一、OpenCV图像读取
import cv2
image = cv2.imread(image_path) # BGR
# print(image.shape) # [H, W, C]
cv2.imshow("window1", image)
cv2.waitKey(0)
opencv-python cv2.imread()读取的图像类型是np.ndarry类型，通道顺序默认为BGR
opencv存储图像按照BGR通道顺序的历史原因：Why does OpenCV use BGR color format ? | LearnOpenCV #
二、PIL(Pillow)图像读取
from PIL import Image
image = Image.open(image_path) # <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=900x1354 at 0x1736DC84790> for jpg image input
image_np = np.array(image, dtype=np.float32) / 255.0
image_np = cv2.resize(image_np, (200, 200)) # resize
input = torch.from_numpy(image).unsqueeze(0).permute(0, 3, 1, 2)
print(input.size())
用Image.open()读取图像文件后，转为np.ndarray的格式
三、np.numpy与torch.Tensor相互转换
3.1 np.ndarray转torch.tensor
torch.from_numpy()torch.Tensor()
How to Convert NumPy Array to PyTorch Tensor | The Research Scientist Pod
3.2 torch.tensor转np.ndarray
def tocpu(x):
return x.detach().cpu().numpy().copy()
切断梯度-->转为cpu类型的数据-->转numpy-->复制
四、转为base64编码，用于网络传输
import base64
with open("my_image.jpg", "rb") as img_file:
my_string = base64.b64encode(img_file.read())
print(my_string)
