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Merge pull request #404 from roboflow/develop
`supervision-0.15.0` release
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‎.github/workflows/test.yml‎

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python -m pip install --upgrade pip
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pip install -e .
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pip install pytest
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pip install isort
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pip install flake8
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pip install "black==22.3.0"
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- name: 🧪 Test
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run: "python -m pytest ./test"

‎.pre-commit-config.yaml‎

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- repo: https://github.com/psf/black
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rev: 23.7.0
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rev: 23.9.1
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hooks:
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- id: black
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.0.286
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rev: v0.0.292
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hooks:
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- id: ruff
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args: [--fix, --exit-non-zero-on-fix]

‎CODE_OF_CONDUCT.md‎

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# Contributor Covenant Code of Conduct
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## Our Pledge
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We as members, contributors, and leaders pledge to make participation in our
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community a harassment-free experience for everyone, regardless of age, body
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size, visible or invisible disability, ethnicity, sex characteristics, gender
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identity and expression, level of experience, education, socio-economic status,
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nationality, personal appearance, race, caste, color, religion, or sexual
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identity and orientation.
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We pledge to act and interact in ways that contribute to an open, welcoming,
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diverse, inclusive, and healthy community.
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## Our Standards
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Examples of behavior that contributes to a positive environment for our
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community include:
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* Demonstrating empathy and kindness toward other people
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* Being respectful of differing opinions, viewpoints, and experiences
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* Giving and gracefully accepting constructive feedback
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* Accepting responsibility and apologizing to those affected by our mistakes,
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and learning from the experience
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* Focusing on what is best not just for us as individuals, but for the overall
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community
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Examples of unacceptable behavior include:
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* The use of sexualized language or imagery, and sexual attention or advances of
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any kind
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* Trolling, insulting or derogatory comments, and personal or political attacks
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* Public or private harassment
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* Publishing others' private information, such as a physical or email address,
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without their explicit permission
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* Other conduct which could reasonably be considered inappropriate in a
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professional setting
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## Enforcement Responsibilities
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Community leaders are responsible for clarifying and enforcing our standards of
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acceptable behavior and will take appropriate and fair corrective action in
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response to any behavior that they deem inappropriate, threatening, offensive,
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or harmful.
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Community leaders have the right and responsibility to remove, edit, or reject
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comments, commits, code, wiki edits, issues, and other contributions that are
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not aligned to this Code of Conduct, and will communicate reasons for moderation
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decisions when appropriate.
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## Scope
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This Code of Conduct applies within all community spaces, and also applies when
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an individual is officially representing the community in public spaces.
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Examples of representing our community include using an official e-mail address,
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posting via an official social media account, or acting as an appointed
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representative at an online or offline event.
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## Enforcement
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Instances of abusive, harassing, or otherwise unacceptable behavior may be
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reported to the community leaders responsible for enforcement at
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community-reports@roboflow.com.
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All complaints will be reviewed and investigated promptly and fairly.
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All community leaders are obligated to respect the privacy and security of the
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reporter of any incident.
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## Enforcement Guidelines
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Community leaders will follow these Community Impact Guidelines in determining
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the consequences for any action they deem in violation of this Code of Conduct:
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### 1. Correction
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**Community Impact**: Use of inappropriate language or other behavior deemed
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unprofessional or unwelcome in the community.
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**Consequence**: A private, written warning from community leaders, providing
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clarity around the nature of the violation and an explanation of why the
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behavior was inappropriate. A public apology may be requested.
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### 2. Warning
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**Community Impact**: A violation through a single incident or series of
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actions.
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**Consequence**: A warning with consequences for continued behavior. No
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interaction with the people involved, including unsolicited interaction with
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those enforcing the Code of Conduct, for a specified period of time. This
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includes avoiding interactions in community spaces as well as external channels
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like social media. Violating these terms may lead to a temporary or permanent
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ban.
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### 3. Temporary Ban
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**Community Impact**: A serious violation of community standards, including
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sustained inappropriate behavior.
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**Consequence**: A temporary ban from any sort of interaction or public
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communication with the community for a specified period of time. No public or
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private interaction with the people involved, including unsolicited interaction
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with those enforcing the Code of Conduct, is allowed during this period.
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Violating these terms may lead to a permanent ban.
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### 4. Permanent Ban
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**Community Impact**: Demonstrating a pattern of violation of community
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standards, including sustained inappropriate behavior, harassment of an
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individual, or aggression toward or disparagement of classes of individuals.
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**Consequence**: A permanent ban from any sort of public interaction within the
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community.
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## Attribution
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This Code of Conduct is adapted from the [Contributor Covenant][homepage],
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version 2.1, available at
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[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
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Community Impact Guidelines were inspired by
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[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
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For answers to common questions about this code of conduct, see the FAQ at
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[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
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[https://www.contributor-covenant.org/translations][translations].
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[homepage]: https://www.contributor-covenant.org
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[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
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[Mozilla CoC]: https://github.com/mozilla/diversity
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[FAQ]: https://www.contributor-covenant.org/faq
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[translations]: https://www.contributor-covenant.org/translations

‎README.md‎

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</details>
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## 🛠️ built with supervision
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Did you build something cool using supervision? [Let us know!](https://github.com/roboflow/supervision/discussions/categories/built-with-supervision)
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https://user-images.githubusercontent.com/26109316/207858600-ee862b22-0353-440b-ad85-caa0c4777904.mp4
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## 🎬 tutorials
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<p align="left">
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<a href="https://youtu.be/oEQYStnF2l8" title="Accelerate Image Annotation with SAM and Grounding DINO"><img src="https://github.com/SkalskiP/SkalskiP/assets/26109316/ae1ca38e-40b7-4b35-8582-e8ea5de3806e" alt="Accelerate Image Annotation with SAM and Grounding DINO" width="300px" align="left" /></a>
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<a href="https://youtu.be/oEQYStnF2l8" title="Accelerate Image Annotation with SAM and Grounding DINO"><strong>Accelerate Image Annotation with SAM and Grounding DINO</strong></a>
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<div><strong>Created: 20 Apr 2023</strong> | <strong>Updated: 20 Apr 2023</strong></div>
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<br/> Discover how to speed up your image annotation process using Grounding DINO and Segment Anything Model (SAM). Learn how to convert object detection datasets into instance segmentation datasets, and see the potential of using these models to automatically annotate your datasets for real-time detectors like YOLOv8... </p>
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<a href="https://youtu.be/4Q3ut7vqD5o" title="Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking"><img src="https://github.com/roboflow/supervision/assets/26109316/54afdf1c-218c-4451-8f12-627fb85f1682" alt="Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking" width="300px" align="left" /></a>
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<a href="https://youtu.be/4Q3ut7vqD5o" title="Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking"><strong>Traffic Analysis with YOLOv8 and ByteTrack - Vehicle Detection and Tracking</strong></a>
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<div><strong>Created: 6 Sep 2023</strong> | <strong>Updated: 6 Sep 2023</strong></div>
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<br/> In this video, we explore real-time traffic analysis using YOLOv8 and ByteTrack to detect and track vehicles on aerial images. Harnessing the power of Python and Supervision, we delve deep into assigning cars to specific entry zones and understanding their direction of movement. By visualizing their paths, we gain insights into traffic flow across bustling roundabouts... </p>
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<br/>
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<div><strong>Created: 11 Apr 2023</strong> | <strong>Updated: 11 Apr 2023</strong></div>
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<br/> Discover the incredible potential of Meta AI's Segment Anything Model (SAM)! We dive into SAM, an efficient and promptable model for image segmentation, which has revolutionized computer vision tasks. With over 1 billion masks on 11M licensed and privacy-respecting images, SAM's zero-shot performance is often competitive with or even superior to prior fully supervised results... </p>
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## 💜 built with supervision
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Did you build something cool using supervision? [Let us know!](https://github.com/roboflow/supervision/discussions/categories/built-with-supervision)
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https://user-images.githubusercontent.com/26109316/207858600-ee862b22-0353-440b-ad85-caa0c4777904.mp4
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https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-60e9c81b3900
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## 📚 documentation
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Visit our [documentation](https://roboflow.github.io/supervision) page to learn how supervision can help you build computer vision applications faster and more reliably.

‎docs/annotators.md‎

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=== "BoundingBox"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> bounding_box_annotator = sv.BoundingBoxAnnotator()
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>>> annotated_frame = bounding_box_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![bounding-box-annotator-example](https://media.roboflow.com/supervision-annotator-examples/bounding-box-annotator-example.png){ align=center width="800" }
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</div>
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=== "Mask"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> mask_annotator = sv.MaskAnnotator()
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>>> annotated_frame = mask_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![mask-annotator-example](https://media.roboflow.com/supervision-annotator-examples/mask-annotator-example.png){ align=center width="800" }
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</div>
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=== "Ellipse"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> ellipse_annotator = sv.EllipseAnnotator()
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>>> annotated_frame = ellipse_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![ellipse-annotator-example](https://media.roboflow.com/supervision-annotator-examples/ellipse-annotator-example.png){ align=center width="800" }
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</div>
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=== "BoxCorner"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> corner_annotator = sv.BoxCornerAnnotator()
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>>> annotated_frame = corner_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![box-corner-annotator-example](https://media.roboflow.com/supervision-annotator-examples/box-corner-annotator-example.png){ align=center width="800" }
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</div>
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=== "Circle"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> circle_annotator = sv.CircleAnnotator()
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>>> annotated_frame = circle_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![circle-annotator-example](https://media.roboflow.com/supervision-annotator-examples/circle-annotator-example.png){ align=center width="800" }
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</div>
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=== "Label"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
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>>> annotated_frame = label_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![label-annotator-example](https://media.roboflow.com/supervision-annotator-examples/label-annotator-example-2.png){ align=center width="800" }
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</div>
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=== "Blur"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> blur_annotator = sv.BlurAnnotator()
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>>> annotated_frame = blur_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![blur-annotator-example](https://media.roboflow.com/supervision-annotator-examples/blur-annotator-example-2.png){ align=center width="800" }
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</div>
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=== "Trace"
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```python
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>>> import supervision as sv
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>>> image = ...
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>>> detections = sv.Detections(...)
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>>> trace_annotator = sv.TraceAnnotator()
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>>> annotated_frame = trace_annotator.annotate(
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... scene=image.copy(),
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... detections=detections
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... )
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```
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<div class="result" markdown>
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![trace-annotator-example](https://media.roboflow.com/supervision-annotator-examples/trace-annotator-example.png){ align=center width="800" }
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</div>
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## BoundingBoxAnnotator
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:::supervision.annotators.core.BoundingBoxAnnotator
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## MaskAnnotator
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:::supervision.annotators.core.MaskAnnotator
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## EllipseAnnotator
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:::supervision.annotators.core.EllipseAnnotator
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## BoxCornerAnnotator
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:::supervision.annotators.core.BoxCornerAnnotator
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## CircleAnnotator
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:::supervision.annotators.core.CircleAnnotator
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## LabelAnnotator
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:::supervision.annotators.core.LabelAnnotator
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## TraceAnnotator
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:::supervision.annotators.core.TraceAnnotator
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## BlurAnnotator
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:::supervision.annotators.core.BlurAnnotator

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