TFlite INT8 Exports failing

[glenn-jocher]

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• I have searched the YOLOv8 issues and found no similar bug report.

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Bug

Environment

Ultralytics YOLOv8.2.18 🚀 Python-3.10.12 torch-2.3.0+cu121 CUDA:0 (Tesla T4, 15102MiB)
Setup complete ✅ (2 CPUs, 12.7 GB RAM, 32.1/78.2 GB disk)

OS                  Linux-6.1.85+-x86_64-with-glibc2.35
Environment         Colab
Python              3.10.12
Install             pip
RAM                 12.67 GB
CPU                 Intel Xeon 2.30GHz
CUDA                12.1

matplotlib          ✅ 3.7.1>=3.3.0
opencv-python       ✅ 4.8.0.76>=4.6.0
pillow              ✅ 9.4.0>=7.1.2
pyyaml              ✅ 6.0.1>=5.3.1
requests            ✅ 2.31.0>=2.23.0
scipy               ✅ 1.11.4>=1.4.1
torch               ✅ 2.3.0+cu121>=1.8.0
torchvision         ✅ 0.18.0+cu121>=0.9.0
tqdm                ✅ 4.66.4>=4.64.0
psutil              ✅ 5.9.5
py-cpuinfo          ✅ 9.0.0
thop                ✅ 0.1.1-2209072238>=0.1.1
pandas              ✅ 2.0.3>=1.1.4
seaborn             ✅ 0.13.1>=0.11.0

Minimal Reproducible Example

!yolo export format=tflite imgsz=[320,320] int8

Additional

No response

Are you willing to submit a PR?

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

[github-actions]

👋 Hello @glenn-jocher, thank you for your interest in Ultralytics YOLOv8 🚀! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.

If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it.

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Install

Pip install the ultralytics package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.

pip install ultralytics

Environments

YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

• Notebooks with free GPU:
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Amazon Deep Learning AMI. See AWS Quickstart Guide
• Docker Image. See Docker Quickstart Guide

Status

If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLOv8 Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.

[glenn-jocher]

@sergiuwaxmann @yogendrasinghx bug report opened here for our INT8 TFLite failures!

[github-actions]

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

• Docs: https://docs.ultralytics.com
• HUB: https://hub.ultralytics.com
• Community: https://community.ultralytics.com

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐