‘’’
import torchvision
import numpy as np
from PIL import Image
import torch
model = torchvision.models.resnet50(pretrained=True)
k = Image.open(’/p300/data/images/000b7d55b6184b08.png’)
k = np.array(k)
k = np.expand_dims(k, axis=0)
k = torch.Tensor(k)
result = model(k)
‘’’
k is an image whose size is [299,299,3]
And the error is RuntimeError: Given groups=1, weight of size 64 3 7 7, expected input[1, 299, 299, 3] to have 3 channels, but got 299 channels instead.
I already have change the k.shape from [299,299,3] to [1,299,299,3].
How the conv2d recognized the input channels?