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Hi,
I'm not understand why you set all instance id to 1, cleaned_db_instance_annotation = np.stack(cleaned_db_instance_annotation, axis=2) instance_annotation = cleaned_db_instance_annotation.copy() instance_annotation[instance_annotation != 0] = 1
The text was updated successfully, but these errors were encountered:
instance_annotation is a numpy array of shape (image_height, image_width, number_of_instances) and stores instance annotations as a one-hot vector at each channel. semantic_annotation is a numpy array of shape (image_height, image_width) and stores semantic class indexes.
cleaned_db_instance_annotation at line 149 is a numpy array of shape (image_height, image_width, number_of_instances) and each channel stores instance annotations with their semantic class index.
Therefore, I converted cleaned_db_instance_annotation to one-hot instance_annotation at line 153.
Also, I did not experiment with cityscapes dataset yet. There may be bugs in dataset creation procedure.
Hi,
I'm not understand why you set all instance id to 1,
cleaned_db_instance_annotation = np.stack(cleaned_db_instance_annotation, axis=2) instance_annotation = cleaned_db_instance_annotation.copy() instance_annotation[instance_annotation != 0] = 1
The text was updated successfully, but these errors were encountered: