL = transforms.ToPILImage([mode])(img_tensor) img_tensor = transforms.PILToTenso()(img_PIL)# 不进行 scaleimg_tensor = transforms.ToTensor()(img_PIL)# 默认进行 scale mode的解释 PIL -- opencv img_PIL = Image.open("../datasets/MVTec/bottle/train/good/000.png") img_cv2 = cv2...
return image.to(device, torch.float) # 将image的tensor拷贝一份到device所指向的GPU上,这样可以便于之后运算 basicpath = r'C:\Users\七翅兽\Desktop\【CSDN】Pytorch 图像风格迁移教程代码 逐句详解\images 4 neural-style' # 这个地址换成您自己的文件地址 style_img = image_loader(basicpath + r'\pica...
1、numpy和PIL互转 fromPILimportImageimportnumpy as npimportcv2 img= cv2.imread('image.jpg') np.size(img,0)#0,1,2print(type(img))#numpy to PILpil_img=Image.fromarray(img)print(type(pil_img))#PIL to numpynp_img=np.array(pil_img)print(type(np_img)) 2、tensor(pytorch)和numpy互转 ...
tensor_img = tensor_trans(img)#实现ToTensor的功能,将一个input(PIL Image)转化成tensor print(tensor_img) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 为什么需要tensor数据类型呢? 在使用tensorboard里面常用的add_image时,里面的第二个参数是图片的数据类型,这个数据类型,可以是torch.Tensor, numpy.array, ...
opencv->tensor img = cv.imread('image/000001.jpg') transf = transforms.ToTensor() img_tensor = transf(img) 个人觉得使用opencv转tensor还是比较方便的,但是tensor转opencv图像,可能会遇到一些问题。 tensor->opencv tensor转opencv首先将tensor转为numpy数组,再将numpy转为opencv的mat数据。
将PIL对象转换为Tensor 借助torchvision.transforms 即可很方便地实现这个转换,之后再调整一下对应的维度即可 from torchvision import transforms from PIL import Image img = Image.open('data/cars/img1/0021.jpg') loader = transforms.Compose([ transforms.ToTensor() ]) img_tensor = loader(img) img_tensor...
# numpy img_shape:HxWxC# torch img_shape:CXHXWX=X.transpose((2,0,1))Y=Y.transpose((2,0,1))# convert to tensorX=torch.from_numpy(X)Y=torch.from_numpy(Y)ifself.X_type is not None:X=X.type(self.X_type)ifself.Y_type is not None:Y=Y.type(self.Y_type)returnX,Y ...
plt.subplot(221),plt.imshow(img[:,:,::-1]),plt.title('Original') plt.xticks([]), plt.yticks([]) plt.subplot(222),plt.imshow(dst[:,:,::-1]),plt.title('Averaging') plt.xticks([]), plt.yticks([]) plt.subplot(223),plt.im...
img_name='%s/%d.jpg'%(path_name,num)image=frame[y-10:y+h+10,x-10:x+w+10]cv2.imwrite(img_name,image)num+=1ifnum>(catch_pic_num):#如果超过指定最大保存数量退出循环break#画出矩形框 cv2.rectangle(frame,(x-10,y-10),(x+w+10,y+h+10),color,2)#显示当前捕捉到了多少人脸图片了,...