Can it train different types of detection tasks at the same time？

[Willforcv]

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Can it train different types of detection tasks at the same time, such as keypoint detection and object detection, but their targets are not the same?

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[glenn-jocher]

@Willforcv hello!

Thank you for your question. Currently, YOLOv8 does not support training different types of detection tasks (e.g., keypoint detection and object detection) simultaneously within the same model training session. Each task, such as object detection, segmentation, classification, and pose estimation, requires its own specific model architecture and training pipeline.

However, you can train separate models for each task and then use them in tandem for inference. For example, you could train one model for object detection and another for keypoint detection, and then run both models sequentially on your data.

Here’s a brief example of how you might approach this using Python:

from ultralytics import YOLO

# Load and train object detection model
object_detection_model = YOLO('yolov8n.pt')
object_detection_model.train(data='object_detection_data.yaml', epochs=100)

# Load and train keypoint detection model
keypoint_detection_model = YOLO('yolov8n-pose.pt')
keypoint_detection_model.train(data='keypoint_detection_data.yaml', epochs=100)

# Use both models for inference
object_results = object_detection_model.predict(source='image.jpg')
keypoint_results = keypoint_detection_model.predict(source='image.jpg')

# Display results
object_results[0].show()
keypoint_results[0].show()

For more detailed guidance on each task, you can refer to the Ultralytics documentation.

If you have any further questions or need additional assistance, feel free to ask! 😊

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