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HSAP/algorithms/dms_yolo/code.embedded.bak/docker/Dockerfile-conda
Chengfang Lu e72bc061c5 feat: HSAP platform v2 — modular navigation, quality review, audit log, world model simulation
Major changes:
- New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind
- 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理
- Data catalog with charts (DMS/ADAS/Lane 3-tab view)
- Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance
- Audit enhancements: batch operations, rejection categories, Feishu notifications
- Operation audit log (操作日志)
- World model simulation studio (仿真工坊)
- Dataset version management with snapshots and diff
- ADAS 7-class dataset integration (138K images organized + compressed)
- User management with Feishu integration and pagination
- CRUD/search/filter on all pages, card layout redesign
- PIL-optimized image overlay rendering
- Auto-snapshot on build, in_review workflow stage
- Removed embedded algorithm code (now in workspace)
2026-06-03 11:40:21 +08:00

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# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Builds ultralytics/ultralytics:latest-conda image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Image is optimized for Ultralytics Anaconda (https://anaconda.org/conda-forge/ultralytics) installation and usage
# Start FROM miniconda3 image https://hub.docker.com/r/continuumio/miniconda3
FROM continuumio/miniconda3:latest
# Set environment variables
ENV PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
PIP_NO_CACHE_DIR=1 \
PIP_BREAK_SYSTEM_PACKAGES=1
# Downloads to user config dir
ADD https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.ttf \
https://github.com/ultralytics/assets/releases/download/v0.0.0/Arial.Unicode.ttf \
/root/.config/Ultralytics/
# Install linux packages and conda packages
RUN apt-get update && \
apt-get install -y --no-install-recommends libgl1 && \
apt-get clean && \
# Install conda packages
# mkl required to fix 'OSError: libmkl_intel_lp64.so.2: cannot open shared object file: No such file or directory'
conda config --set solver libmamba && \
conda install -y pytorch torchvision pytorch-cuda=12.1 -c pytorch -c nvidia && \
conda install -y -c conda-forge ultralytics mkl && \
conda clean -afy && \
# Remove extra build files
rm -rf /var/lib/apt/lists/* /root/.config/Ultralytics/persistent_cache.json
# Copy model
ADD https://github.com/ultralytics/assets/releases/download/v8.4.0/yolo26n.pt .
# Usage --------------------------------------------------------------------------------------------------------------
# Production builds: https://github.com/ultralytics/ultralytics/blob/main/.github/workflows/docker.yml
# Example (build): t=ultralytics/ultralytics:latest-conda && docker build -f docker/Dockerfile-conda -t $t .
# Example (push): docker push $t
# Example (pull): t=ultralytics/ultralytics:latest-conda && docker pull $t
# Example (run): docker run -it --ipc=host $t
# Example (run-with-volume): docker run -it --ipc=host -v "$PWD/shared/datasets:/datasets" $t