3dtours
bbc64118a5
- backend: preserve aspect ratio with edge-replicated square padding into 512x512 LaMa model - backend: fix inverted mask threshold (>0.85*plane) and prune CUDA/TensorRT binaries for slim image - frontend: enable server AI by default and route masks >3.5% or edge-crossing to LaMa Tier 2 - frontend: enforce 60%-80% context padding (min 64px) aligned to multiples of 8 - frontend: add 3-5px binary mask dilation and high-frequency sensor grain matching - frontend: anchor deletion badge to topmost point of brush stroke - build & export: updated docker containers and recipescam-images.tar.gz (357MB)
32 lines
1.3 KiB
Docker
32 lines
1.3 KiB
Docker
# RecipesCam API — self-contained build (context = this folder).
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# Builder compiles TypeScript; runtime carries production deps only.
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FROM node:22-slim AS builder
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WORKDIR /app
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COPY package.json package-lock.json ./
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RUN npm ci
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COPY tsconfig.json ./
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COPY src ./src
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RUN npm run build && npm prune --omit=dev
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# onnxruntime-node ships every platform's runtime, and 260MB of it is the CUDA /
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# TensorRT providers this container (CPU inference, no GPU) never loads. The
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# bindings for the other two operating systems go the same way; both Linux
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# architectures stay so the image can still be built for an ARM host.
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RUN rm -rf node_modules/onnxruntime-node/bin/napi-v6/darwin \
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node_modules/onnxruntime-node/bin/napi-v6/win32 \
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node_modules/onnxruntime-node/bin/napi-v6/linux/x64/libonnxruntime_providers_cuda.so \
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node_modules/onnxruntime-node/bin/napi-v6/linux/x64/libonnxruntime_providers_tensorrt.so
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FROM node:22-slim
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ENV NODE_ENV=production \
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PORT=3000 \
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DATA_DIR=/data \
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INPAINT_MODEL_PATH=/app/models/lama_fp32.onnx
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WORKDIR /app
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COPY --from=builder /app/node_modules ./node_modules
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COPY --from=builder /app/dist ./dist
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COPY package.json ./
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COPY models ./models
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RUN ln -sf /app/models /models
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EXPOSE 3000
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CMD ["node", "dist/server.js"]
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