[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-72120":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":42,"readmeContent":43,"aiSummary":44,"trendingCount":16,"starSnapshotCount":16,"syncStatus":45,"lastSyncTime":46,"discoverSource":47},72120,"sports","roboflow\u002Fsports","roboflow","computer vision and sports","",null,"Python",5026,608,92,31,0,10,14,57,30,97.05,"MIT License",false,"main",true,[27,28,29,30,31,32,33,34,35,36,37,5,38,39,40,41],"computer-vision","deep-learning","deep-neural-networks","football","football-data","image-embeddings","keypoint-detection","object-detection","soccer","soccer-analytics","soccer-data","sports-analytics","sports-data","tutorial","visualization","2026-06-12 04:01:03","\u003Cdiv align=\"center\">\n\n  \u003Ch1>sports\u003C\u002Fh1>\n\n[notebooks](https:\u002F\u002Fgithub.com\u002Froboflow\u002Fnotebooks) | [inference](https:\u002F\u002Fgithub.com\u002Froboflow\u002Finference) | [autodistill](https:\u002F\u002Fgithub.com\u002Fautodistill\u002Fautodistill) | [maestro](https:\u002F\u002Fgithub.com\u002Froboflow\u002Fmultimodal-maestro)\n\n\u003C\u002Fdiv>\n\n## 👋 hello\n\nIn sports, every centimeter and every second matter. That's why Roboflow decided to use sports as a testing ground to push our object detection, image segmentation, keypoint detection, and foundational models to their limits. This repository contains reusable tools that can be applied in sports and beyond.\n\n## 🥵 challenges\n\nAre you also a fan of computer vision and sports?  We welcome contributions from anyone who shares our passion! Together, we can build powerful open-source tools for sports analytics. Here are the main challenges we're looking to tackle:\n\n- **Ball tracking:** Tracking the ball is extremely difficult due to its small size and rapid movements, especially in high-resolution videos.\n- **Reading jersey numbers:** Accurately reading player jersey numbers is often hampered by blurry videos, players turning away, or other objects obscuring the numbers.\n- **Player tracking:** Maintaining consistent player identification throughout a game is a challenge due to frequent occlusions caused by other players or objects on the field.\n- **Player re-identification:** Re-identifying players who have left and re-entered the frame is tricky, especially with moving cameras or when players are visually similar.\n- **Camera calibration:** Accurately calibrating camera views is crucial for extracting advanced statistics like player speed and distance traveled. This is a complex task due to the dynamic nature of sports and varying camera angles.\n\n## 💻 install\n\nWe don't have a Python package yet. Install from source in a\n[**Python>=3.8**](https:\u002F\u002Fwww.python.org\u002F) environment.\n\n```bash\npip install git+https:\u002F\u002Fgithub.com\u002Froboflow\u002Fsports.git\n```\n\n## ⚽ datasets\n\n| use case                               | dataset                                                                                                                                                           |\n|:---------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| ⚽ soccer player detection              | [![Download Dataset](https:\u002F\u002Fapp.roboflow.com\u002Fimages\u002Fdownload-dataset-badge.svg)](https:\u002F\u002Funiverse.roboflow.com\u002Froboflow-jvuqo\u002Ffootball-players-detection-3zvbc)  |\n| ⚽ soccer ball detection                | [![Download Dataset](https:\u002F\u002Fapp.roboflow.com\u002Fimages\u002Fdownload-dataset-badge.svg)](https:\u002F\u002Funiverse.roboflow.com\u002Froboflow-jvuqo\u002Ffootball-ball-detection-rejhg)     |\n| ⚽ soccer pitch keypoint detection      | [![Download Dataset](https:\u002F\u002Fapp.roboflow.com\u002Fimages\u002Fdownload-dataset-badge.svg)](https:\u002F\u002Funiverse.roboflow.com\u002Froboflow-jvuqo\u002Ffootball-field-detection-f07vi)    |\n| 🏀 basketball court keypoint detection | [![Download Dataset](https:\u002F\u002Fapp.roboflow.com\u002Fimages\u002Fdownload-dataset-badge.svg)](https:\u002F\u002Funiverse.roboflow.com\u002Froboflow-jvuqo\u002Fbasketball-court-detection-2)      |\n| 🏀 basketball jersey numbers ocr       | [![Download Dataset](https:\u002F\u002Fapp.roboflow.com\u002Fimages\u002Fdownload-dataset-badge.svg)](https:\u002F\u002Funiverse.roboflow.com\u002Froboflow-jvuqo\u002Fbasketball-jersey-numbers-ocr)     |\n\n\nVisit [Roboflow Universe](https:\u002F\u002Funiverse.roboflow.com\u002F) and explore other sport-related datasets.\n\n## 🔥 demos\n\nhttps:\u002F\u002Fgithub.com\u002Froboflow\u002Fsports\u002Fassets\u002F26109316\u002F7ad414dd-cc4e-476d-9af3-02dfdf029205\n\n## 🏆 contribution\n\nWe love your input! [Let us know](https:\u002F\u002Fgithub.com\u002Froboflow\u002Fsports\u002Fissues) what else we should build!\n","该项目旨在通过计算机视觉技术解决体育领域的挑战，特别是足球比赛中的目标检测、图像分割和关键点检测等问题。它利用深度学习模型来实现球跟踪、球员号码识别、球员跟踪及再识别等功能，并提供了一系列可用于这些任务的数据集。项目采用Python语言编写，适合需要进行体育数据分析或希望在实际应用中测试和改进计算机视觉算法的研究人员和技术爱好者使用。",2,"2026-06-11 03:40:27","high_star"]