12k images

Rocket Detect Computer Vision Project

NASASpaceflight

Updated 2 years ago

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Metrics

mAP is equal to the average of the Average Precision metric across all classes in a model. Learn more

mAP

89.4%

Precision measures how often your model's predictions are correct. Learn more

Precision

91.0%

Recall measures what percentage of relevant labels were successfully identified. Learn more

Recall

87.9%

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Description

Rocket Detect is the dataset used to train the nueral network behind Autotrack, NASASpaceflight's automated rocket tracking system. Rocket Detect uses three classes:

Engine Flames - The fire produced by the rocket
Rocket Body - The body of the launch vehicle
Space - A tiny spec in the sky that is the rocket after it has ascended into space

Using YoloV5 and Strongsort, Rocket Detect in its current form has proven sufficient to reliably track a Falcon 9 first stage continuously form launch to landing. It also works on a wide variety of other launch vehicles. The dataset will increase with time to further improve reliablity.

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Cite This Project

LICENSE

CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        
        highlighted
        
            
        
     
@misc{
                            rocket-detect_dataset,
                            title = { Rocket Detect Dataset },
                            type = { Open Source Dataset },
                            author = { NASASpaceflight },
                            howpublished = { \url{ https://universe.roboflow.com/nasaspaceflight/rocket-detect } },
                            url = { https://universe.roboflow.com/nasaspaceflight/rocket-detect },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2025-03-06 },
                            }