I am in the “Exercise 3 - yolo_non_max_suppression” from hw Autonomous_driving_application_Car_detection. I am not sure I passed this section or not. But some questions here.
Q2. The code below is correct or not? I found out that, I still get the same index (nms_indices) if I use the constant max_boxes=10 directly. Another thing is, I didn’t use the iou_threshold at all (because the hint says the tf version for this hw is not supported). I probably already made some mistakes already?
{code removed by mentor}
thank you!
Yes! It said “All tests passed!”, right? However, there will be other tests when you submit your assignment, so whether it can pass those tests are for you to tell us
I just read it but the hint is talking about “score_threshold” instead of “iou_threshold”. Would you like to try it again first?
Cheers,
Raymond
PS: I am removing the code for you because we can’t share it here.
@rmwkwok
Q1, I put iou_threshold in the function tf.image.non_max_suppression, and nothing happens (at least no error). From the reference, what is this score_threshold ? Is this same as threshold in yolo_filter_boxes(boxes, box_confidence, box_class_probs, threshold = .6) from Exercise 1 - yolo_filter_boxes ?
Q2, for the function tf.image.non_max_suppression , I tried directly using max_boxes = 10 instead of max_boxes_tensor = tf.Variable(max_boxes, dtype='int32') . both give me no error. So, I am not sure which is the correct way.
It is usual that we want to understand how to use a function provided by a package, and tensorflow has very good documentation, so I am suggesting you to try to read through it yourself. You can get yourself the answers of what you have asked - definition of score_threshold, and what is correct to set to max_output_size.
I encourage you to always check out the documentation for functions that you are not familiar with. This is a good practice.
