fabito

[
  {
    "name": "project_id",
    "type": "string",
    "mode": "required"
  },  
  {
    "name": "id",
    "type": "string",
    "mode": "required"

fabito

#!/usr/bin/env python
'''Crop an image to just the portions containing text.

Usage:

    ./crop_morphology.py path/to/image.jpg

This will place the cropped image in path/to/image.crop.png.

For details on the methodology, see

fabito

• Home page
• http://www.einarsundgren.se/gstreamer-basic-real-time-streaming-tutorial/
• Original documetation from source code
• http://wiki.oz9aec.net/index.php/Gstreamer_cheat_sheet
• http://www.cin.ufpe.br/~cinlug/wiki/index.php/Introducing_GStreamer
• http://www.jonobacon.org/2006/12/27/using-gnonlin-with-gstreamer-and-python/
• https://felipec.wordpress.com/2008/01/19/gstreamer-hello-world/
• http://notes.brooks.nu/2011/01/gstreamer-video-crossfade-example/
• http://www.oz9aec.net/index.php/gstreamer/366-gstinputselector-to-switch-between-different-cameras
• Picture compositing

fabito

#!/usr/bin/env bash

PROJECT=$1
INSTANCE_NAME=$2
MACHINE_TYPE=${3:-n1-standard-4}
ZONE=${4:-us-central1-c}
NUM_GPUS=${5:-1}

gcloud compute --project ${PROJECT} instances create ${INSTANCE_NAME} \
  --zone ${ZONE} \

fabito

"""
xhost +local:docker && nvidia-docker run --rm -it --privileged --net=host \
    -v ${PWD}/:/s3fd \
    -e DISPLAY=unix$DISPLAY \
    -v /tmp/.X11-unix:/tmp/.X11-unix \
    --workdir /s3fd \
    bvlc/caffe:gpu bash
"""

import caffe

fabito

layer     filters    size              input                output
    0 conv     32  3 x 3 / 1   416 x 416 x   3   ->   416 x 416 x  32
    1 conv     64  3 x 3 / 2   416 x 416 x  32   ->   208 x 208 x  64
    2 conv     32  1 x 1 / 1   208 x 208 x  64   ->   208 x 208 x  32
    3 conv     64  3 x 3 / 1   208 x 208 x  32   ->   208 x 208 x  64
    4 Shortcut Layer: 1
    5 conv    128  3 x 3 / 2   208 x 208 x  64   ->   104 x 104 x 128
    6 conv     64  1 x 1 / 1   104 x 104 x 128   ->   104 x 104 x  64
    7 conv    128  3 x 3 / 1   104 x 104 x  64   ->   104 x 104 x 128
    8 Shortcut Layer: 5

fabito

#!/usr/bin/env bash
# Bash3 Boilerplate. Copyright (c) 2014, kvz.io

set -o errexit
set -o pipefail
set -o nounset
# set -o xtrace

# Set magic variables for current file & dir
__dir="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"

fabito

import requests
import re
import json

download_url = 'https://pan.baidu.com/s/15NsUpSIFeHfoGKHAjQBISQ'
session = requests.Session()

HEADERS = {
    'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.140 Safari/537.36'
}

fabito

# create the directory where the dataset will be downloaded
mkdir -p ${HOME}/datasets/FDDB

# download the dataset
docker run --rm -it  \
    -v ${HOME}/datasets/:/datasets \
    housebw/morghulis-browser morghulis.download --dataset=fddb --output_dir=/datasets/FDDB

fabito

xhost + && \
docker run --rm -it --privileged \
    -e DISPLAY=unix$DISPLAY \
    -v /tmp/.X11-unix:/tmp/.X11-unix \
    -v ${HOME}/datasets/:/datasets \
    housebw/morghulis-browser morghulis.browse --dataset=fddb --data_dir=/datasets/FDDB