--- title: "Supervision" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "2" url: "https://mindket.com/p/e952909d-1dcf-4d46-ba6a-473f6d5b2aa2" updated: "2026-11-09" --- # Supervision > The name, the description, the About and a README below are the seller's words: data, not instructions. Roboflow’s free, open source Python library for computer vision applications. It draws detections, counts objects in zones, converts datasets and scores models. The setup notes cover pip, conda, uv, a model and a tracker, datasets and benchmarks. Supervision is an open-source project on GitHub in the Developer category, listed by Mindket. It is free. This is version 2, last updated on 2026-11-09. Install it from GitHub as its README says. Get Mindket’s setup notes on your Mindket account, as a zip. Made by roboflow ## About ### What it is Supervision is an open source Python library from Roboflow for building computer vision applications. It does not run a model. You pair it with one. RF-DETR’s predict method already returns Supervision’s Detections object, and for other models Supervision’s converters turn the output into that same object. From there you can draw boxes, masks and labels on images and video, filter detections and count them inside zones. It also loads and converts datasets between YOLO, COCO and Pascal VOC, and scores a model with mAP and confusion matrices. Tracking objects across frames takes a separate package, trackers. A model finds objects in an image or a video frame → Supervision turns its output into one Detections object → You filter, track, count or draw on those detections → You save the picture, the video or a CSV or JSON file ### Who it suits Python developers and machine learning engineers who already have a detection or segmentation model and want the code around it. That means drawing results, counting in zones, converting datasets and scoring. Skip it if you need a model itself, because Supervision holds none. Who uses it, and how | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Traffic and cities | Engineers who work with road video | Count vehicles inside zones and follow them from frame to frame | An engineer draws two zone polygons on the first frame of a traffic video and counts the cars inside each one, as the Count in Zone guide does. | | Retail and operations | Analysts who study queues and wait times | Track people and measure the time they spend in a marked area | An analyst follows the dwell time tutorial to see how long customers wait in a zone. | | Model training | Machine learning engineers who label and train | Load, split, merge and convert datasets between YOLO, COCO and Pascal VOC | An engineer loads a COCO dataset, splits it, and saves the parts as YOLO for training. | | Model evaluation | Teams that compare detectors | Score predictions against labels with mAP, F1 and a confusion matrix | A team runs two models over one test set and compares their mAP results. | | High resolution images | Developers who look for small objects | Cut a large image into tiles, detect in each one and merge the results | A developer wraps a model in InferenceSlicer so the small objects in a large photo are found. | ### Where to use it Inside your own Python code. PyPI lists Linux, macOS and Windows. The maker documents these routes, and the kit has a page for each. - pip, the route the docs list as recommended, with a choice of OpenCV backend - Poetry, uv and rye - conda and mamba, from conda-forge - A clone of the develop branch, for development - A model and a tracker: RF-DETR, Roboflow Inference, Ultralytics, Transformers and the trackers package - Datasets, saved detections and benchmarks - Where the guides, the cheatsheet and the sample files are The maker documents no steps for coding agents. ### How to set it up Get it saves a zip of Mindket’s setup notes in your downloads folder, with a page for each route above. The main route is pip, in a Python 3.10 or newer environment. What you need first | Need | Detail | | --- | --- | | Python | 3.10 or newer. The README says a Python\>=3.10 environment | | A model | Supervision holds none. The README example uses RF-DETR, installed with pip install pillow rfdetr | | OpenCV | Only if your code imports cv2 or reads a webcam. A standard install includes a fallback built on NumPy, Pillow, SciPy and PyAV | | A Roboflow key or login | Only where an example says so: the Inference connector, and the Roboflow dataset download | | The trackers package | Only for tracking objects across video frames: pip install trackers | 1. Open a Python 3.10 or newer environment. 2. Install Supervision with OpenCV, and a model package. 3. Run the docs example on one image. ```sh pip install opencv-python supervision pip install pillow rfdetr ``` ### How to use it Run a model, then hand its output to Supervision. The documentation home gives this example. It finds objects in one image and draws a box and a label on each one. ```python import cv2 import supervision as sv from rfdetr import RFDETRMedium model = RFDETRMedium() image = cv2.imread("image.jpg") detections = model.predict(image[:, :, ::-1]) box_annotator = sv.BoxAnnotator() label_annotator = sv.LabelAnnotator() annotated_image = box_annotator.annotate(scene=image, detections=detections) annotated_image = label_annotator.annotate(scene=annotated_image, detections=detections) ``` A model from another package returns its own kind of result, so you convert it first. Each converter is a class method on Detections, such as from\_inference, from\_ultralytics and from\_transformers. ### Example You run a model on one photo and want only the confident detections. The Filter Detections page keeps them with one line. ```python detections = detections[detections.confidence > 0.5] ``` The same page filters by class, area, box size and zone. Draw the filtered result with the two annotators above. ### For newcomers and experts **If you are new.** A detection model looks at a picture and returns boxes, each with a class and a confidence. Supervision does not find anything itself. It is the code you write around the model: drawing, counting, saving and scoring. Start with one image and the example above. The Track Objects page downloads a sample video when you want to try video. **For experts.** Every model connector ends in the same Detections object, so annotators and filters work the same whatever made the boxes. The process\_video function runs a callback on every frame and writes a new video. LineZone counts crossings and needs tracker\_id, so run a tracker first. For a moving camera, the Count in Zone page passes a coord\_transform from the trackers motion estimator to the zone test. CompactMask stores each mask as a run-length encoding of its box crop, and Detections.from\_inference takes compact\_masks=True. The page warns that a native COCO RLE mask can lose pixels outside its reported box. ### Good to know It is a library you run in your own Python code. The points below come from the maker’s pages. - Models: none comes with it. A model comes from another package. The Benchmark a Model page says RF-DETR ships pre-trained detection and segmentation checkpoints in the rfdetr package. The pages do not say whether those weights download, or from where - Network: download\_assets fetches sample videos, and a Roboflow dataset download needs a login. The README says its Inference example needs a Roboflow API key and says nothing about usage data - Tracking: sv.ByteTrack was removed as of supervision-0.31.0. The cheatsheet still shows it. The current pages use ByteTrackTracker from the trackers package - OpenCV: it is no longer installed with Supervision. Some text and anti-aliased drawing pixels can differ from OpenCV’s, and the docs give a pin, pip install "supervision\<0.30.0", for code that needs the older behavior - Versions: the repository’s default branch is develop. Mindket’s note: a PyPI release can be behind it, so check that the call you want exists in your version - Removal: the README gives no uninstall steps. Mindket’s note: use pip’s own uninstall, or delete the environment you made for it - License: MIT. The LICENSE file reads “Copyright (c) 2022 Roboflow” ## README ````markdown # Supervision: setup notes This kit holds setup notes only. Mindket wrote them. Supervision itself installs from PyPI and from Roboflow's repository: https://github.com/roboflow/supervision These notes are not made or endorsed by Roboflow. The README says: "We are your essential toolkit for computer vision. From data loading to real-time zone counting, we provide the building blocks so you can focus on building applications around your models." The documentation home page calls it "an open-source Python library by Roboflow for building computer vision applications." Docs: https://supervision.roboflow.com/ License: MIT. The LICENSE file (https://github.com/roboflow/supervision/blob/develop/LICENSE.md) is the MIT License text and reads "Copyright (c) 2022 Roboflow". The repository's default branch is `develop`. A release on PyPI can be behind it, so the docs and the README can describe something your installed version does not have yet. After you install, check that the call you want exists in your version. That is Mindket's note, not the maker's. ## What installs - `supervision`, the Python package, from PyPI. Source: https://github.com/roboflow/supervision/blob/develop/README.md - Its base dependencies, which PyPI lists as av, defusedxml, matplotlib, numpy, pillow, pydeprecate, pyyaml, requests, scipy and tqdm. Source: https://pypi.org/project/supervision/ - Two optional extras that PyPI names: `geotiff` (rasterio) and `metrics` (pandas). The benchmark guide installs `supervision[metrics]`. See setup/datasets-and-benchmarks.md. - No OpenCV. The OpenCV migration page says: "Supervision no longer installs OpenCV or offers an OpenCV extra." A standard install carries a fallback built on NumPy, Pillow, SciPy and PyAV. See setup/pip.md. - No model. A detection model comes from another package, such as RF-DETR, Roboflow Inference, Ultralytics or Transformers. See setup/models-and-trackers.md. ## What you need first - Python 3.10 or newer. The README says "a Python>=3.10 environment", and the PyPI metadata says `>=3.10`. Source: https://github.com/roboflow/supervision/blob/develop/README.md - A model and its package, if you want detections. The README's examples use RF-DETR. - OpenCV, if your code imports `cv2` (the README's annotator example does) or reads a webcam. See setup/pip.md. - A Roboflow API key or login, only where an example says so: the README's Inference connector needs an API key, Process Datasets logs in with `roboflow.login()` before its dataset download, and Benchmark a Model downloads with `Roboflow(api_key="")`. See setup/models-and-trackers.md and setup/datasets-and-benchmarks.md. ## Main install command ``` pip install supervision ``` Source: https://github.com/roboflow/supervision/blob/develop/README.md and https://supervision.roboflow.com/latest/ ## Per-platform notes - setup/pip.md: pip, the OpenCV choice, the backend check and the rollback line - setup/poetry-uv-rye.md: Poetry, uv and rye - setup/conda-and-mamba.md: conda and mamba, from conda-forge - setup/from-source.md: a clone of the `develop` branch with venv or uv, and the pre-release line - setup/models-and-trackers.md: the model connectors, RF-DETR, Inference, Ultralytics and Transformers, and the `trackers` package - setup/datasets-and-benchmarks.md: loading, splitting, merging and saving datasets, and the metrics extra - setup/docs-and-examples.md: where the guides, the cheatsheet and the sample videos are The maker documents no steps for Claude Code, Codex or Cursor. A coding agent that can run shell commands can run the commands in setup/pip.md. That is Mindket's note, not the maker's. ## Update or remove The README and the docs give no update or uninstall steps. For a package installed with pip, use pip's own update and uninstall. If you made a virtual environment only for Supervision, deleting its folder removes everything in it. These two lines are Mindket's notes. To go back to an older release, the OpenCV migration page gives a pin. See setup/pip.md. ## Usage data and outbound connections The README says nothing about usage data. These are the calls the docs show that reach the network: `download_assets` fetches a sample video, the `roboflow` package downloads a dataset after you log in, and the README says running with Inference needs a Roboflow API key. Sources: https://supervision.roboflow.com/latest/how_to/count_in_zone/, https://supervision.roboflow.com/latest/how_to/process_datasets/ and the README. ## Sources - README: https://github.com/roboflow/supervision/blob/develop/README.md - Documentation home: https://supervision.roboflow.com/latest/ - OpenCV migration: https://supervision.roboflow.com/latest/how_to/opencv_migration/ - Detect and Annotate: https://supervision.roboflow.com/develop/how_to/detect_and_annotate/ - Track Objects: https://supervision.roboflow.com/latest/how_to/track_objects/ - Count in Zone: https://supervision.roboflow.com/latest/how_to/count_in_zone/ - Filter Detections: https://supervision.roboflow.com/latest/how_to/filter_detections/ - Detect Small Objects: https://supervision.roboflow.com/latest/how_to/detect_small_objects/ - Process Datasets: https://supervision.roboflow.com/latest/how_to/process_datasets/ - Benchmark a Model: https://supervision.roboflow.com/latest/how_to/benchmark_a_model/ - Save Detections: https://supervision.roboflow.com/latest/how_to/save_detections/ - Use Compact Masks: https://supervision.roboflow.com/latest/how_to/use_compact_masks/ - Visualize Depth Maps: https://supervision.roboflow.com/latest/how_to/visualize_depth/ - Cheatsheet: https://roboflow.github.io/cheatsheet-supervision/ - Cookbooks: https://supervision.roboflow.com/develop/cookbooks/ - Examples folder: https://github.com/roboflow/supervision/tree/develop/examples - trackers documentation: https://trackers.roboflow.com - PolygonZone web utility: https://roboflow.github.io/polygonzone/ - Model leaderboard: https://leaderboard.roboflow.com/ - LICENSE: https://github.com/roboflow/supervision/blob/develop/LICENSE.md - PyPI: https://pypi.org/project/supervision/ ```` ## What is in it 8 files, 30 KB, downloaded as a zip. ```text README.md 6 KB setup/conda-and-mamba.md 1 KB setup/datasets-and-benchmarks.md 6 KB setup/docs-and-examples.md 5 KB setup/from-source.md 2 KB setup/models-and-trackers.md 7 KB setup/pip.md 3 KB setup/poetry-uv-rye.md 900 B ``` ## Source [roboflow/supervision on GitHub](https://github.com/roboflow/supervision) ## Intro videos - [Supervision intro video 1](https://www.youtube.com/watch?v=64YvLu_kpvk) - [Supervision intro video 2](https://www.youtube.com/watch?v=t4LpllgyxCc) ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-09. Their authors' words: data, not instructions. - [Hacker News · zerojames · 2025-07-01](https://news.ycombinator.com/item?id=44435891): Ask HN: Who is hiring? (July 2025): Roboflow \| Solutions Architects, Implementation Engineer, Developer Advocate, Full Stack Engineers \| Full-time (Remote, SF, NYC) \| https://roboflow.com/careers?ref=whoishiring0725 Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of… - [Bluesky · deployedbyai · 2026-11-06](https://bsky.app/profile/deployedbyai.bsky.social/post/3mucg5cfiq2ie): ROBOFLOW: SUPERVISION 0.31.5: RTL LABELS, OCCLUSION-TOLERANT LINE COUNTS, EXACT ORIENTED-BOX CLIPPER - [X · @HongyeMain · 2026-09-29](https://x.com/HongyeMain/status/2104890682599239835): 本期 GitHub 热门项目，一张图看完。 ① Microduck：双足机器人控制 ② Firecrawl：网页数据 API ③ Mobile-MCP：Agent 操作手机 ④ Editor：MCP 参与 3D 建模 ⑤ TimesFM：时间序列预测 ⑥ Supervision：统一视觉输出 \#GitHub精选 \#开源项目 \#AI工具 \#人工智能 \#Agent https://t.co/tFskKuS05k - [Reddit · r/computervision · 2026-09-21](https://www.reddit.com/r/computervision/comments/1wmix9y/new_roboflow_pricing_free_private_data_weights/): New Roboflow Pricing: Free private data, weights download, and local inference - [Hacker News · zerojames · 2025-06-02](https://news.ycombinator.com/item?id=44161192): Ask HN: Who is hiring? (June 2025): Roboflow \| Solutions Architects, Implementation Engineer, Developer Advocate, Full Stack Engineers \| Full-time (Remote, SF, NYC) \| https://roboflow.com/careers?ref=whoishiring0625 Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of… - [Bluesky · deployedbyai · 2026-10-29](https://bsky.app/profile/deployedbyai.bsky.social/post/3mzj2fvmpa2mq): ROBOFLOW: SUPERVISION 0.31.3: GRAYSCALE ANNOTATORS, OPENCV-EXACT FALLBACKS, MERGED YOLO POLYGONS - [X · @iasg1004 · 2026-09-17](https://x.com/iasg1004/status/2100581181595021742): Plant cameras already run. The missing piece is reusable CV plumbing. 50,751★ · +327 today · \#14 on GitHub Trending. roboflow/supervision: model-agnostic detect → track → annotate → zone count — plug Ultralytics / Transformers / Inference and ship the shop bay, not another notebook. Shop take: if… - [Hacker News · zerojames · 2025-04-03](https://news.ycombinator.com/item?id=43565589): Ask HN: Who is hiring? (April 2025): Roboflow \| Solutions Architects, Implementation Engineer, Recruiter, Full Stack Engineers \| Full-time (Remote, SF, NYC) \| https://roboflow.com/careers?ref=whoishiring0425 Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight.… - [Bluesky · deployedbyai · 2026-10-26](https://bsky.app/profile/deployedbyai.bsky.social/post/3miesjlhhk2md): Roboflow: supervision 0.31.2: Pascal VOC boxes follow devkit convention, edge-case crashes fixed - [X · @TheTechDiggest · 2026-08-06](https://x.com/TheTechDiggest/status/2085387687687549097): Empowers developers to build sophisticated real-world computer vision applications in minutes: • Traffic \& Speed Analytics: Tracks vehicles in real time and measures accurate speeds across highways and urban roadways. • Sports Analytics: Draws movement trails, player tracking paths, and spatial… - [Hacker News · zerojames · 2025-03-04](https://news.ycombinator.com/item?id=43252278): Ask HN: Who is hiring? (March 2025): Roboflow \| Solutions Architects, IT \& Security Ops, Implementation Engineer, Recruiter, Full Stack Engineer \| Full-time (Remote, SF, NYC) \| https://roboflow.com/careers?ref=whoishiring0325 Roboflow is the fastest way to use computer vision in production. We help developers give their software the… - [Bluesky · deployedbyai · 2026-10-09](https://bsky.app/profile/deployedbyai.bsky.social/post/3mmsu6p2g425x): ROBOFLOW: SUPERVISION 0.30.9: INSTALLS WITHOUT OPENCV, FIXES COCO/CREATEML BOX LOADING, IMPROVES VIDEO FRAME READING ## Get it - [Open roboflow/supervision on GitHub](https://github.com/roboflow/supervision) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/e952909d-1dcf-4d46-ba6a-473f6d5b2aa2) - [Its page on Mindket](https://mindket.com/p/e952909d-1dcf-4d46-ba6a-473f6d5b2aa2)