From cac62e834f05fd072219c2f1d1cddfea86fda2c3 Mon Sep 17 00:00:00 2001 From: wehub-resource-sync Date: Mon, 13 Jul 2026 09:51:58 +0000 Subject: [PATCH] docs: preserve upstream English README --- README.en.md | 321 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 321 insertions(+) create mode 100644 README.en.md diff --git a/README.en.md b/README.en.md new file mode 100644 index 0000000..c8d587e --- /dev/null +++ b/README.en.md @@ -0,0 +1,321 @@ +
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+ +[notebooks](https://github.com/roboflow/notebooks) | [inference](https://github.com/roboflow/inference) | [autodistill](https://github.com/autodistill/autodistill) | [maestro](https://github.com/roboflow/multimodal-maestro) + +
+ +[![version](https://badge.fury.io/py/supervision.svg)](https://badge.fury.io/py/supervision) [![downloads](https://img.shields.io/pypi/dm/supervision)](https://pypistats.org/packages/supervision) [![license](https://img.shields.io/pypi/l/supervision)](LICENSE.md) [![python-version](https://img.shields.io/pypi/pyversions/supervision)](https://badge.fury.io/py/supervision) [![codecov](https://codecov.io/gh/roboflow/supervision/graph/badge.svg?token=HMNJ5FVZ36)](https://codecov.io/gh/roboflow/supervision) + +[![snyk](https://snyk.io/advisor/python/supervision/badge.svg)](https://snyk.io/advisor/python/supervision) [![colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/supervision/blob/main/demo.ipynb) [![gradio](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/Roboflow/Annotators) [![discord](https://img.shields.io/discord/1159501506232451173?logo=discord&label=discord&labelColor=fff&color=5865f2&link=https%3A%2F%2Fdiscord.gg%2FGbfgXGJ8Bk)](https://discord.gg/GbfgXGJ8Bk) + +
+ roboflow%2Fsupervision | Trendshift +
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+ +
+📑 Table of Contents + +- [👋 Hello](#-hello) +- [💻 Install](#-install) +- [🔥 Quickstart](#-quickstart) + - [Models](#models) + - [Annotators](#annotators) + - [Datasets](#datasets) +- [🎬 Tutorials](#-tutorials) +- [💜 Built with Supervision](#-built-with-supervision) +- [📚 Documentation](#-documentation) +- [🏆 Contribution](#-contribution) + +
+ +## 👋 Hello + +**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. 🤝 + +## 💻 Install + +Pip install the supervision package in a [**Python>=3.10**](https://www.python.org/) environment. + +```bash +pip install supervision +``` + +Read more about conda, mamba, and installing from source in our [guide](https://roboflow.github.io/supervision/). + +## 🔥 Quickstart + +### Models + +Supervision was designed to be model agnostic. Just plug in any classification, detection, or segmentation model. For your convenience, we have created [connectors](https://supervision.roboflow.com/latest/detection/core/#detections) for the most popular libraries like Ultralytics, Transformers, MMDetection, or Inference. Other integrations, like `rfdetr`, already return `sv.Detections` directly. + +Install the optional dependencies for this example with `pip install pillow rfdetr`. + +```python +import supervision as sv +from PIL import Image +from rfdetr import RFDETRSmall + +image = Image.open("path/to/image.jpg") +model = RFDETRSmall() +detections = model.predict(image, threshold=0.5) + +len(detections) +# 5 +``` + +
+👉 more model connectors + +- inference + + Running with [Inference](https://github.com/roboflow/inference) requires a [Roboflow API KEY](https://docs.roboflow.com/api-reference/authentication#retrieve-an-api-key). + + ```python + import supervision as sv + from PIL import Image + from inference import get_model + + image = Image.open("path/to/image.jpg") + model = get_model(model_id="rfdetr-small", api_key="ROBOFLOW_API_KEY") + result = model.infer(image)[0] + detections = sv.Detections.from_inference(result) + + len(detections) + # 5 + ``` + +
+ +### Annotators + +Supervision offers a wide range of highly customizable [annotators](https://supervision.roboflow.com/latest/detection/annotators/), allowing you to compose the perfect visualization for your use case. + +```python +import cv2 +import supervision as sv + +image = cv2.imread("path/to/image.jpg") +# Assuming detections are obtained from a model +detections = sv.Detections(...) + +box_annotator = sv.BoxAnnotator() +annotated_frame = box_annotator.annotate(scene=image.copy(), detections=detections) +``` + +https://github.com/roboflow/supervision/assets/26109316/691e219c-0565-4403-9218-ab5644f39bce + +### Datasets + +Supervision provides a set of [utils](https://supervision.roboflow.com/latest/datasets/core/) that allow you to load, split, merge, and save datasets in one of the supported formats. + +```python +import supervision as sv +from roboflow import Roboflow + +project = Roboflow().workspace("WORKSPACE_ID").project("PROJECT_ID") +dataset = project.version("PROJECT_VERSION").download("coco") + +ds = sv.DetectionDataset.from_coco( + images_directory_path=f"{dataset.location}/train", + annotations_path=f"{dataset.location}/train/_annotations.coco.json", +) + +path, image, annotation = ds[0] +# loads image on demand + +for path, image, annotation in ds: + # loads image on demand + pass +``` + +
+👉 more dataset utils + +- load + + ```python + dataset = sv.DetectionDataset.from_yolo( + images_directory_path=..., + annotations_directory_path=..., + data_yaml_path=..., + ) + + dataset = sv.DetectionDataset.from_pascal_voc( + images_directory_path=..., + annotations_directory_path=..., + ) + + dataset = sv.DetectionDataset.from_coco( + images_directory_path=..., + annotations_path=..., + ) + ``` + +- split + + ```python + train_dataset, test_dataset = dataset.split(split_ratio=0.7) + test_dataset, valid_dataset = test_dataset.split(split_ratio=0.5) + + len(train_dataset), len(test_dataset), len(valid_dataset) + # (700, 150, 150) + ``` + +- merge + + ```python + ds_1 = sv.DetectionDataset(...) + len(ds_1) + # 100 + ds_1.classes + # ['dog', 'person'] + + ds_2 = sv.DetectionDataset(...) + len(ds_2) + # 200 + ds_2.classes + # ['cat'] + + ds_merged = sv.DetectionDataset.merge([ds_1, ds_2]) + len(ds_merged) + # 300 + ds_merged.classes + # ['cat', 'dog', 'person'] + ``` + +- save + + ```python + dataset.as_yolo( + images_directory_path=..., + annotations_directory_path=..., + data_yaml_path=..., + ) + + dataset.as_pascal_voc( + images_directory_path=..., + annotations_directory_path=..., + ) + + dataset.as_coco( + images_directory_path=..., + annotations_path=..., + ) + ``` + +- convert + + ```python + sv.DetectionDataset.from_yolo( + images_directory_path=..., + annotations_directory_path=..., + data_yaml_path=..., + ).as_pascal_voc( + images_directory_path=..., + annotations_directory_path=..., + ) + ``` + +
+ +## 🎬 Tutorials + +Want to learn how to use Supervision? Explore our [how-to guides](https://supervision.roboflow.com/develop/how_to/detect_and_annotate/), [end-to-end examples](./examples), [cheatsheet](https://roboflow.github.io/cheatsheet-supervision/), and [cookbooks](https://supervision.roboflow.com/develop/cookbooks/)! + +
+ +

+Dwell Time Analysis with Computer Vision | Real-Time Stream Processing +Dwell Time Analysis with Computer Vision | Real-Time Stream Processing +

Created: 5 Apr 2024
+
Learn how to use computer vision to analyze wait times and optimize processes. This tutorial covers object detection, tracking, and calculating time spent in designated zones. Use these techniques to improve customer experience in retail, traffic management, or other scenarios.

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+Speed Estimation & Vehicle Tracking | Computer Vision | Open Source +Speed Estimation & Vehicle Tracking | Computer Vision | Open Source +

Created: 11 Jan 2024
+
Learn how to track and estimate the speed of vehicles using YOLO, ByteTrack, and Roboflow Inference. This comprehensive tutorial covers object detection, multi-object tracking, filtering detections, perspective transformation, speed estimation, visualization improvements, and more.

+ +## 💜 Built with Supervision + +Did you build something cool using supervision? [Let us know!](https://github.com/roboflow/supervision/discussions/categories/built-with-supervision) + +https://user-images.githubusercontent.com/26109316/207858600-ee862b22-0353-440b-ad85-caa0c4777904.mp4 + +https://github.com/roboflow/supervision/assets/26109316/c9436828-9fbf-4c25-ae8c-60e9c81b3900 + +https://github.com/roboflow/supervision/assets/26109316/3ac6982f-4943-4108-9b7f-51787ef1a69f + +## 📚 Documentation + +Visit our [documentation](https://roboflow.github.io/supervision) page to learn how supervision can help you build computer vision applications faster and more reliably. + +## 🏆 Contribution + +We love your input! Please see our [contributing guide](.github/CONTRIBUTING.md) to get started. Thank you 🙏 to all our contributors! + +

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