PP-OCRV1

Key Features:

• Lightweight Architecture: Optimized for fast inference on CPUs and edge devices.

• English & Chinese Support: Primarily focused on these two languages.

• Single-Step Detection & Recognition: Uses a simple CNN + LSTM-based approach.

• Moderate Accuracy: Works well on clean documents but struggles with complex layouts or noisy backgrounds.

• Open-Source Availability: Released to encourage community adoption and improvements.

Model Deployment Status:

General Availability Yes (Open-source)

Supported Data Types for Input Image (PNG, JPG)

Supported Data Types for Output Text

Supported # Tokens for Input Single image (max 1024x1024 px)

Supported # Tokens for Output 1k (basic text extraction)

Knowledge Cutoff December 2021

Tool Use None (standalone OCR)

Best For

• Lightweight document scanning

• Basic text extraction (English/Chinese)

• Availability:

  • GitHub (PaddleOCR)

  • Edge devices