# ============================================================
# 基础镜像：NVIDIA TensorRT 23.08
# 内含：CUDA 12.1.1 | cuDNN 8.9.3 | TensorRT 8.6.1.6 | Python 3.10
# ============================================================
FROM nvcr.io/nvidia/tensorrt:23.08-py3

LABEL maintainer="AI Edge Architecture Team"
LABEL description="Edge AI Inference Service - YOLOv11n + TensorRT"

# 设置时区
ENV TZ=Asia/Shanghai
RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone

# 系统依赖（视频解码、OpenCV 运行时）
RUN apt-get update && apt-get install -y --no-install-recommends \
    ffmpeg \
    libsm6 \
    libxext6 \
    libgl1-mesa-glx \
    && rm -rf /var/lib/apt/lists/*

WORKDIR /app

# 先复制依赖文件，利用 Docker 层缓存
COPY requirements.txt .

# 安装 PyTorch（CUDA 12.1 版本）+ 其余依赖
RUN pip install --no-cache-dir \
    torch==2.1.2 torchvision==0.16.2 \
    --index-url https://download.pytorch.org/whl/cu121 \
    && pip install --no-cache-dir -r requirements.txt

# 复制项目代码
COPY __init__.py .
COPY main.py .
COPY algorithms.py .
COPY build_engine.py .
COPY config/ ./config/
COPY core/ ./core/
COPY utils/ ./utils/

# 模型和数据通过卷挂载，不打入镜像
# -v /path/to/models:/app/models
# -v /path/to/data:/app/data

# 日志目录
RUN mkdir -p /app/logs /app/data

EXPOSE 9001

CMD ["python", "main.py"]