pip install microsoftvision
Input images should be in BGR format of shape (3 x H x W), where H and W are expected to be at least 224. The images have to be loaded in to a range of [0, 1] and then normalized using mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225].
Example script:
import microsoftvision
import torch
# This will load pretrained model
model = microsoftvision.models.resnet50(pretrained=True)
# Load model to CPU memory, interface is the same as torchvision
model = microsoftvision.models.resnet50(pretrained=True, map_location=torch.device('cpu'))
Example of creating image embeddings:
import microsoftvision
from torchvision import transforms
import torch
from PIL import Image
def get_image():
img = cv2.imread('example.jpg', cv2.IMREAD_COLOR)
preprocess = transforms.Compose([
transforms.ToPILImage(),
transforms.Resize(224),
transforms.CenterCrop(224),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
])
return preprocess(img).unsqueeze(0) # Unsqueeze only required when there's 1 image in images batch
model = microsoftvision.models.resnet50(pretrained=True)
features = model(get_image())
print(features.shape)
Should output
...
torch.Size([1, 2048])
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