persian-license-plate-recognition
PLPR utilizes YOLOv5 and custom models for high-accuracy Persian license plate recognition
GraphCanon updated 3w · GitHub synced 3w
Decision brief
The persian-license-plate-recognition tool uses YOLOv5 and custom models to identify Persian license plates with real-time processing capabilities.
Good fit when
- When you need software specifically calibrated for recognizing Persian license plate formats.
- For applications requiring real-time processing of video streams or images for high accuracy in identifying vehicles registered within the Persian region.
Avoid when
- If your project involves other types of license plates that are not specific to Persia, as the tool is optimized exclusively for Persian license plate formats.
- For environments with hardware below the recommended specifications; this system requires a dedicated GPU and significant RAM for efficient real-time processing.
- Requirements:
- Min 8 GB RAM; Requires an NVIDIA GPU with at least 4 GB of VRAM or equivalent for efficient real-time processing.; Compatible with Windows 10/11, Linux (Ubuntu 18.04 or later), and macOS (10.14 Mojave or later).; The system must have an SSD with at least 20 GB of free space.
Observed Jul 16, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (775d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No criticals
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install persian-license-plate-recognitionSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
The PLPR system is designed to detect and recognize Persian license plates in images and video streams with real-time processing
Capability facts
- Languages
- python
Source: github.language · Aug 1, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 1, 2026)
2. Install the required Python packages:Source link
Tags
README
🚗 Persian License Plate Recognition System (PLPR)
The Persian License Plate Recognition (PLPR) system is a state-of-the-art solution designed for detecting and recognizing Persian license plates in images and video streams. Leveraging advanced deep learning models and a user-friendly interface, it ensures reliable performance across different scenarios.
💻 System Hardware Requirements
To ensure optimal performance of the Persian License Plate Recognition System (PLPR), the following hardware specifications are recommended:
- Processor: Intel Core i5 (8th Gen) or equivalent/higher.
- Memory: 8 GB RAM or more.
- Graphics: Dedicated GPU (NVIDIA GTX 1060 or equivalent) with at least 4 GB VRAM for efficient real-time processing and deep learning model computations.
- Storage: SSD with at least 20 GB of free space for software, models, and datasets.
- Operating System: Compatible with Windows 10/11, Linux (Ubuntu 18.04 or later), and macOS (10.14 Mojave or later).
These specifications are designed to handle the computational demands of advanced deep learning models, real-time video processing, and high-volume data management integral to the PLPR system. Adjustments may be necessary based on specific deployment scenarios and performance expectations.
🔧 Installation
- Clone the repository and navigate to its directory:
git clone https://github.com/mtkarimi/smart-resident-guard.git cd smart-resident-guard - Install the required Python packages:
pip install -r requirements.txt
📄 License
GPL-3.0. See the LICENSE file for details. It means you can:
- Share Source Code: If you distribute binaries or modified versions, you must make the source code available under GPL-3.
- License: Must keep and apply GPL-3 to the modified work.
- State Modifications: If modified, must disclose that it was changed.
For agents
This page has a .md twin and JSON over the API.