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loss function like has a bug #1988

Description

@rrjia

🐛 Bug

A clear and concise description of what the bug is.

utils/loss.py line108

gain[2:6] = torch.tensor(p[i].shape)[[3, 2, 3, 2]]  # xyxy gain

for yolov5s.yaml
if i=1
p[i].shape = 3,80,80,85
gain[2:6] = [85, 80, 85, 80]

gain[2:6] = torch.tensor(p[i].shape)[[2, 1, 2, 1]]  # xyxy gain

it shoud be [80, 80, 80, 80]

Activity

github-actions commented on Jan 20, 2021

@github-actions
Contributor

👋 Hello @rrjia, thank you for your interest in 🚀 YOLOv5! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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 training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available.

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Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

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rrjia commented on Jan 20, 2021

@rrjia
Author

image

glenn-jocher commented on Jan 20, 2021

@glenn-jocher
Member

@rrjia hi thanks for the bug report and the screenshot! We have updated the loss function recently, creating a new ComputeLoss() class to replace it. Can you verify that you see the same bug in the most recent code please?

You can update your code with git pull, or alternatively you can git clone https://github.com/ultralytics/yolov5 again.

glenn-jocher commented on Jan 20, 2021

@glenn-jocher
Member

@rrjia if I try to reproduce by training with default settings and placing a breakpoint here, everything looks correct:

Screen Shot 2021-01-20 at 9 53 34 AM

rrjia commented on Jan 21, 2021

@rrjia
Author

sorry it's my fault, the model get A list of length 3, i use y[0] input compute_loss function, thank you.

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