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data about IoU #1401
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Hello @wanterlim, thank you for your interest in our work! Please visit our Custom Training Tutorial to get started, and see our Jupyter Notebook If this is a bug report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom model or data training question, please note Ultralytics does not provide free personal support. As a leader in vision ML and AI, we do offer professional consulting, from simple expert advice up to delivery of fully customized, end-to-end production solutions for our clients, such as:
For more information please visit https://www.ultralytics.com. |
Regression loss is the first column. Regression metric is CIoU. |
This is CIoU loss. |
So, where can i find the Regression metric? Sorry, I'm still confused. |
utils/loss.py compute_loss() |
@wanterlim loss.py is not a runnable file, it has functions used for loss computation. The function that computes CIoU between pairs of boxes is here: Lines 188 to 231 in 2026d4c
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Can you give some code to save or dispay my IoU? Do i need to retrain my dataset or using my best_weights? I really apreciate your helps |
This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
If you find work around, would you post it? i am also finding how to get IOU |
Is it not possible to get the IoU metric somehow? |
@JakobStadlhuber I don't know what you're asking |
I mean we get as a result of the training process for example the mAP@0.5 or the recall... but it would be release helpful to get the IoU to compare it to results of for example papers. |
@JakobStadlhuber IoU is not an output, IoU threshold is an input, i.e.: python val.py --iou_thres 0.6 See val.py argparser for details: Lines 318 to 347 in 6445a81
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I am also trying to know this. Have you got any clarity about Iou mentioned in papers.? @JakobStadlhuber |
If i understand your question right, I tried to implement a simple script to show IoU score on each bounding box for my test data, here's the code. the output is very similar to original val.py output but extended with IOU score for each bounding box. I didn't test on it large data, it may be very slow or something may break. Here's an example of what the output looks like: |
@CatB1t could you confirm a few things about your code which you linked to calculate the IoU of predicted and ground-truth bounding boxes?
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❔Question
I'm currently working on object detection using yolov. I did training on my model, but i can't find the IoU. Is it the Box val that replaces the the IoU now?
![results](https://user-images.githubusercontent.com/63143827/99178985-99b8fd00-274b-11eb-830a-c9d5aa20184a.png)
Here's my training results
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Additional context
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