docs: update documentation for chart recognition enablement
Updates all project documentation to reflect that chart recognition is now fully enabled with PaddlePaddle 3.2.1+. Changes: - README.md: Remove Known Limitations section about chart recognition, update tech stack and prerequisites to include PaddlePaddle 3.2.1+, add WSL CUDA configuration notes - openspec/project.md: Add comprehensive chart recognition feature descriptions, update system requirements for GPU/CUDA support - openspec/changes/add-gpu-acceleration-support/tasks.md: Mark task 5.4 as completed with resolution details - openspec/changes/add-gpu-acceleration-support/proposal.md: Update Known Issues section to show chart recognition is now resolved - setup_dev_env.sh: Upgrade PaddlePaddle from 3.0.0 to 3.2.1+, add WSL CUDA library path configuration, add chart recognition API verification All documentation now accurately reflects: ✅ Chart recognition fully enabled ✅ PaddlePaddle 3.2.1+ with fused_rms_norm_ext API ✅ WSL CUDA path auto-configuration ✅ Comprehensive PP-StructureV3 capabilities 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -122,39 +122,39 @@ detect_gpu() {
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if [ "$CUDA_MAJOR" -ge 13 ]; then
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echo "將安裝 PaddlePaddle GPU 版本 (CUDA 13.x)"
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echo "使用穩定版本 3.0.0 (兼容 CUDA 12.6+)"
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echo "使用版本 3.2.1+ (兼容 CUDA 12.6+, 支援圖表識別)"
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USE_GPU=true
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PADDLE_PACKAGE="paddlepaddle-gpu==3.0.0"
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PADDLE_PACKAGE="paddlepaddle-gpu>=3.2.1"
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PADDLE_INDEX="https://www.paddlepaddle.org.cn/packages/stable/cu126/"
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elif [ "$CUDA_MAJOR" -eq 12 ]; then
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echo "將安裝 PaddlePaddle GPU 版本 (CUDA 12.x)"
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echo "使用穩定版本 3.0.0 (兼容 CUDA 12.3+)"
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echo "使用版本 3.2.1+ (兼容 CUDA 12.3+, 支援圖表識別)"
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USE_GPU=true
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PADDLE_PACKAGE="paddlepaddle-gpu==3.0.0"
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PADDLE_PACKAGE="paddlepaddle-gpu>=3.2.1"
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PADDLE_INDEX="https://www.paddlepaddle.org.cn/packages/stable/cu123/"
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elif [ "$CUDA_MAJOR" -eq 11 ]; then
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echo "將安裝 PaddlePaddle GPU 版本 (CUDA 11.x)"
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echo "使用穩定版本 3.0.0 (兼容 CUDA 11.8+)"
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echo "使用版本 3.2.1+ (兼容 CUDA 11.8+, 支援圖表識別)"
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USE_GPU=true
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PADDLE_PACKAGE="paddlepaddle-gpu==3.0.0"
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PADDLE_PACKAGE="paddlepaddle-gpu>=3.2.1"
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PADDLE_INDEX="https://www.paddlepaddle.org.cn/packages/stable/cu118/"
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else
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echo -e "${YELLOW}⚠ CUDA 版本不支援 ($CUDA_VERSION)${NC}"
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echo "將安裝 CPU 版本"
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USE_GPU=false
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PADDLE_PACKAGE="paddlepaddle"
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PADDLE_PACKAGE="paddlepaddle>=3.2.1"
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fi
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else
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echo -e "${YELLOW}⚠ 無法獲取 CUDA 版本${NC}"
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echo "將安裝 CPU 版本"
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USE_GPU=false
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PADDLE_PACKAGE="paddlepaddle"
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PADDLE_PACKAGE="paddlepaddle>=3.2.1"
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fi
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else
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echo -e "${YELLOW}ℹ 未偵測到 NVIDIA GPU 或 nvidia-smi${NC}"
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echo "將安裝 CPU 版本的 PaddlePaddle"
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USE_GPU=false
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PADDLE_PACKAGE="paddlepaddle"
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PADDLE_PACKAGE="paddlepaddle>=3.2.1"
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fi
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}
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@@ -179,7 +179,40 @@ if [ "$USE_GPU" = true ]; then
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fi
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else
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echo "安裝 CPU 版本..."
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pip install paddlepaddle
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pip install 'paddlepaddle>=3.2.1'
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fi
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# WSL CUDA 路徑配置 (針對 WSL GPU 用戶)
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if [ "$USE_GPU" = true ]; then
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echo ""
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echo -e "${YELLOW}配置 WSL CUDA 庫路徑...${NC}"
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# 檢查是否在 WSL 環境中
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if grep -qi microsoft /proc/version; then
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echo "偵測到 WSL 環境，配置 CUDA 庫路徑..."
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# 檢查 CUDA 庫是否存在於 WSL 路徑
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if [ -d "/usr/lib/wsl/lib" ]; then
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# 檢查 ~/.bashrc 中是否已包含此配置
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if ! grep -q "export LD_LIBRARY_PATH=/usr/lib/wsl/lib" ~/.bashrc; then
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echo "" >> ~/.bashrc
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echo "# WSL CUDA Libraries Path for PaddlePaddle GPU support (Added by Tool_OCR setup)" >> ~/.bashrc
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echo "export LD_LIBRARY_PATH=/usr/lib/wsl/lib:\$LD_LIBRARY_PATH" >> ~/.bashrc
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echo "✓ 已將 WSL CUDA 路徑添加到 ~/.bashrc"
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else
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echo "✓ WSL CUDA 路徑已存在於 ~/.bashrc"
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fi
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# 立即應用到當前 session
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export LD_LIBRARY_PATH=/usr/lib/wsl/lib:$LD_LIBRARY_PATH
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echo "✓ 已應用 CUDA 路徑到當前環境"
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else
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echo -e "${YELLOW}⚠ 未找到 /usr/lib/wsl/lib 目錄${NC}"
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echo "請確認 NVIDIA CUDA 驅動已安裝於 WSL"
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fi
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else
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echo "非 WSL 環境，跳過 WSL CUDA 路徑配置"
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fi
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fi
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# 安裝其他依賴（跳過 requirements.txt 中的 paddlepaddle）
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@@ -217,6 +250,26 @@ except Exception as e:
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print('ℹ 將使用 CPU 模式')
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" || echo "⚠ PaddlePaddle 驗證失敗，但可繼續使用"
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# 驗證圖表識別 API 可用性
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echo ""
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echo -e "${YELLOW}驗證圖表識別 API...${NC}"
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python -c "
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import paddle.incubate.nn.functional as F
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# 檢查 API 可用性
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has_base = hasattr(F, 'fused_rms_norm')
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has_ext = hasattr(F, 'fused_rms_norm_ext')
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print('📊 圖表識別 API 檢查:')
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print(f' - fused_rms_norm: {'✅ 可用' if has_base else '❌ 不可用'}')
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print(f' - fused_rms_norm_ext: {'✅ 可用' if has_ext else '❌ 不可用'}')
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if has_ext:
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print('🎉 圖表識別功能: ✅ 可啟用')
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else:
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print('⚠️ 圖表識別功能: ❌ 不可用 (需要 PaddlePaddle 3.2.0+)')
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" || echo "⚠ 圖表識別 API 驗證失敗"
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echo ""
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echo -e "${YELLOW}[8/9] 安裝前端依賴...${NC}"
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cd frontend
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@@ -251,10 +304,15 @@ echo ""
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echo "系統配置:"
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if [ "$USE_GPU" = true ]; then
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echo -e " GPU 加速: ${GREEN}已啟用${NC}"
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echo " PaddlePaddle: GPU 版本"
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echo " PaddlePaddle: GPU 版本 (3.2.1+)"
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echo -e " 圖表識別: ${GREEN}已啟用${NC}"
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if grep -qi microsoft /proc/version; then
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echo " WSL CUDA 路徑: 已配置於 ~/.bashrc"
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fi
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else
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echo -e " GPU 加速: ${YELLOW}未啟用 (CPU 模式)${NC}"
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echo " PaddlePaddle: CPU 版本"
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echo " PaddlePaddle: CPU 版本 (3.2.1+)"
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echo -e " 圖表識別: ${GREEN}已啟用${NC} (CPU 模式)"
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fi
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echo ""
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echo "下一步操作："
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@@ -276,3 +334,7 @@ echo " 前端: http://localhost:5173"
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echo " API文檔: http://localhost:8000/docs"
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echo " 健康檢查: http://localhost:8000/health"
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echo ""
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if [ "$USE_GPU" = true ] && grep -qi microsoft /proc/version; then
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echo "注意: WSL GPU 用戶需要重新啟動終端或執行 'source ~/.bashrc' 以應用 CUDA 路徑配置"
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echo ""
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fi
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