Please update vyolov5.6.2 to support numpy1.20 or higher.

[FN4321]

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• I have searched the YOLOv5 issues and found no similar bug report.

YOLOv5 Component

Training

Bug

### Bug details

I am training a yolov5.6.2 model with google colab.
At that time, an error occurred in the attached image.

The contents are "AttributeError: module 'numpy' has no attribute 'int'." in the directory "/content/drive/MyDrive/ncom-pj/myfolder/code_main_valid7/yolov5/utils/dataloaders.py".
The error is that the method int is not applied to numpy.
This is happening in the content of the file, so I would appreciate it if you could fix it.

Environment

YOLOv5 🚀 v6.2-0-gd3ea0df8 Python-3.10.12 torch-2.2.1+cu121 CUDA:0 (Tesla T4, 15102MiB)
Setup complete ✅ (8 CPUs, 51.0 GB RAM, 29.0/201.2 GB disk)

Minimal Reproducible Example

１
!git clone https://github.com/ultralytics/yolov5.git -b v6.2
２
!pip install -qr yolov5/requirements.txt
３
%cd yolov5
４

import utils
display = utils.notebook_init()

５ ← Error location
!python train.py --img 416 --batch 16 --epochs 1 --weights yolov5s.pt --data data/data.yaml --cfg models/yolov5s.yaml --patience 50

Additional

Before code 2, I installed numpy==1.19.5, which supports numpy.int(). However, it was automatically updated during training.
Also, with the git clone !git clone https://github.com/ultralytics/yolov5.git, I was able to successfully training and predicting.
If you like, configure the model with !git clone https://github.com/ultralytics/yolov5.git -b v6.2 and !git clone https://github.com/ultralytics/yolov5.git I would be happy if I knew if it didn't change.

Are you willing to submit a PR?

• Yes I'd like to help by submitting a PR!

[github-actions]

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Requirements

Python>=3.8.0 with all requirements.txt installed including PyTorch>=1.8. To get started:

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[glenn-jocher]

Thank you for the detailed report! 👍

It seems you've encountered a compatibility issue with numpy versions. The numpy.int attribute error is known to occur with numpy 1.20 and above due to deprecation of certain aliases for Python built-in types.

To prevent numpy from automatically updating, you can try pinning its version right after installing YOLOv5's requirements. Here's a modified step to include after your step 2:

!pip install numpy==1.19.5

This ensures numpy remains at version 1.19.5 throughout your training session. If you still encounter issues, consider creating a virtual environment specifically for your YOLOv5 project to better manage dependency versions.

We appreciate your willingness to submit a PR. Enhancements for compatibility with newer numpy versions can certainly benefit the community. For further guidance on contributing, refer to our documentation at https://docs.ultralytics.com/yolov5/.

Your collaboration helps us all! 🌟

[github-actions]

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