Google vision has orientation on it's own Cloud Storage when we talk about BigData.
API is extensive. Although SDK doesn't have all features available.
Advantages of GCP is a wide variety of pre-defined models and ability to upload your own. Existance of human labeled model can give better results, although the price is higher and there is no free tier.
| from nuxeo.client import Nuxeo | |
| import argparse | |
| # size in MB | |
| def _query(client, begin, end=None): | |
| query = None | |
| if (end is None): | |
| query = f"SELECT * FROM Document WHERE ecm:primaryType = 'Design' AND ecm:currentLifeCycleState != 'deleted' AND ecm:isVersion = 0 AND file:content/length > {begin * 1024 * 1024}" | |
| else: |
| import os | |
| def get_meta(line): | |
| splitted = line.split() | |
| if len(splitted) <= 4: | |
| return None, None, None | |
| s = float(splitted[2]) | |
| t = splitted[3] | |
| name = splitted[4].strip() |
| from pydub import AudioSegment | |
| from pydub.utils import make_chunks | |
| import csv | |
| import os | |
| from pprint import pprint | |
| chunk_s = 2000 | |
| natives = {} |
| from time import sleep | |
| from nuxeo.client import Nuxeo | |
| from nuxeo.exceptions import HTTPError | |
| from nuxeo.users import User | |
| from nuxeo.groups import Group | |
| import csv | |
| import argparse | |
| from jira import JIRA | |
| import csv | |
| import re | |
| import time | |
| from jira.exceptions import JIRAError | |
| no_format = re.compile(r'{(code|noformat}).*?(code|noformat)}') | |
| no_inline = re.compile(r'{{.*?}}') | |
| no_xml = re.compile(r'<[^>]+>') |
| /opt/bin/nvidia-smi | |
| wget https://developer.nvidia.com/compute/cuda/8.0/Prod2/local_installers/cuda-repo-ubuntu1604-8-0-local-ga2_8.0.61-1_amd64-deb | |
| dpkg -i cuda-repo-ubuntu1604-8-0-local-ga2_8.0.61-1_amd64-deb 2> /dev/null | |
| apt-key add /var/cuda-repo-8-0-local-ga2/7fa2af80.pub | |
| apt-get update | |
| apt-get install -qq cuda gcc-5 g++-5 -y | |
| ln -s /usr/bin/gcc-5 /usr/local/cuda/bin/gcc | |
| ln -s /usr/bin/g++-5 /usr/local/cuda/bin/g++ | |
| /usr/local/cuda/bin/nvcc --version |
| #include <stdio.h> | |
| #define N 2048 * 2048 // Number of elements in each vector | |
| /* | |
| * Optimize this already-accelerated codebase. Work iteratively, | |
| * and use nvprof to support your work. | |
| * | |
| * Aim to profile `saxpy` (without modifying `N`) running under | |
| * 50us. |
| #include <stdio.h> | |
| /* | |
| * Host function to initialize vector elements. This function | |
| * simply initializes each element to equal its index in the | |
| * vector. | |
| */ | |
| __global__ | |
| void initWith(float num, float *a, int N) |
