python - 特征提取跟踪

Question

我正在尝试提取特征向量（128 暗淡）以进行深度排序跟踪。我正在使用框架Detectron2。我看到以下用于特征提取的代码：

image = cv2.imread('my_image.jpg')
height, width = image.shape[:2]
image = torch.as_tensor(image.astype("float32").transpose(2, 0, 1))
inputs = [{"image": image, "height": height, "width": width}]
with torch.no_grad():
    images = model.preprocess_image(inputs)  # don't forget to preprocess
    features = model.backbone(images.tensor)  # set of cnn features
    proposals, _ = model.proposal_generator(images, features, None)  # RPN

    features_ = [features[f] for f in model.roi_heads.box_in_features]
    box_features = model.roi_heads.box_pooler(features_, [x.proposal_boxes for x in proposals])
    box_features = model.roi_heads.box_head(box_features)  # features of all 1k candidates
    predictions = model.roi_heads.box_predictor(box_features)
    pred_instances, pred_inds = model.roi_heads.box_predictor.inference(predictions, proposals)
    pred_instances = model.roi_heads.forward_with_given_boxes(features, pred_instances)

    # output boxes, masks, scores, etc
    pred_instances = model._postprocess(pred_instances, inputs, images.image_sizes)  # scale box to orig size
    # features of the proposed boxes
    feats = box_features[pred_inds]

但我不明白如何从这段代码中提取 128 维特征向量。我很乐意在这里得到一点帮助。提前致谢。