about the similar result compare

[Usernamezhx]

thanks for you work. I test pair image by the model:imagenet_64bit_0.8734_resnet50.pkl. and get the hamming distance:0 This is my test code:

class CSQ(object):
    def __init__(self):
        self.model_path = 'checkpoint/imagenet_64bit_0.8734_resnet50.pkl'
        self.device = "cuda" if torch.cuda.is_available() else "cpu"
        self.transform = prep.image_test(resize_size=255, crop_size=224)
        self.load_model()

    def load_model(self, ):
        self.model = torch.load(self.model_path)
        self.model = self.model.module
        self.model.to(device=self.device)
        self.model.eval()

    def forward(self, img_path):
        tensor_img = self.transform(Image.open(img_path).convert('RGB')).unsqueeze(0).to(self.device)
        with torch.no_grad():
            out = self.model(tensor_img)

        hash_code = out.cpu().numpy()
        hash_code[hash_code < 0] = -1
        hash_code[hash_code >= 0] = 1

        code_list = ''.join(['1' if item == 1.0 else '0' for item in hash_code[0].tolist()])
        return code_list