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Bug Report: Incorrect Data Path in YOLOv8 Dataset Configuration
Description
While using the Roboflow Python client to download a YOLOv8 dataset for a tennis ball tracking project, I encountered an issue with the generated data.yaml file. The file's paths were incorrectly set, leading to a RuntimeError when attempting to train the YOLO model.
Steps to Reproduce
Download the dataset using the Roboflow Python client:
Observe the downloaded TennisBallTracker-9 folder with the standard YOLOv8 dataset structure.
Check the data.yaml file, which incorrectly references paths for training, validation, and test images.
Expected Behavior
The data.yaml file should correctly point to the respective image directories within the dataset folder.
Actual Behavior
The data.yaml file contains incorrect paths, leading to a RuntimeError when the YOLO model attempts to access the image directories:
RuntimeError: Dataset 'TennisBallTracker-9/data.yaml' error ❌
Dataset 'TennisBallTracker-9/data.yaml' images not found ⚠️, missing path '/.../android_figurine/datasets/TennisBallTracker-9/TennisBallTracker-9/valid/images'
Note dataset download directory is '/..../android_figurine/datasets'. You can update this in '/..../Ultralytics/settings.yaml'
TL;DR
The issue might be related to residual settings from a previous project (android_figurine) that seems to interfere with the current dataset configuration. It's unclear why the old dataset path is being referenced.
Temporary Solution
I modified the data.yaml file manually to correct the paths, which allowed the training to proceed successfully:
Hey @tomershukhman . Did some digging around the source code and struggled to see if this was an Ultralytics issue or a pathing issue in Roboflow. Did changing the ultralytics settings affect anything? If not, can you check your environment variables for a DATASET_DIRECTORY? If you don't provide a location in version.download(), it will check the environment for this variable and use it for pathing, rather than defaulting on just the filename.
Bug Report: Incorrect Data Path in YOLOv8 Dataset Configuration
Description
While using the Roboflow Python client to download a YOLOv8 dataset for a tennis ball tracking project, I encountered an issue with the generated
data.yaml
file. The file's paths were incorrectly set, leading to aRuntimeError
when attempting to train the YOLO model.Steps to Reproduce
Download the dataset using the Roboflow Python client:
Observe the downloaded
TennisBallTracker-9
folder with the standard YOLOv8 dataset structure.Check the
data.yaml
file, which incorrectly references paths for training, validation, and test images.Expected Behavior
The
data.yaml
file should correctly point to the respective image directories within the dataset folder.Actual Behavior
The
data.yaml
file contains incorrect paths, leading to aRuntimeError
when the YOLO model attempts to access the image directories:TL;DR
The issue might be related to residual settings from a previous project (
android_figurine
) that seems to interfere with the current dataset configuration. It's unclear why the old dataset path is being referenced.Temporary Solution
I modified the
data.yaml
file manually to correct the paths, which allowed the training to proceed successfully:Environment
Python version: 3.12
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