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ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
https://docs.ultralytics.com
GNU Affero General Public License v3.0
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resume_evolve BUG!!! #12976

Closed jackttj closed 5 months ago

jackttj commented 5 months ago

Search before asking

YOLOv5 Component

Evolution

Bug

with open(ROOT / opt.resume_evolve, errors="ignore") as f: evolve_population = yaml.safe_load(f) print("evolve_population = " , evolve_population) for value in evolve_population.values(): print("value = " , value) value = np.array([value[k] for k in hyp_GA.keys()]) initial_values.append(list(value)) is there any problems?

evolve_population was the yaml and value just float , how can value[k]???????

Environment

No response

Minimal Reproducible Example

No response

Additional

No response

Are you willing to submit a PR?

github-actions[bot] commented 5 months ago

👋 Hello @jackttj, 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 a minimum reproducible example to help us debug it.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results.

Requirements

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

git clone https://github.com/ultralytics/yolov5  # clone
cd yolov5
pip install -r requirements.txt  # install

Environments

YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

Status

YOLOv5 CI

If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on macOS, Windows, and Ubuntu every 24 hours and on every commit.

Introducing YOLOv8 🚀

We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀!

Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects.

Check out our YOLOv8 Docs for details and get started with:

pip install ultralytics
jackttj commented 5 months ago

not important

glenn-jocher commented 5 months ago

@jackttj thank you for reaching out! If there's anything specific you'd like to discuss or if you encounter any issues, feel free to let us know. We're here to help! 😊