Missing dataset when following tutorials

Beginners
20

If it’s done manually it means I wrote my own uhh… what’s the format again for the labels, json? I need to lookup which one of these files are the label.

Ah okay, what we’re trying to do is to do pretrain with the previous labeled dataset so i didn’t have to label it myself right, but even so the labels are not what I expecting like the image are supposed to be representing a river but it only have something like cars or sky. Is that the purpose of the link we’re following?

the details are like this

the code
`panoptic_segmentation = pipeline(“image-segmentation”, “facebook/mask2former-swin-large-cityscapes-panoptic”)
results3 = panoptic_segmentation(image)
results3

results2_river = panoptic_segmentation(image_river)
results2_river
`

the output

[{'score': 0.986528,
  'label': 'car',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.907122,
  'label': 'car',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.976372,
  'label': 'car',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.991359,
  'label': 'fence',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.999967,
  'label': 'vegetation',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.964172,
  'label': 'pole',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.902589,
  'label': 'car',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.999337,
  'label': 'building',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.939224,
  'label': 'car',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.994364,
  'label': 'wall',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.97558,
  'label': 'road',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.973715,
  'label': 'car',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>},
 {'score': 0.999913,
  'label': 'sky',
  'mask': <PIL.Image.Image image mode=L size=1420x1080>}]
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