Im trying to combine following two np.arrays into a single array:
prediction_score = [0.99764085 0.26231623 0.07232302] prediction_boxes = [[282.25906 79.13187 420.98575 226.11221 ] [109.91688 94.8121 333.07764 225.87985 ] [340.3894 96.612015 601.4172 231.13196 ]]
The combination array must look like this [[i, pred, boxes],…]:
prediction_boxes = [[1 0.99764085 282.25906 79.13187 420.98575 226.11221 ] [1 0.26231623 109.91688 94.8121 333.07764 225.87985 ] [1 0.07232302 340.3894 96.612015 601.4172 231.13196 ]]
I tried doing it this way, but it unfortunately didn’t work:
import numpy as np i=1 for x in range(len(pred_scores)): np.insert(pred_bboxes[x], 0, pred_scores[x]) np.insert(pred_bboxes[x], 0, i) print(pred_bboxes)
Is there a way to do this? I tried other means but those tries were even worse.
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Answer
Try hstack
:
np.hstack(([[1]]*len(pred_boxes), # classes pred_scores[...,None], # scores pred_boxes) # boxes )