Open Ilovecode93 opened 1 week ago
👋 Hello @Ilovecode93, thank you for your interest in Ultralytics 🚀! 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 verify that the issue persists with the latest version of the ultralytics
package by upgrading all dependencies in your environment as shown below:
pip install -U ultralytics
If the issue persists, kindly provide a minimum reproducible example (MRE) to help us reproduce and debug the problem. For example:
data.yaml
or model.yaml
).If this is a ❓ Custom Training Question, providing additional details like the dataset configuration, training settings, and logs will help us better understand your situation.
For real-time conversation and support, feel free to join our Discord 🎧. For longer discussions, head over to Discourse or share insights on our Subreddit.
Ensure you are using the latest supported Python (>=3.8) and PyTorch (>=1.8) versions. Refer to the requirements for more details.
For compatibility and smooth execution, YOLO has been verified in various environments, which include:
If this badge is green, all Ultralytics CI tests are currently passing. CI tests verify the correct operation of all YOLO Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
⚠️ Please note that this is an automated response. Rest assured, an Ultralytics engineer will review your issue and assist you soon! 🚀
Is this OBB model?
@Y-T-G No, and I have found how to solve this issue. It seems that this photo was taken by the cellphone and when I try to pass the image_path to the model() function, pillow load this picture reversal automatically.
Search before asking
Ultralytics YOLO Component
No response
Bug
I create my own custom dataset and have trained it with yolov8 successfully, but when I tried to predict the images with the best model that I got. An image in the test set was completely wrong, other images were predicted successfully, how does that happen? Here is the bug image in the test set.
Environment
Ultralytics YOLOv8.2.90 🚀 Python-3.11.9 torch-2.4.0+cu121 CUDA:0 (NVIDIA A100-PCIE-40GB, 40339MiB) Setup complete ✅ (96 CPUs, 754.4 GB RAM, 401.0/438.9 GB disk)
OS Linux-5.15.0-113-generic-x86_64-with-glibc2.35 Environment Linux Python 3.11.9 Install pip RAM 754.35 GB CPU Intel Xeon Gold 6248R 3.00GHz CUDA 12.1
Minimal Reproducible Example
Additional
No response
Are you willing to submit a PR?