feat: .gitignore & deploy file

.gitea/workflows/ci.yml

@@ -0,0 +1,31 @@
+name: CI
+
+on:
+  push:
+    branches:
+      - develop
+  workflow_dispatch:
+
+jobs:
+  docker:
+    runs-on: runner
+    env:
+      NAME: lone/xunlian
+    steps:
+      - name: Checkout
+        uses: https://git.ailuowan.com/deploy/checkout@v4
+
+      - name: Login Registry
+        run: |
+          echo "${{ secrets.REGISTRY_PASSWORD }}" | docker login ${{ vars.REGISTRY }} -u "${{ vars.REGISTRY_USERNAME }}" --password-stdin
+
+      - name: Docker build
+        run: |
+          docker buildx build --load \
+            -f Dockerfile \
+            -t ${{ vars.REGISTRY }}/$NAME:latest \
+            .
+
+      - name: Docker push
+        run: |
+          docker push ${{ vars.REGISTRY }}/$NAME:latest

.gitignore

@@ -0,0 +1,4 @@
+*.pt
+__pycache__/
+
+runs/

Dockerfile

@@ -1,8 +1,7 @@
-# YOLOv8 training environment (NVIDIA GPU)
+# YOLOv8 training image (NVIDIA GPU)
 #
-# The image contains Python, PyTorch and Ultralytics only. The project
-# directory (including data.yaml, train/valid/test and *.pt files) is mounted
-# at /workspace when the container is started; this keeps the image small.
+# Image contains Python / PyTorch / Ultralytics + train script.
+# Dataset (*.pt weights, /data/facepp, runs/) are mounted at runtime.
 
 FROM nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04
 
@@ -22,11 +21,10 @@ RUN apt-get update \
         libxext6 \
         libxrender1 \
         python3 \
-        python3-dev \
         python3-pip \
     && rm -rf /var/lib/apt/lists/*
 
-# PyTorch 2.5.1 is paired with torchvision 0.20.1 and CUDA 12.4.
+# PyTorch 2.5.1 + torchvision 0.20.1 (CUDA 12.4)
 RUN python3 -m pip install --upgrade pip \
     && python3 -m pip install \
         torch==2.5.1 \
@@ -36,8 +34,7 @@ RUN python3 -m pip install --upgrade pip \
 
 WORKDIR /workspace
 
-# These files make the image usable for a quick smoke test. The normal run
-# command mounts the whole project over /workspace.
 COPY train_yolov8.py data.yaml ./
 
 ENTRYPOINT ["python3", "train_yolov8.py"]
+CMD ["--model", "yolov8n.pt", "--device", "0"]

data.yaml

@@ -1,7 +1,7 @@
 path: .
-train: train/images
-val: valid/images
-test: test/images
+train: /data/facepp/train/images
+val: /data/facepp/valid/images
+test: /data/facepp/test/images
 
 nc: 11
 names: ['0', '1', '10', '2', '3', '4', '5', '6', '7', '8', '9']

docker-compose.prod.yml

@@ -0,0 +1,16 @@
+services:
+  xunlian:
+    image: git.ailuowan.com/lone/xunlian:latest
+    gpus: all
+    volumes:
+      - ./yolov8n.pt:/workspace/yolov8n.pt:ro
+      - ./yolov8m.pt:/workspace/yolov8m.pt:ro
+      - ./yolo26n.pt:/workspace/yolo26n.pt:ro
+      - /data/facepp:/data/facepp:ro
+
+      - ./runs:/workspace/runs
+    environment:
+      TZ: Asia/Shanghai
+      NVIDIA_VISIBLE_DEVICES: all
+      NVIDIA_DRIVER_CAPABILITIES: compute,utility
+    restart: "no"