Thank you guys for all the hard work you do! And making available for free to all of us!
@EvangelosKarajan
Ай бұрын
Great content!
@sonnyson0723
2 ай бұрын
Thanks ALL FOR instruction
@Anton_Sh.
7 ай бұрын
7:10 The IoU is not the amount of overlap between the two boxes, it's "Intersection over Union", so the area of overlap / area of union, its the proportion, whereas the intersection alone is the overlap value.
@yuganshgoyal6348
4 жыл бұрын
1. F1 score is harmonic mean of precision and recall, and just not simply the result of their multiplication. 2. 9:20 you totally failed to clarify things. So what mAP is: a. is it average of AP at different IoUs of a single class b. or average of AP across different classes but then what happened to AP at different IoUs Overall it is informative. But would be better if you can just clarify things a bit more..
@ben6
4 жыл бұрын
I found the same thing on their blog post. Doesn't actually answer the title of the video.
@alejandromarceloproiettian5079
4 жыл бұрын
AP is calculated using a single IoU, as the mean of precisions achieved at each recall level (different detection thresholds). As AP is calculated for each class, mAP (mean average precision) is calculated as the mean value of average precisions. AP and mAP depend on the selected IoU, and are thus called by its IoU (mAP50, mAP75, etc.)
@ankitmagan
3 жыл бұрын
@@alejandromarceloproiettian5079 You mention different detection thresholds. Is this the confidence value that the model outputs?
@VinayVerma982
3 жыл бұрын
@@ankitmagan Confidence Value (confidence score) is the probability of the object present in a particular anchor box. Its mostly coming from the classifier. We are talking about IoU. Its overlap/union ratio between the predicted and ground truth(actual) bounding box that we have in our labelled dataset. We can calculate mAP when we have labelled test dataset and we predict boxes and compare how precise bounding boxes are generated with respect to ground truth boxes.
@brunozana
Ай бұрын
Best video in this topic
@XiaoZhao-d4j
4 ай бұрын
AP (of a single class) is caculated for a fixed IoU, right? Because a P-R value is dependent on confidence and IoU (two factors). By computing the P-R curve, only confidence is changed (IoU is fixed).
@durarara911
2 жыл бұрын
Amazingly explained!
@Roboflow
2 жыл бұрын
Glad it was helpful!
@robertmigliara7827
Жыл бұрын
Nice work. Thanks!
@diogenesia376
Жыл бұрын
Thank you very much
@Roboflow
Жыл бұрын
You welcome 🙏🏻
@Maciek17PL
2 жыл бұрын
What is that plot with confidence as y-axis at 4.18 its super confusing
@nitinbommi1867
2 жыл бұрын
Can I get the link to the paper that introduced mAP?
@kokebdese4787
3 жыл бұрын
Can I get the code to calculate them?
@legohistory
2 жыл бұрын
use tensorflow for that
@abbasalsiweedi9019
Жыл бұрын
@@legohistory isn't calculated directly inside google colab algorithm folders?
@legohistory
Жыл бұрын
@@abbasalsiweedi9019 I do not understand. What do you mean?
Пікірлер: 24