# DataXujing/YOLOv8

:fire: Official YOLOv8模型训练和部署

Repository: https://github.com/DataXujing/YOLOv8
Canonical: https://ross.abutalabs.com/products/yolov8
Language: Python
License Family: other
Last push: 2024-11-15T05:41:19+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 95
- inputs: {"age_days": 1331, "days_push": 656, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1480, forks 174 (observed 2026-08-28T04:04:50.868902+00:00)

## What it is
A Chinese-language tutorial repository for training custom datasets with YOLOv8 (ultralytics 8.0.0) and deploying it end-to-end with NVIDIA TensorRT, Huawei Ascend acceleration, and Android mobile deployment. It includes explanatory material on YOLO architecture evolution and YOLOv5 vs YOLOv8 differences.

## Use cases
- train yolov8 on my own dataset
- deploy yolov8 with tensorrt
- convert yolov8 model for huawei ascend
- run yolov8 on android phone
- learn differences between yolov5 and yolov8
- object detection model training tutorial

## When to choose
- you want a guided walkthrough of YOLOv8 training plus TensorRT/Ascend/Android deployment
- you prefer Chinese-language documentation for the YOLO ecosystem

## When to avoid
- you need the official, maintained YOLOv8 package itself (use ultralytics/ultralytics)
- you need a permissively licensed library - this repo has no license
- you need deployment targets other than TensorRT, Ascend, or Android

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, computer-vision, image-processing, gpu-computing, deployment
- domain: deep-learning, computer-vision, tutorials, gpu-computing
- platform: python
- tags: yolo, object-detection, tensorrt, ascend, model-deployment, chinese-documentation, ultralytics, linux, android, gpu

## Member repositories
- DataXujing/YOLOv8 (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:50.868902+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:34:12.627092+00:00, confidence not recorded.
  - readme: https://github.com/DataXujing/YOLOv8 (fetched 2026-08-28T04:04:50.868902+00:00, sha 3404f469d7a4)
- Data as of 2026-08-30T08:39:29.467469+00:00.