yolo_test

[gnoscerer]

Search before asking

• I have searched the HUB issues and found no similar feature requests.

Description

Make the test better.

Use case

I would like to test the yolo

Additional

No response

[UltralyticsAssistant]

👋 Hello @gnoscerer, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:

• Quickstart. Start training and deploying YOLO models with HUB in seconds.
• Datasets: Preparing and Uploading. Learn how to prepare and upload your datasets to HUB in YOLO format.
• Projects: Creating and Managing. Group your models into projects for improved organization.
• Models: Training and Exporting. Train YOLOv5 and YOLOv8 models on your custom datasets and export them to various formats for deployment.
• Integrations. Explore different integration options for your trained models, such as TensorFlow, ONNX, OpenVINO, CoreML, and PaddlePaddle.
• Ultralytics HUB App. Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
  • iOS. Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
  • Android. Explore TFLite acceleration on mobile devices.
• Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.

If this is a 🐛 Bug Report, please provide screenshots and steps to reproduce your problem to help us investigate further.

If this is a ❓ Question or feature request, please expand with additional details about your goals, environment, and specific requirements so that we can assist you better.

An Ultralytics engineer will also review and assist with your inquiry shortly. Thank you for your patience! 😊

[pderrenger]

@gnoscerer hello there! 👋

It seems you're looking to improve the testing experience with YOLO. Could you clarify specifically what aspect of testing you'd like to enhance? For example, are you referring to:

1. Testing Pre-Trained Models: Running inference with pre-trained YOLO models on new data.
2. Validation/Testing During Training: Evaluating a model's performance on a validation/test set.
3. Benchmarking: Measuring your model's performance across different formats or hardware platforms.
4. Any Specific Features: Suggestions for automated testing, debugging tools, or other enhancements?

If you're starting with testing pre-trained models, you can try out the Ultralytics HUB for a seamless, no-code experience. Simply upload your data, test models via our web interface, or use the mobile app for real-time object detection. You can learn more about getting started here: Quickstart Guide.

For Python-based testing, here’s a quick example using the ultralytics package:

from ultralytics import YOLO

# Load a pre-trained YOLOv8 model
model = YOLO("yolov8n.pt")

# Run inference on an image
results = model("path/to/your_image.jpg")
results.show()  # Display detected objects

If you’re looking to validate your models, you can run:

yolo val model=yolov8n.pt data=coco.yaml

Let us know more about your use case, and we’ll be happy to guide you further! 🚀