{"id":50497450,"url":"https://github.com/lhlizdabezt/nhapmonai","last_synced_at":"2026-06-02T09:01:04.909Z","repository":{"id":357618097,"uuid":"1237714649","full_name":"lhlizdabezt/NhapMonAI","owner":"lhlizdabezt","description":"Vietnamese ALPR project using YOLO/PyTorch and OCR/FastALPR with Kaggle/IPYNB training evidence, desktop inference and LAN demo scope.","archived":false,"fork":false,"pushed_at":"2026-06-02T06:49:05.000Z","size":65118,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-06-02T07:26:17.372Z","etag":null,"topics":["computer-vision","kaggle","machine-learning","ocr","opencv","pytorch","yolo"],"latest_commit_sha":null,"homepage":"https://github.com/lhlizdabezt/NhapMonAI/releases/latest","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Vietnamese Automatic License Plate Recognition with YOLO and OCR\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://github.com/lhlizdabezt/NhapMonAI/releases/latest\"\u003e\u003cimg src=\"https://img.shields.io/github/v/release/lhlizdabezt/NhapMonAI?style=for-the-badge\u0026logo=github\u0026label=Release\" alt=\"Latest release for NhapMonAI\" /\u003e\u003c/a\u003e\n  \u003ca href=\"https://github.com/lhlizdabezt/NhapMonAI/tags\"\u003e\u003cimg src=\"https://img.shields.io/github/v/tag/lhlizdabezt/NhapMonAI?style=for-the-badge\u0026logo=git\u0026label=Tag\" alt=\"Latest tag for NhapMonAI\" /\u003e\u003c/a\u003e\n  \u003cimg src=\"https://img.shields.io/badge/Portfolio-English%20review%20ready-0f766e?style=for-the-badge\" alt=\"English portfolio ready\" /\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"assets/portfolio-motion.svg\" alt=\"Animated engineering portfolio visual for NhapMonAI\" width=\"100%\" /\u003e\n\u003c/p\u003e\n\n\n## Overview\n\nThis repository presents a Vietnamese automatic license plate recognition workflow that combines YOLO/PyTorch detection, OCR/FastALPR recognition, Kaggle/IPYNB training evidence, a Python desktop application and a LAN-based PlateGate PC demo.\n\n| Field | Details |\n|---|---|\n| Repository | [NhapMonAI](https://github.com/lhlizdabezt/NhapMonAI) |\n| Portfolio category | Computer vision / machine learning course project |\n| Primary stack | Python, PyTorch, Ultralytics YOLO, OpenCV, FastALPR, fast-plate-ocr, FFmpeg, Tkinter, Kaggle, IPYNB, Typst, Git LFS. |\n| Latest release | [GitHub Releases](https://github.com/lhlizdabezt/NhapMonAI/releases/latest) |\n| Tags | [Version tags](https://github.com/lhlizdabezt/NhapMonAI/tags) |\n| Owner profile | [Luong Hai Long](https://github.com/lhlizdabezt) |\n\n## Reviewer Map\n\n| What to Review | Where to Look | Why It Matters |\n|---|---|---|\n| Technical scope | This README and source tree | Gives a quick, bounded reading path before opening every file |\n| Evidence assets | Release page and top-level project files | Shows what can be downloaded or inspected quickly |\n| Implementation material | Source folders, scripts, notebooks or design files | Connects the portfolio claim to real project artifacts |\n| Version history | Tags and release notes | Makes the repository easier to audit over time |\n\n## Evidence Highlights\n\n- YOLO detector with reported mAP50 0.99450 on the project validation set.\n- OCR pipeline using FastALPR / fast-plate-ocr concepts with plate-crop normalization.\n- Python desktop app for image/video inference and a PlateGate PC LAN prototype with health and scan endpoints.\n- Typst report, seminar slides, motion GIF, reviewer card, Git LFS-managed assets and release packages.\n\n## Repository Structure\n\n| Path | Purpose |\n|---|---|\n| `Academic_Deliverables/` | Top-level directory included in the repository |\n| `AppPythonPlateGatePC/` | Top-level directory included in the repository |\n| `AppPythonYOLO_OCR/` | Top-level directory included in the repository |\n| `assets/` | Top-level directory included in the repository |\n| `Group5_BaoCaoNhapMonAI/` | Top-level directory included in the repository |\n| `Group5_Notebook_IPYNB/` | Top-level directory included in the repository |\n| `HinhAnhBaoCao/` | Top-level directory included in the repository |\n| `Group5_BaoCaoSeminarNhapMonAI.pdf` | Top-level file included in the repository |\n\n## Scope and Boundaries\n\nAcademic team project and portfolio archive. The detector metrics are tied to the project validation set; the OCR and gate-control components are prototypes, not production traffic-enforcement systems.\n\n## Role and Portfolio Context\n\nLuong Hai Long maintained the public repository and release packaging, and co-developed the Python desktop and PlateGate PC demo within the team context.\n\n## Release and Tagging Notes\n\nThis repository is maintained as part of an English-facing engineering portfolio. Releases and tags are used to preserve reviewable snapshots of the project, including source state, documentation updates and any available visual or report assets.\n\n## Writing Standard\n\nThe README follows an evidence-first style: direct technical nouns, clear project boundaries, release-backed artifacts and no inflated claims beyond what the repository can support.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flhlizdabezt%2Fnhapmonai","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flhlizdabezt%2Fnhapmonai","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flhlizdabezt%2Fnhapmonai/lists"}