{"id":22979375,"url":"https://github.com/jparedesds/ai-yolo","last_synced_at":"2025-04-02T09:15:43.083Z","repository":{"id":264652907,"uuid":"864295511","full_name":"jparedesDS/AI-YOLO","owner":"jparedesDS","description":"AI-YOLO Project Object Detection / Computer Vision","archived":false,"fork":false,"pushed_at":"2025-03-18T11:24:30.000Z","size":45,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-18T12:28:25.911Z","etag":null,"topics":["computer-vision","model","object-detection","opencv","tensorflow","torch","track-detection","ultralytics","yolo","yolo11","yolov10","yolov9"],"latest_commit_sha":null,"homepage":"https://huggingface.co/jparedesDS","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jparedesDS.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-09-27T21:56:55.000Z","updated_at":"2025-03-18T11:24:34.000Z","dependencies_parsed_at":"2025-02-08T00:23:29.567Z","dependency_job_id":"76b3a075-296c-49f1-825c-722c17c69b3c","html_url":"https://github.com/jparedesDS/AI-YOLO","commit_stats":null,"previous_names":["jparedesds/ai-yolo"],"tags_count":6,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jparedesDS%2FAI-YOLO","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jparedesDS%2FAI-YOLO/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jparedesDS%2FAI-YOLO/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jparedesDS%2FAI-YOLO/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jparedesDS","download_url":"https://codeload.github.com/jparedesDS/AI-YOLO/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246785487,"owners_count":20833497,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer-vision","model","object-detection","opencv","tensorflow","torch","track-detection","ultralytics","yolo","yolo11","yolov10","yolov9"],"created_at":"2024-12-15T01:30:13.376Z","updated_at":"2025-04-02T09:15:43.038Z","avatar_url":"https://github.com/jparedesDS.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI-YOLO  \n**All my YOLO-based models for various applications**  \n\n## Table of Contents  \n- [Overview](#overview)  \n- [Metallurgical Applications](#metallurgical-applications)  \n- [Counter-Strike 2 Object Detection](#counter-strike-2-object-detection)  \n- [Valorant Object Detection](#valorant-object-detection)  \n- [Deadlock Object Detection](#deadlock-object-detection)  \n- [Overwatch 2 Object Detection](#overwatch-2-object-detection)\n- [Fortnite Object Detection](#fortnite-object-detection) \n- [How to Use the Models](#how-to-use-the-models)  \n- [All Models](#all-models)  \n\n---\n\n## Overview  \nThis repository showcases my YOLO models, customized for diverse applications, including industrial, gaming, and general object detection tasks. From metallurgical inspections to in-game object detection, these models leverage cutting-edge deep learning to achieve high precision.  \n\n---\n\n## Metallurgical Applications  \n### Fluorescent Penetrant Inspection  \n- **Model**: YOLO11l  \n- **Details**: Optimized for detecting defects in fluorescent penetrant inspections.  \n- [Access Model on Hugging Face](https://huggingface.co/jparedesDS/fluorescent-penetrant-inspection)  \n\n### Welding Defects Detection  \n- **Model**: YOLO11x  \n- **Details**: Designed to identify welding defects with high accuracy.  \n- [Access Model on Hugging Face](https://huggingface.co/jparedesDS/welding-defects-detection)  \n\n---\n\n## Counter-Strike 2 Object Detection  \nYOLO models tailored for detecting objects and events in Counter-Strike 2.  \n\n- **YOLOv9c**: [Hugging Face Link](https://huggingface.co/jparedesDS/cs2-yolov9c)  \n- **YOLOv10s**: [Hugging Face Link](https://huggingface.co/jparedesDS/cs2-yolov10s)  \n- **YOLOv10m**: [Hugging Face Link](https://huggingface.co/jparedesDS/cs2-yolov10m)  \n- **YOLOv10b**: [Hugging Face Link](https://huggingface.co/jparedesDS/cs2-yolov10b)  \n\n---\n\n## Valorant Object Detection  \nModels designed to detect in-game objects in Valorant.  \n\n- **YOLOv10b**: [Hugging Face Link](https://huggingface.co/jparedesDS/valorant-yolov10b)  \n- **YOLO11m**: [Hugging Face Link](https://huggingface.co/jparedesDS/valorant-yolo11m)  \n\n---\n\n## Deadlock Object Detection  \nCustom YOLO models for detecting objects in **Deadlock**.  \n\n- **YOLO11l**: [Hugging Face Link](https://huggingface.co/jparedesDS/deadlock-yolo11l)  \n\n---\n\n## Overwatch 2 Object Detection  \nAdvanced object detection for Overwatch 2.  \n\n- **YOLO11m**: [Hugging Face Link](https://huggingface.co/jparedesDS/ow2-yolo11m)  \n\n---\n\n## Fortnite Object Detection  \nAdvanced object detection for Fortnite.  \n\n- **YOLO11m**: [Hugging Face Link](https://huggingface.co/jparedesDS/fortnite-yolo11m)\n\n---\n\n## How to Use the Models  \nEasily integrate the models into your projects using the `ultralytics` library.  \n\n```python  \nfrom ultralytics import YOLO  \n\n# Load a pretrained YOLO model  \nmodel = YOLO(r'your_model.pt')  \n\n# Run inference on an image  \nmodel.predict(  \n    'image.png',  \n    save=True,  \n    device=0  \n)  \n```\n\n## All Models\nYou can find all my models on Hugging Face:\nhttps://huggingface.co/jparedesDS\n\n## Contributing\nIf you'd like to contribute, feel free to open an issue or submit a pull request.\n\n## License\nThis repository is licensed under the MIT License. See the LICENSE file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjparedesds%2Fai-yolo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjparedesds%2Fai-yolo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjparedesds%2Fai-yolo/lists"}