Calling Timeout Object Detection Dataset and Pre-Trained Model by Mohamed Traore

Images

88 images

Explore Dataset

Peyton Manning couldn't help but try to call timeout for the Broncos

on Monday, September 12's ESPN Monday Night Football.

Video Source

This model is available to use any time you'd like to try make a video including object (timeout) counts of Peyton Manning, or another TV sports analyst, attempting to call timeout, or criticize a team for failing to call timeout.

Classes:

timeout
hands
- Note: this class is omitted for the Deploy tab model - it only exists in versions: v1, v2, v3
- Modify Classes was used to omit the hands class
- The class was originally included in case the model did not do well with recognizing the timeout hand signal, and post-processing such as comparing the overlap/distance between the predicted hands bounding boxes was necessary for confirming a timeout call

Want to test it for yourself??

Click this link for the video and right-click to copy/paste the Video Address for the video in the Deploy tab, or right-click to save the video file and upload it to the Deploy tab for testing.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            calling-timeout_dataset,
                            title = { Calling Timeout Dataset },
                            type = { Open Source Dataset },
                            author = { Mohamed Traore },
                            howpublished = { \url{ https://universe.roboflow.com/mohamed-traore-2ekkp/calling-timeout } },
                            url = { https://universe.roboflow.com/mohamed-traore-2ekkp/calling-timeout },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { sep },
                            note = { visited on 2024-04-25 },
                            }