Hi ALL:
When I first commit , I found this Error as below :
WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap.
Traceback (most recent call last):
File "/tmp/codalab/tmpQewVjR/run/program/evaluate.py", line 89, in <module>
score_task = evaluate_tasks[task](pred, gt, settings[task])
File "/tmp/codalab/tmpQewVjR/run/program/evaluate_tasks.py", line 35, in evaluate_object_detection
ious = bbox_overlaps(bboxes_pred, bboxes_gt)
File "/tmp/codalab/tmpQewVjR/run/program/utils.py", line 99, in bbox_overlaps
bboxes1 = bboxes1.astype(np.float32)
AttributeError: 'list' object has no attribute 'astype'
Then I have Debug the Eval Code , I find if the gt has the class eg: 3 , and the predict do not has this class, then the program will get above error!
So Please Check the Code!
Thanks!
May be you can fix this bug in the Eval Code like this:
In evaluate_tasks.py file , before modify the line 28,29 is like this:
bboxes_pred = pred[i][label_gt] if label_gt in pred[i] else []
bboxes_gt = gt[i][label_gt] if label_gt in gt[i] else []
we can modify it as below:
bboxes_pred = pred[i][label_gt] if label_gt in pred[i] else np.array([])
bboxes_gt = gt[i][label_gt] if label_gt in gt[i] else np.array([])
the this bug will fixed!
GoodLucky!
Posted by: caic-ailab @ April 27, 2022, 12:56 a.m.Dear caic-ailab,
We're sorry that your submission resulted in an error. Thanks for reporting this.
We encountered another error and this will be fixed soon.
Regards,
Saravanabalagi.
Hi all,
This issue has been fixed and you should be able to submit without errors.
Cheers,
Saravanabalagi.
Sorry to trouble you, i have found that the label only has 3 class, but you want 5 class out.
Please Check!
Dear caic-ailab,
Thanks for bringing this to our notice. We’ll get back to you soon. I appreciate your patience.
Regards,
Saravanabalagi.
Dear caic-ailab,
The 2D bounding box annotations for the training set have been updated in the official Woodscape repository to include class 4 and 5 (traffic_light and traffic_sign), which were previously missing due to an error. We kindly request you to re-download the ground truth labels for the training set (the links are provided in Participate > Get Data section).
Regards,
Saravanabalagi.