---

name: ocr-super-surya description: "GPU-optimized OCR using Surya. Use when: (1) Extracting text from images/screenshots, (2) Processing PDFs with embedded images, (3) Multi-language document OCR, (4) Layout analysis and table detection. Supports 90+ languages with 2x accuracy over Tesseract." license: CC BY-NC-SA 4.0 metadata: author: yamapan (https://github.com/aktsmm)

OCR Super Surya

GPU-optimized OCR using Surya.

When to Use

• OCR, extract text from image, text recognition, 画像から文字
• Extracting text from screenshots, photos, or scanned images
• Processing PDFs with embedded images
• Multi-language document OCR (90+ languages including Japanese)

Features

| Feature | Description | | ------------- | --------------------------------------- | | Accuracy | 2x better than Tesseract (0.97 vs 0.88) | | GPU | PyTorch-based, CUDA optimized | | Languages | 90+ including CJK | | Layout | Document layout, table recognition |

Quick Start

Installation

# 1. Check GPU
python -c "import torch; print(f'CUDA: {torch.cuda.is_available()}')"

# 2. Install (with CUDA if GPU available)
pip install surya-ocr

# If CUDA=False but you have GPU, reinstall PyTorch:
pip uninstall torch torchvision torchaudio -y
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121

Windows + uv 環境（OneDrive配下でのインストール）

OneDrive 配下のフォルダでは uv のハードリンクが失敗するため、以下の手順を使う：

# キャッシュをOneDrive外に設定
$env:UV_CACHE_DIR = "C:\Temp\uv_cache"

# 仮想環境をOneDrive外に作成
uv venv C:\Users\<USERNAME>\ocr_env --python 3.12

# surya-ocrをインストール（link-mode=copy でハードリンクを回避）
uv pip install surya-ocr --python C:\Users\<USERNAME>\ocr_env\Scripts\python.exe --link-mode=copy

# transformers 5.x は非互換 → 4.x を強制
uv pip install "transformers<5.0" --python C:\Users\<USERNAME>\ocr_env\Scripts\python.exe --link-mode=copy

Usage

# CLI
python scripts/ocr_helper.py image.png
python scripts/ocr_helper.py document.pdf -l ja en -o result.txt

# Or use surya directly
surya_ocr image.png --output_dir ./results

Python API

import sys, io
# Windows CP932エンコードエラー対策
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')

from PIL import Image
from surya.recognition import RecognitionPredictor
from surya.detection import DetectionPredictor
from surya.foundation import FoundationPredictor

image = Image.open("document.png").convert("RGB")
found_pred = FoundationPredictor()
rec_pred = RecognitionPredictor(found_pred)  # v0.13+ : FoundationPredictor必須
det_pred = DetectionPredictor()

# v0.17.x以降: langs引数は廃止 → 渡さないこと
for page in rec_pred([image], det_predictor=det_pred):
    for line in page.text_lines:
        if line.text.strip():
            print(line.text)

API変更履歴 (v0.17.x):

• RecognitionPredictor(foundation_predictor) - FoundationPredictor が必須引数に変更
• __call__() から langs 引数が削除（自動検出に変更）

GPU Configuration

| Variable | Default | Description | | ------------------------ | ------- | --------------------- | | RECOGNITION_BATCH_SIZE | 512 | Reduce for lower VRAM | | DETECTOR_BATCH_SIZE | 36 | Reduce if OOM |

export RECOGNITION_BATCH_SIZE=256
surya_ocr image.png

Scripts

| Script | Description | | ----------------------- | ----------------------------------------- | | scripts/ocr_helper.py | Helper with OOM auto-retry, batch support |

Troubleshooting

| エラー | 原因 | 対処 | | ------ | ---- | ---- | | RecognitionPredictor.__init__() missing 1 required positional argument: 'foundation_predictor' | v0.13+ でAPIが変更 | found_pred = FoundationPredictor() を作成して引数に渡す | | TypeError: __call__() got an unexpected keyword argument 'langs' | v0.17.x で langs 引数廃止 | langs 引数を削除する | | AttributeError: 'SuryaDecoderConfig' object has no attribute 'pad_token_id' | transformers 5.x との非互換 | pip install "transformers<5.0" でダウングレード | | failed to hardlink file ... OneDrive (uv, os error 396) | OneDrive のハードリンク制限 | --link-mode=copy を付けてインストール＋UV_CACHE_DIR をOneDrive外に設定 | | UnicodeEncodeError: 'cp932' codec can't encode character | Windows のCP932デフォルトエンコード | sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8') を先頭に追加 |

License Note

• Surya: GPL-3.0 (code), commercial license required for >$2M revenue