我在jupyterlab中运行了这段代码，使用了facebook的segment-anything：

import cv2
import matplotlib.pyplot as plt
from segment_anything import SamAutomaticMaskGenerator, sam_model_registry
import numpy as np
import gc

def show_anns(anns):
    if len(anns) == 0:
        return
    sorted_anns = sorted(anns, key=(lambda x: x['area']), reverse=True)
    ax = plt.gca()
    ax.set_autoscale_on(False)
    polygons = []
    color = []
    for ann in sorted_anns:
        m = ann['segmentation']
        img = np.ones((m.shape[0], m.shape[1], 3))
        color_mask = np.random.random((1, 3)).tolist()[0]
        for i in range(3):
            img[:,:,i] = color_mask[i]
        ax.imshow(np.dstack((img, m*0.35)))

sam = sam_model_registry["default"](checkpoint="VIT_H SAM Model/sam_vit_h_4b8939.pth")
mask_generator = SamAutomaticMaskGenerator(sam)
image = cv2.imread('Untitled Folder/292282 sample.jpg')
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
sam.to(device='cuda')
masks = mask_generator.generate(image)
print(len(masks))
print(masks[0].keys())
plt.figure(figsize=(20,20))
plt.imshow(image)
show_anns(masks)
plt.axis('off')
plt.show() 
del(masks)
gc.collect()

运行前内存消耗约200 MB，运行完成后内存消耗约3.4GB，即使我关闭笔记本或重新运行此程序，这些内存也不会释放。那么如何解决这个问题呢？