DeerWatch Computer Vision Project

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Project Overview
Creating a model to detect deer when driving down the road

There are 3 categories used to create the class for each photo. Example: buck_front_standing

  1. Deer type - buck, doe, fawn; help model in case it improves results to distinguish between having antlers or not, having spots or not, etc
  2. View of deer - front, rear, side; not only to help the model identify a deer that looks different from different angles (2 legs from the front) but also in case long term there is usefulness in identifying that a deer is running towards the road or away from it
  3. Activity - standing, walking, running, eating; again, both to help the model but also for "threat" assessment as you drive and need to understand the current state of the deer

Initial images loaded (c. 60) to experiment with. Hope to have a larger dataset by 2023

Contribution and Labeling Guidelines
Any and all are welcome! We especially need deer in settings around roads.

Cite this Project

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

@misc{ deerwatch_dataset,
    title = { DeerWatch Dataset },
    type = { Open Source Dataset },
    author = { Automatez },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { dec },
    note = { visited on 2022-12-02 },



Last Updated

Just Now

Project Type

Object Detection




0, Deer, buck_front_eating, buck_front_standing, buck_front_walking, buck_rear_eating, buck_rear_running, buck_rear_standing, buck_side_eating, buck_side_running, buck_side_standing, buck_side_walking, doe, doe_front_eating, doe_front_running, doe_front_standing, doe_rear_eating, doe_rear_standing, doe_rear_walking, doe_side_eating, doe_side_jumping, doe_side_running, doe_side_standing, doe_side_walking, fawn_front_standing, fawn_rear_standing, fawn_side_eating, fawn_side_running, fawn_side_standing, fawn_side_walking


CC BY 4.0