chore: archive upgrade-ppstructure-models proposal
Archived as 2025-11-27-upgrade-ppstructure-models Spec updated: ocr-processing (added PP-StructureV3 Configuration) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
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# PP-StructureV3 Model Cache Cleanup Guide
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## Overview
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After upgrading PP-StructureV3 models, older unused models may remain in the cache directory. This guide explains how to safely remove them to free disk space.
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## Model Cache Location
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PaddleX/PaddleOCR 3.x stores downloaded models in:
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```
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~/.paddlex/official_models/
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```
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## Models After Upgrade
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### Current Active Models (DO NOT DELETE)
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| Model | Purpose | Approx. Size |
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|-------|---------|--------------|
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| `PP-DocLayout_plus-L` | Layout detection for Chinese documents | ~350MB |
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| `SLANeXt_wired` | Table structure recognition (bordered tables) | ~351MB |
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| `SLANeXt_wireless` | Table structure recognition (borderless tables) | ~351MB |
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| `PP-FormulaNet_plus-L` | Formula recognition (Chinese + English) | ~800MB |
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| `PP-OCRv5_*` | Text detection and recognition | ~150MB |
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| `picodet_lcnet_x1_0_fgd_layout_cdla` | CDLA layout model option | ~10MB |
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### Deprecated Models (Safe to Delete)
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| Model | Reason | Approx. Size |
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|-------|--------|--------------|
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| `PP-DocLayout-S` | Replaced by PP-DocLayout_plus-L | ~50MB |
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| `SLANet` | Replaced by SLANeXt_wired/wireless | ~7MB |
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| `SLANet_plus` | Replaced by SLANeXt_wired/wireless | ~7MB |
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| `PP-FormulaNet-S` | Replaced by PP-FormulaNet_plus-L | ~200MB |
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| `PP-FormulaNet-L` | Replaced by PP-FormulaNet_plus-L | ~400MB |
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## Cleanup Commands
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### List Current Cache
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```bash
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# List all cached models
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ls -la ~/.paddlex/official_models/
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# Show disk usage per model
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du -sh ~/.paddlex/official_models/*
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```
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### Delete Deprecated Models
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```bash
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# Remove deprecated layout model
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rm -rf ~/.paddlex/official_models/PP-DocLayout-S
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# Remove deprecated table models
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rm -rf ~/.paddlex/official_models/SLANet
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rm -rf ~/.paddlex/official_models/SLANet_plus
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# Remove deprecated formula models (if present)
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rm -rf ~/.paddlex/official_models/PP-FormulaNet-S
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rm -rf ~/.paddlex/official_models/PP-FormulaNet-L
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```
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### Cleanup Script
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```bash
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#!/bin/bash
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# cleanup_old_models.sh - Remove deprecated PP-StructureV3 models
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CACHE_DIR="$HOME/.paddlex/official_models"
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echo "PP-StructureV3 Model Cleanup"
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echo "============================"
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echo ""
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# Check if cache directory exists
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if [ ! -d "$CACHE_DIR" ]; then
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echo "Cache directory not found: $CACHE_DIR"
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exit 0
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fi
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# List deprecated models
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DEPRECATED_MODELS=(
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"PP-DocLayout-S"
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"SLANet"
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"SLANet_plus"
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"PP-FormulaNet-S"
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"PP-FormulaNet-L"
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)
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echo "Checking for deprecated models..."
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echo ""
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TOTAL_SIZE=0
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for model in "${DEPRECATED_MODELS[@]}"; do
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MODEL_PATH="$CACHE_DIR/$model"
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if [ -d "$MODEL_PATH" ]; then
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SIZE=$(du -sh "$MODEL_PATH" 2>/dev/null | cut -f1)
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echo "Found: $model ($SIZE)"
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TOTAL_SIZE=$((TOTAL_SIZE + 1))
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fi
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done
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if [ $TOTAL_SIZE -eq 0 ]; then
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echo "No deprecated models found. Cache is clean."
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exit 0
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fi
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echo ""
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read -p "Delete these models? [y/N]: " confirm
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if [ "$confirm" = "y" ] || [ "$confirm" = "Y" ]; then
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for model in "${DEPRECATED_MODELS[@]}"; do
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MODEL_PATH="$CACHE_DIR/$model"
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if [ -d "$MODEL_PATH" ]; then
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rm -rf "$MODEL_PATH"
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echo "Deleted: $model"
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fi
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done
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echo ""
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echo "Cleanup complete."
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else
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echo "Cleanup cancelled."
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fi
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```
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## Space Savings Estimate
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After cleanup, you can expect to free approximately:
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- **~65MB** from deprecated layout model
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- **~14MB** from deprecated table models
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- **~600MB** from deprecated formula models (if present)
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Total potential savings: **~680MB**
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## Notes
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1. Models are downloaded on first use. Deleting active models will trigger re-download.
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2. The cache directory may vary if `PADDLEX_HOME` environment variable is set.
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3. Always verify which models your configuration uses before deleting.
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# Upgrade PP-StructureV3 Models
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## Why
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目前專案使用的 PP-StructureV3 模型配置存在以下問題:
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1. **版面偵測模型精度不足**:PP-DocLayout-S (70.9% mAP) 無法正確處理複雜表格和版面
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2. **表格識別準確率低**:SLANet (59.52%) 產出錯誤的 HTML 結構
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3. **預處理模組未啟用**:文檔方向校正和彎曲校正功能關閉
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4. **模型佔用空間過大**:下載了不使用的模型,浪費儲存空間
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## What Changes
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### Stage 1: 預處理模組 - 全部開啟
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| 功能 | 當前 | 變更後 |
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|-----|-----|-------|
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| `use_doc_orientation_classify` | False | **True** |
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| `use_doc_unwarping` | False | **True** |
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| `use_textline_orientation` | False | **True** |
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### Stage 2: OCR 模組 - 維持現狀
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- 繼續使用 PP-OCRv5 (預設配置)
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- 不需要更改
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### Stage 3: 版面分析模組 - 升級模型選項
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| 選項名稱 | 當前模型 | 變更後模型 | mAP |
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|---------|---------|-----------|-----|
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| `chinese` | PP-DocLayout-S (移除) | **PP-DocLayout_plus-L** | 83.2% |
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| `default` | PubLayNet | PubLayNet (維持) | ~94% |
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| `cdla` | CDLA | CDLA (維持) | ~86% |
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**重點變更**:
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- 移除 PP-DocLayout-S (70.9% mAP)
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- 新增 PP-DocLayout_plus-L (83.2% mAP, 20類別)
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- 前端「中文文檔」選項改用 PP-DocLayout_plus-L
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### Stage 4: 元素識別模組 - 升級表格識別
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| 模組 | 當前模型 | 變更後模型 | 準確率變化 |
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|-----|---------|-----------|-----------|
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| 表格識別 | SLANet (預設) | **SLANeXt_wired + SLANeXt_wireless** | 59.52% → 69.65% |
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| 公式識別 | PP-FormulaNet (預設) | **PP-FormulaNet_plus-L** | 45.78% → 90.64% (中文) |
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| 圖表解析 | PP-Chart2Table | PP-Chart2Table (維持) | - |
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| 印章識別 | PP-OCRv4_seal | PP-OCRv4_seal (維持) | - |
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**表格識別策略**:
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- SLANeXt_wired 和 SLANeXt_wireless 搭配使用
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- 先用分類器判斷有線/無線表格類型
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- 根據類型選擇對應的 SLANeXt 模型
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- 聯合測試準確率達 69.65%
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### 儲存空間優化 - 刪除未使用模型
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PaddleOCR 3.x 模型緩存位置:`~/.paddlex/official_models/`
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可刪除的模型目錄:
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- PP-DocLayout-S (被 PP-DocLayout_plus-L 取代)
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- SLANet (被 SLANeXt 取代)
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- 其他未使用的舊版模型
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**注意**:刪除後首次使用新模型會觸發下載
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## Requirements
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### REQ-1: 預處理模組開啟
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系統 **SHALL** 在 PP-StructureV3 初始化時啟用所有預處理功能:
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- 文檔方向分類 (use_doc_orientation_classify=True)
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- 文檔彎曲校正 (use_doc_unwarping=True)
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- 文字行方向偵測 (use_textline_orientation=True)
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**Scenario: 處理旋轉的掃描文檔**
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- Given 一個旋轉 90 度的 PDF 文檔
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- When 使用 OCR track 處理
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- Then 系統應自動校正方向後再進行 OCR
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### REQ-2: 版面模型升級
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系統 **SHALL** 將「chinese」選項對應的模型從 PP-DocLayout-S 更改為 PP-DocLayout_plus-L
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**Scenario: 處理中文複雜文檔**
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- Given 包含表格、圖片、公式的中文文檔
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- When 選擇「chinese」版面模型處理
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- Then 應使用 PP-DocLayout_plus-L (83.2% mAP) 進行版面分析
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### REQ-3: 表格識別升級
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系統 **SHALL** 使用 SLANeXt_wired 和 SLANeXt_wireless 搭配進行表格識別
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**Scenario: 處理有線表格**
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- Given 包含有線表格的文檔
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- When 進行表格結構識別
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- Then 應使用 SLANeXt_wired 模型
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- And 輸出正確的 HTML 表格結構
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**Scenario: 處理無線表格**
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- Given 包含無線表格的文檔
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- When 進行表格結構識別
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- Then 應使用 SLANeXt_wireless 模型
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### REQ-4: 公式識別升級
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系統 **SHALL** 使用 PP-FormulaNet_plus-L 進行公式識別以支援中文公式
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### REQ-5: 模型緩存清理
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系統 **SHOULD** 提供工具或文檔說明如何清理未使用的模型緩存以節省儲存空間
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## Model Comparison Data
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### 表格識別模型對比
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| 模型 | 準確率 | 推理時間 | 模型大小 | 適用場景 |
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|-----|-------|---------|---------|---------|
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| SLANet | 59.52% | 24ms | 6.9 MB | ❌ 準確率不足 |
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| SLANet_plus | 63.69% | 23ms | 6.9 MB | ❌ 仍不足 |
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| **SLANeXt_wired** | 69.65% | 86ms | 351 MB | ✅ 有線表格 |
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| **SLANeXt_wireless** | 69.65% | - | 351 MB | ✅ 無線表格 |
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**結論**:SLANeXt 系列比 SLANet/SLANet_plus 準確率高約 10%,但模型大小增加約 50 倍。考慮到表格識別是核心功能,建議升級。
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### 版面偵測模型對比
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| 模型 | 類別數 | mAP | 推理時間 | 適用場景 |
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|-----|-------|-----|---------|---------|
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| PP-DocLayout-S | 23 | 70.9% | 12ms | ❌ 精度不足 |
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| PP-DocLayout-L | 23 | 90.4% | 34ms | ✅ 通用高精度 |
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| **PP-DocLayout_plus-L** | 20 | 83.2% | 53ms | ✅ 複雜文檔推薦 |
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## References
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- [PaddleOCR Table Structure Recognition](http://www.paddleocr.ai/main/en/version3.x/module_usage/table_structure_recognition.html)
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- [SLANeXt_wired on HuggingFace](https://huggingface.co/PaddlePaddle/SLANeXt_wired)
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- [SLANeXt_wireless on HuggingFace](https://huggingface.co/PaddlePaddle/SLANeXt_wireless)
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- [PP-StructureV3 Technical Report](https://arxiv.org/html/2507.05595v1)
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- [PaddleOCR Model Cache Issue](https://github.com/PaddlePaddle/PaddleOCR/issues/10234)
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## ADDED Requirements
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### Requirement: PP-StructureV3 Configuration
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The system SHALL configure PP-StructureV3 with the following settings:
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**Preprocessing (Stage 1):**
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- Document orientation classification MUST be enabled (`use_doc_orientation_classify=True`)
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- Document unwarping MUST be enabled (`use_doc_unwarping=True`)
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- Textline orientation detection MUST be enabled (`use_textline_orientation=True`)
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**Layout Detection (Stage 3):**
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- The `chinese` layout model option SHALL use PP-DocLayout_plus-L (83.2% mAP)
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- The `default` layout model option SHALL use PubLayNet for English documents
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- The `cdla` layout model option SHALL use picodet_lcnet_x1_0_fgd_layout_cdla
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**Element Recognition (Stage 4):**
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- Table structure recognition SHALL use SLANeXt_wired and SLANeXt_wireless models (69.65% combined accuracy)
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- Formula recognition SHALL use PP-FormulaNet_plus-L (92.22% English, 90.64% Chinese BLEU)
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- Chart parsing SHALL use PP-Chart2Table
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- Seal recognition SHALL use PP-OCRv4_seal
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#### Scenario: Processing rotated scanned document
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- **WHEN** a PDF document with rotated pages is processed using OCR track
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- **THEN** the system SHALL automatically detect and correct the orientation before OCR processing
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#### Scenario: Processing complex Chinese document with tables
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- **WHEN** a Chinese document containing tables, images, and formulas is processed
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- **AND** the user selects "chinese" layout model
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- **THEN** the system SHALL use PP-DocLayout_plus-L for layout detection (83.2% mAP)
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- **AND** the system SHALL correctly identify table regions
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#### Scenario: Table structure recognition with wired tables
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- **WHEN** a document contains wired (bordered) tables
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- **THEN** the system SHALL use SLANeXt_wired model for structure recognition
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- **AND** output correct HTML table structure with proper row/column spanning
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#### Scenario: Table structure recognition with wireless tables
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- **WHEN** a document contains wireless (borderless) tables
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- **THEN** the system SHALL use SLANeXt_wireless model for structure recognition
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#### Scenario: Chinese formula recognition
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- **WHEN** a document contains mathematical formulas with Chinese characters
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- **THEN** the system SHALL use PP-FormulaNet_plus-L for recognition
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- **AND** output LaTeX code with correct Chinese character representation
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## ADDED Requirements
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### Requirement: Model Cache Cleanup
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The system SHALL provide documentation for cleaning up unused model caches to optimize storage space.
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#### Scenario: User wants to free disk space after model upgrade
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- **WHEN** the user has upgraded from older models (PP-DocLayout-S, SLANet) to newer models
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- **THEN** the documentation SHALL explain how to delete unused cached models from `~/.paddlex/official_models/`
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- **AND** list which model directories can be safely removed
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@@ -0,0 +1,77 @@
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# Tasks: Upgrade PP-StructureV3 Models
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## 1. Backend Configuration Changes
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- [x] 1.1 Update `backend/app/core/config.py` - Enable preprocessing flags
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- Set `use_doc_orientation_classify` default to True
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- Set `use_doc_unwarping` default to True
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- Set `use_textline_orientation` default to True
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- Add `table_structure_model_name` configuration
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- Add `formula_recognition_model_name` configuration
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- [x] 1.2 Update `backend/app/services/ocr_service.py` - Model mapping changes
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- Update `LAYOUT_MODEL_MAPPING`:
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- Change `"chinese"` from `"PP-DocLayout-S"` to `"PP-DocLayout_plus-L"`
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- Keep `"default"` as PubLayNet
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- Keep `"cdla"` as is
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- Update `_ensure_structure_engine()`:
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- Pass preprocessing flags to PPStructureV3
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- Configure SLANeXt models for table recognition
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- Configure PP-FormulaNet_plus-L for formula recognition
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- [x] 1.3 Update PPStructureV3 initialization kwargs
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- Add `table_structure_model_name="SLANeXt_wired"` (or configure dual model)
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- Add `formula_recognition_model_name="PP-FormulaNet_plus-L"`
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- Verify preprocessing flags are passed correctly
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## 2. Schema Updates
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- [x] 2.1 Update `backend/app/schemas/task.py` - LayoutModelEnum
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- Rename or update `CHINESE` description to reflect PP-DocLayout_plus-L
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- Update docstrings to reflect new model capabilities
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## 3. Frontend Updates
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- [x] 3.1 Update `frontend/src/components/LayoutModelSelector.tsx`
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- Update Chinese option description to mention PP-DocLayout_plus-L
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- Update accuracy information displayed to users
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- [x] 3.2 Update `frontend/src/i18n/locales/zh-TW.json`
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- Update `layoutModel.chinese.description` to reflect new model
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- Update any accuracy percentages in descriptions
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## 4. Testing
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- [x] 4.1 Create unit tests for new model configuration
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- Test preprocessing flags are correctly passed
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- Test model mapping resolves correctly
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- Test engine initialization with new models
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- [ ] 4.2 Integration testing with real documents
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- Test rotated document handling (preprocessing)
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- Test complex Chinese document layout detection
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- Test table structure recognition accuracy
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- Test formula recognition with Chinese formulas
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- [x] 4.3 Update existing tests
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- Update `backend/tests/services/test_layout_model.py` for new mapping
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- Update `backend/tests/api/test_layout_model_api.py` if needed
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## 5. Documentation
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|
||||
- [x] 5.1 Create model cleanup documentation
|
||||
- Document `~/.paddlex/official_models/` cache location
|
||||
- List models that can be safely deleted after upgrade
|
||||
- Provide cleanup script/commands
|
||||
- See: [MODEL_CLEANUP.md](./MODEL_CLEANUP.md)
|
||||
|
||||
- [x] 5.2 Update API documentation
|
||||
- Document preprocessing feature behavior
|
||||
- Update layout model descriptions
|
||||
|
||||
## 6. Verification & Deployment
|
||||
|
||||
- [ ] 6.1 Verify new models download correctly on first use
|
||||
- [ ] 6.2 Measure memory/GPU usage with new models
|
||||
- [ ] 6.3 Compare processing speed before/after upgrade
|
||||
- [ ] 6.4 Verify existing functionality not broken
|
||||
Reference in New Issue
Block a user