Autonomous_driving_application_Car_detection with YOLO

For the function Yolo boxes, it tells me my scores shape is wrong and I have no idea why:

scores[2] = 81.324005
boxes[2] = [-3.004828   3.7354143  1.6863731  3.1173077]
classes[2] = 44
scores.shape = (268,)
boxes.shape = (268, 4)
classes.shape = (268,)
AssertionError                            Traceback (most recent call last)
<ipython-input-105-2cab1199ef30> in <module>
     16 assert type(classes) == EagerTensor, "Use tensorflow functions"
---> 18 assert scores.shape == (1789,), "Wrong shape in scores"
     19 assert boxes.shape == (1789, 4), "Wrong shape in boxes"
     20 assert classes.shape == (1789,), "Wrong shape in classes"

AssertionError: Wrong shape in scores

I have commented on each line of code about what I think the line is doing and the reasoning behind it, so if you see wrong logic, please correct me.

My code below:

# mentor edit: code removed to clear the course Honor Code.

Why are you using a fixed value of 60 instead of the “threshold” variable?

You might also look at the order of the operands in computing the box_scores.

I’m laughing at myself, the fixed value of 60 was the issue, it was there previously for debugging but I forgot to take it out.

Thank you so much for spotting my careless mistake

I thought the order of the operands didn’t matter for elementwise broadcasted operations?

If it is elementwise, that is true.