docker-compose files

src/doctr_service/Dockerfile.gpu

@@ -35,20 +35,15 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     && rm -rf /var/lib/apt/lists/* \
     && ln -sf /usr/bin/python3.12 /usr/bin/python
 
-# Install PyTorch with CUDA support
+# Copy requirements first for better caching
-# cu128 index has both amd64 and arm64 wheels
+COPY requirements.txt .
-RUN python -m pip install --no-cache-dir \
+
+# Install PyTorch with CUDA support first (cu128 index has amd64 + arm64 wheels)
+RUN python -m pip install --no-cache-dir --break-system-packages \
     torch torchvision --index-url https://download.pytorch.org/whl/cu128
 
-# Install DocTR and other dependencies
+# Install remaining dependencies from requirements.txt (skip torch, already installed)
-RUN python -m pip install --no-cache-dir \
+RUN grep -v "^torch" requirements.txt | python -m pip install --no-cache-dir --break-system-packages -r /dev/stdin
-    "python-doctr[torch]>=0.8.0" \
-    fastapi>=0.104.0 \
-    "uvicorn[standard]" \
-    pydantic>=2.0.0 \
-    jiwer>=3.0.0 \
-    numpy>=1.24.0 \
-    pillow>=10.0.0
 
 # Copy application code
 COPY doctr_tuning_rest.py .

src/doctr_service/docker-compose.yml

@@ -0,0 +1,61 @@
+# docker-compose.yml - DocTR REST API
+# Usage:
+#   CPU:  docker compose up ocr-cpu
+#   GPU:  docker compose up ocr-gpu
+#
+# Port: 8003
+
+services:
+  # CPU-only service
+  ocr-cpu:
+    image: seryus.ddns.net/unir/doctr-cpu:latest
+    container_name: doctr-cpu
+    ports:
+      - "8003:8000"
+    volumes:
+      - ../dataset:/app/dataset:ro
+      - doctr-cache:/root/.cache/doctr
+    environment:
+      - PYTHONUNBUFFERED=1
+      - DOCTR_DET_ARCH=db_resnet50
+      - DOCTR_RECO_ARCH=crnn_vgg16_bn
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 180s
+
+  # GPU service (requires NVIDIA Container Toolkit)
+  ocr-gpu:
+    image: seryus.ddns.net/unir/doctr-gpu:latest
+    container_name: doctr-gpu
+    ports:
+      - "8003:8000"
+    volumes:
+      - ../dataset:/app/dataset:ro
+      - doctr-cache:/root/.cache/doctr
+    environment:
+      - PYTHONUNBUFFERED=1
+      - CUDA_VISIBLE_DEVICES=0
+      - DOCTR_DET_ARCH=db_resnet50
+      - DOCTR_RECO_ARCH=crnn_vgg16_bn
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 180s
+
+volumes:
+  doctr-cache:
+    name: doctr-model-cache

src/easyocr_service/Dockerfile.gpu

@@ -34,20 +34,15 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     && rm -rf /var/lib/apt/lists/* \
     && ln -sf /usr/bin/python3.12 /usr/bin/python
 
-# Install PyTorch with CUDA support
+# Copy requirements first for better caching
-# cu128 index has both amd64 and arm64 wheels
+COPY requirements.txt .
-RUN python -m pip install --no-cache-dir \
+
+# Install PyTorch with CUDA support first (cu128 index has amd64 + arm64 wheels)
+RUN python -m pip install --no-cache-dir --break-system-packages \
     torch torchvision --index-url https://download.pytorch.org/whl/cu128
 
-# Install EasyOCR and other dependencies
+# Install remaining dependencies from requirements.txt (skip torch, already installed)
-RUN python -m pip install --no-cache-dir \
+RUN grep -v "^torch" requirements.txt | python -m pip install --no-cache-dir --break-system-packages -r /dev/stdin
-    easyocr>=1.7.0 \
-    fastapi>=0.104.0 \
-    "uvicorn[standard]" \
-    pydantic>=2.0.0 \
-    jiwer>=3.0.0 \
-    numpy>=1.24.0 \
-    pillow>=10.0.0
 
 # Copy application code
 COPY easyocr_tuning_rest.py .

src/easyocr_service/docker-compose.yml

@@ -0,0 +1,59 @@
+# docker-compose.yml - EasyOCR REST API
+# Usage:
+#   CPU:  docker compose up ocr-cpu
+#   GPU:  docker compose up ocr-gpu
+#
+# Port: 8002
+
+services:
+  # CPU-only service
+  ocr-cpu:
+    image: seryus.ddns.net/unir/easyocr-cpu:latest
+    container_name: easyocr-cpu
+    ports:
+      - "8002:8000"
+    volumes:
+      - ../dataset:/app/dataset:ro
+      - easyocr-cache:/root/.EasyOCR
+    environment:
+      - PYTHONUNBUFFERED=1
+      - EASYOCR_LANGUAGES=es,en
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 120s
+
+  # GPU service (requires NVIDIA Container Toolkit)
+  ocr-gpu:
+    image: seryus.ddns.net/unir/easyocr-gpu:latest
+    container_name: easyocr-gpu
+    ports:
+      - "8002:8000"
+    volumes:
+      - ../dataset:/app/dataset:ro
+      - easyocr-cache:/root/.EasyOCR
+    environment:
+      - PYTHONUNBUFFERED=1
+      - CUDA_VISIBLE_DEVICES=0
+      - EASYOCR_LANGUAGES=es,en
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 120s
+
+volumes:
+  easyocr-cache:
+    name: easyocr-model-cache