Ultralytics не может создать маску для уже обученного YOLO

from pathlib import Path
import cv2
import numpy as np
from ultralytics import YOLO
 
m = YOLO("models/last_hardhat_200_epochs.pt")
res = m.predict('input_files')
 
# Iterate detection results
for r in res:
    img = np.copy(r.orig_img)
    img_name = Path(r.path).stem
 
    # Iterate each object contour
    for ci, c in enumerate(r):
        label = c.names[c.boxes.cls.tolist().pop()]
        b_mask = np.zeros(img.shape[:2], np.uint8)
 
 
        # Create contour mask
        contour = c.masks.xy.pop().astype(np.int32).reshape(-1, 1, 2)
        _ = cv2.drawContours(b_mask, [contour], -1, (255, 255, 255), cv2.FILLED)
 
        # Choose one:
        # OPTION-1: Isolate object with black background
        mask3ch = cv2.cvtColor(b_mask, cv2.COLOR_GRAY2BGR)
        isolated = cv2.bitwise_and(mask3ch, img)
 
        # OPTIONAL: detection crop (from either OPT1 or OPT2)
        x1, y1, x2, y2 = c.boxes.xyxy.cpu().numpy().squeeze().astype(np.int32)
        iso_crop = isolated[y1:y2, x1:x2]
 
        cv2.imwrite('output_mask\\{}.png'.format(img_name), isolated)

Traceback (most recent call last):
  File "*адрес до проги*\hard-hat-detection\Mask.py", line 22, in <module>
    contour = c.masks.xy.pop().astype(np.int32).reshape(-1, 1, 2)
              ^^^^^^^^^^
AttributeError: 'NoneType' object has no attribute 'xy'

from ultralytics import YOLO
 
model = YOLO('models/last_hardhat_200_epochs.pt')
r = model.val(data="training/datasets/helmet-tracking-2/data.yaml")
 
# Print metrics
print(r.box.map)  # mAP50-95
print(r.box.map50)  # mAP50
print(r.box.mp)  # mean precision
print(r.box.mr)  # mean recall