Intersection Over Union (IoU) | Essentials of Object Detection
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- Опубликовано: 9 сен 2024
- This tutorial explains how to compute the similarity between 2 bounding boxes using Jaccard Index, commonly known as Intersection over Union in the field of object detection.
This is the best series I have watched on explanation of object detection algorithms.
Also, your approach of asking fundamental questions like "Why in this case, a metric of evaluation can't be used as a loss function" and many more such questions you addressed were so insightful. Really grateful for the efforts you've put in here. Thank you. 🙏🙏
So, in-depth and with those visualization it is a grate learning experience
awesome explanation!
Binge watching your videos. Excellent content and excellent teaching. Thank you.
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Great Video !! Thanks.
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Thanks. Really helpful and easy to understand tutorial. you mentioned that this is used to measure similarity between boxes. Can you elaborate how this can be used with geospatial and image capture?
I am not sure if I understand your question. Possible to elaborate and give an example?
@@KapilSachdeva Is it used for compring 2 images and checking the differences/similarity? I am actually after an example in real life.
It is not about comparing the images rather the two bounding boxes in a given image. The metric is used in the field of object detection and is used to compare the ground truth box and the predicted box by the neural network.
is the same understanding can also be put on semantic and instance segmentation ?
You can use the notion of overlap in segmentation as well.
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Sorry. Not sure I understand your comment.