kennydukor

version: "3"
services:
  nginx-proxy:
    image: jwilder/nginx-proxy
    container_name: nginx-proxy
    ports:
      - "80:80"
    volumes:
      - /var/run/docker.sock:/tmp/docker.sock:ro
    restart: always

kennydukor

FROM strapi/base
WORKDIR /app
COPY ./package.json ./
COPY ./provider-upload-cloudinary ./provider-upload-cloudinary # take this out if you are not using the modified package
RUN yarn install
COPY . .
ENV NODE_ENV production

ARG HOST
ENV HOST=$HOST

kennydukor

image: node:16.11.1

cache:
  paths:
    - node_modules/

stages:
  - build
  - deploy

kennydukor

module.exports = ({ env }) => ({
  // ...
  upload: {
    config: {
      provider: 'cloudinary',
      providerOptions: {
        cloud_name: env('CLOUDINARY_NAME'),
        api_key: env('CLOUDINARY_KEY'),
        api_secret: env('CLOUDINARY_SECRET'),
        folder: env('CLOUDINARY_FOLDER'),

kennydukor

const path = require('path');

module.exports = ({ env }) => ({
  defaultConnection: "default",
  connection: {
    client: "postgres",
    connection: {
      host: process.env.DATABASE_HOST,
      port: process.env.DATABASE_PORT,
      database: process.env.DATABASE_NAME,

kennydukor

ResNet-152 in Keras

This is an Keras implementation of ResNet-152 with ImageNet pre-trained weights. I converted the weights from Caffe provided by the authors of the paper. The implementation supports both Theano and TensorFlow backends. Just in case you are curious about how the conversion is done, you can visit my blog post for more details.

ResNet Paper:

Deep Residual Learning for Image Recognition.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
arXiv:1512.03385