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I tried to load the image and make it inputable to the model.
cracks_guess = []
def check(arr_img):
    print('length->',len(arr_img))
    with torch.no_grad():
        for idx,img in enumerate(arr_img):
            img = torch.tensor(img).type(torch.FloatTensor).cuda()
            img = img.permute(2,0,1)
            img = img.unsqueeze(0)
            #print('shape->',img.shape)
            output = net(img)
            output = torch.sigmoid(output)
            pt = torch.round(output)
            if pt==1:
            #if output > 0.3:
                cracks_guess.append(img)
                print(idx,'output->',output)

is this right way to change the img shape to inputable to model?