ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.

[cskate1997]

(venv) root@cc3180440f4b:/opendr/src/opendr/perception/panoptic_segmentation/efficient_ps/algorithm/EfficientPS# python tools/convert_cityscapes.py ./data_2/ ./data/cityscapes/
Loading Cityscapes from ./data_2/
Converting train ...
0%| | 0/2975 [00:00<?, ?it/s]
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/usr/lib/python3.8/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/usr/lib/python3.8/multiprocessing/pool.py", line 48, in mapstar
return list(map(*args))
File "tools/convert_cityscapes.py", line 163, in call
coco_ann_i = pct.create_annotation_info(
File "/opendr/venv/lib/python3.8/site-packages/pycococreatortools/pycococreatortools.py", line 99, in create_annotation_info
segmentation = binary_mask_to_polygon(binary_mask, tolerance)
File "/opendr/venv/lib/python3.8/site-packages/pycococreatortools/pycococreatortools.py", line 48, in binary_mask_to_polygon
contours = np.subtract(contours, 1)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (2,) + inhomogeneous part.

I am trying to convert my Citscapes dataset to COCO style using pycococreator with following subfolder.

1. gtFine
2. leftImg8bit

Inside gtFine->train-><city_name>->following items
1.aachen_000057_000019_gtFine_color.png
aachen_000057_000019_gtFine_instanceIds.png
aachen_000057_000019_gtFine_labelIds.png
aachen_000057_000019_gtFine_polygons.json

How can I solve the above ValueError issue?

[Abdullah955]

have you able to solve it ?

[cskate1997]

have you able to solve it ?

No, I don’t where problem is with I even tried to change numpy versions, but didn’t worked.
By changing another version of numpy didn’t get above error but got another error.

[yy1443221758]

excuse me，have you able to solve it ?

[yanganlan0310]

I also encountered this problem，this error becourse this line code:

contours = np.subtract(contours, 1)

The previous line of code for this got a list object and this list's length >1，it's original length should have been 1,so，you should keep only one of these elements

[00ffcc]

also encountered this problem
maybe there are more than one polygons?

---

yes, measure.find_contours() returns more than one mask.
you can solve the peoblem by simply using the biggest mask.

contours = measure.find_contours(padded_binary_mask, 0.5)
contours=sorted(contours,key=lambda x: len(x),reverse=True)[0:1]#可能返回多个mask
contours = np.subtract(contours, 1)

[Cai-RS]

also encountered this problem maybe there are more than one polygons?

yes, measure.find_contours() returns more than one mask. you can solve the peoblem by simply using the biggest mask.

contours = measure.find_contours(padded_binary_mask, 0.5)
contours=sorted(contours,key=lambda x: len(x),reverse=True)[0:1]#可能返回多个mask
contours = np.subtract(contours, 1)

可是如果一个物体被遮挡成不相连的两部分，应该是要保留这两部分的mask吧？这种情况有办法解决吗？

[wetrytoease]

also encountered this problem maybe there are more than one polygons?
yes, measure.find_contours() returns more than one mask. you can solve the peoblem by simply using the biggest mask.

contours = measure.find_contours(padded_binary_mask, 0.5)
contours=sorted(contours,key=lambda x: len(x),reverse=True)[0:1]#可能返回多个mask
contours = np.subtract(contours, 1)

可是如果一个物体被遮挡成不相连的两部分，应该是要保留这两部分的mask吧？这种情况有办法解决吗？

我也是这个问题，求助大佬解决了吗？？？