mehdidc

{
  "embeddings": [
    {
      "tensorName": "WIPO",
      "tensorShape": [
        5799,
        300
      ],
      "tensorPath": "https://files.fm/down.php?i=yrkmskvv",
      "metadataPath": "https://gist.githubusercontent.com/mehdidc/af6727cec814cb37a9bc36f6620bc288/raw/383d6805b294397307b659242328cd446cfded1f/labels.tsv"

mehdidc

portable bath bench/seat
bathtub
bath for invalid
a multi-purpose shower device
children's bath
a foot care device
a showering appliance
knockdown bath bench
safety devices
a shower-bath booth structure

mehdidc

"FIRST do : curl -fLo ~/.vim/autoload/plug.vim --create-dirs https://raw.githubusercontent.com/junegunn/vim-plug/master/plug.vim
set autoindent
set nocindent
set nosmartindent
set autoindent
set indentexpr=
set tabstop=8
set expandtab
set shiftwidth=4
set softtabstop=4

mehdidc

wget https://downloads.rclone.org/v1.41/rclone-v1.41-linux-amd64.zip
unzip  rclone-v1.41-linux-amd64.zip
wget https://gist.githubusercontent.com/mehdidc/9f9f7d1f96e2c53571dfac501f61dbbb/raw/252e45e95159dc311468e8aefa875700bce1d195/gistfile1.txt --output-document=$HOME/.rclone.conf
mkdir -p data
git clone https://github.com/tensorflow/models/
curl -OL https://github.com/google/protobuf/releases/download/v3.2.0/protoc-3.2.0-linux-x86_64.zip
rm -fr protoc && unzip protoc-3.2.0-linux-x86_64.zip -d protoc
cd models/research/ && ../../protoc/bin/protoc object_detection/protos/*.proto --python_out=.
pip install contextlib2
cp  models/research/object_detection/dataset_tools/create_oid_tf_record.py .

mehdidc

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

mehdidc

Cython

Cython has two major benefits:

1. Making python code faster, particularly things that can't be done in scipy/numpy
2. Wrapping/interfacing with C/C++ code

Cython gains most of it's benefit from statically typing arguments. However, statically typing is not required, in fact, regular python code is valid cython (but don't expect much of a speed up). By incrementally adding more type information, the code can speed up by several factors. This gist just provides a very basic usage of cython.

mehdidc

# docker build -t ubuntu1604py36
FROM ubuntu:16.04

RUN apt-get update
RUN apt-get install -y software-properties-common vim
RUN add-apt-repository ppa:jonathonf/python-3.6
RUN apt-get update

RUN apt-get install -y build-essential python3.6 python3.6-dev python3-pip python3.6-venv
RUN apt-get install -y git

mehdidc

# remap prefix from 'C-b' to 'C-a'
unbind C-b
set-option -g prefix C-a
bind-key C-a send-prefix
# Start window numbering at 1
set -g base-index 1

set -g @plugin 'tmux-plugins/tpm'
set -g @plugin 'tmux-plugins/tmux-sensible'
set -g @plugin 'tmux-plugins/tmux-copycat'

mehdidc

mehdidc

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name: