from clarifai.client import ClarifaiApi
import sys
clarifai_api = ClarifaiApi(model='nsfw-v1.0')
result = clarifai_api.tag_image_urls(str(sys.argv[1]))
result = result['results'][0]['result']['tag']['probs']
if result[0] > result[1]:
print 'Safe for work!'
else:
print 'Not safe for work.'
import pandas as pd
from clarifai.client import ClarifaiApi
import PIL, os
from bson import json_util, ObjectId
from pandas.io.json import json_normalize
import json
import itertools
from pandas import DataFrame
clarifai_api = ClarifaiApi('<Client Id>','<Client Secret>')
result = clarifai_api.tag_images([open('<path to image file 1>', 'rb'),
open('<path to image file 2>', 'rb'),
open('<path to image file 3>', 'rb')])
sanitized = json.loads(json_util.dumps(result['results']))
normalized = json_normalize(sanitized)
df = pd.DataFrame(normalized)
res = df.to_dict()
data = []
for x in res['docid'].keys():
data.append(itertools.izip_longest([res['docid_str'][x]], res['result.tag.classes'][x], res['result.tag.concept_ids'][x], res['result.tag.probs'][x], fillvalue = res['docid_str'][x]))
new_data = list(itertools.chain.from_iterable(data))
df3 = DataFrame(new_data, columns = ['docid_str', 'tag_class', 'tag_concept', 'tag_probs'])
print df3
# Clarifai Image Tag Accumulator
# to run, follow instructions on: https://github.com/Clarifai/clarifai-python
import json
from collections import defaultdict
from clarifai.client import ClarifaiApi
clarifai_api = ClarifaiApi()
# initialize tag dictionary for tags and their frequencies
d = defaultdict(int)
taglist = []
iter = 0
# read and process each url
with open("imglist.txt") as f:
imglist = f.readlines()
# get tags using clarifai, add tags to taglist
for line in imglist:
result = clarifai_api.tag_image_urls(line.rstrip('\n'))
tags = result['results'][0]['result']['tag']['classes']
for i in range(0,len(tags)):
if type(tags[i]) is str:
taglist.append(tags[i])
print("next iter:" + str(iter))
iter += 1
# convert taglist to dictionary
for x in range(0,len(taglist)):
d[taglist[x]] += 1
from clarifai.client import ClarifaiApi
#credentials to access the Clarifai API
clarifai_api = ClarifaiApi(
app_id="kqwTnQ7CEHM1v3W_nO4Qi0A6k5VjKmzINOKEDG9d",
app_secret="ZCdFchZrIfS0nPMD64mG_keGcAnIPHQnn7dVxX1K")
# clarifai_api = ClarifaiApi(app_id="0GeRCt-zofqj9_xcXAryJDM4U-zwKq7WRnMWf9Dg",
# app_secret="NX073ug4XtrOss3ZGsA1ZS-rx7-ZnYoFiMmH5sP9")
def generate_tags(url_image):
# url_image is the url of the image that need to be tagged.
# the tags are then stored in result in JSON format.
result = clarifai_api.tag_image_urls(url_image)
# result is a nested JSON, from which we can now get classes and probabilities
tags_result = result[u'results'][0]["result"]["tag"]
tags = tags_result["classes"]
probs = tags_result["probs"]
print tags
print probs
return (tags, probs)
#
#
# generate_tags('http://farm1.staticflickr.com/38/77131556_10d679c856.jpg')
def client(self, app_id, app_secret): return ClarifaiApi(app_id, app_secret)
def test_usage(self):
api = ClarifaiApi()
response = api.get_usage()
self.assertTrue(response)
self.assertTrue(len(response['user_throttles']) == 2)
def __init__(self, **kargs):
os.environ['CLARIFAI_APP_ID'] = kargs['app_id']
os.environ['CLARIFAI_APP_SECRET'] = kargs['app_secret']
self.cfa = ClarifaiApi()
def __init__(self, input_filename, output_filename):
self.fio_r = open(input_filename, 'r')
self.fio_w = open(output_filename, 'wb')
self.api = ClarifaiApi(model='general-v1.3')
#Importing the credentials for the various APIs used
import credentials
#Python module for parsing JSON
import json
#Session object makes use of 'a secret key'.
#SECRET_KEY = 'a secret key'
#Flask server side application setup
app = Flask(__name__)
app.config.from_object(__name__)
#Initialization of API clients for Twilio and Clarifai
twilio_api = TwilioRestClient(credentials.account_sid, credentials.auth_token)
clarifai_api = ClarifaiApi(credentials.my_clarifai_id,
credentials.my_clarifai_secret)
def request_yelp(url, url_params=None):
#Initialization of credential parameters for Yelp API
consumer_key = credentials.my_yelp_consumer_key
consumer_secret = credentials.my_yelp_consumer_secret
token = credentials.my_yelp_token
token_secret = credentials.my_yelp_token_secret
url_params = url_params or {}
#Making the API get request using the oauth2 python library using the previously initialized credential parameters
consumer = oauth2.Consumer(consumer_key, consumer_secret)
oauth_request = oauth2.Request(method="GET",
url=url,
parameters=url_params)
from flask import Flask, Response, request, render_template
from pymongo import MongoClient
from bson import json_util
from clarifai.client import ClarifaiApi
import urbanairship as ua
from urbanairship import ios
from settings_local import (CLARIFAI_APP_ID, CLARIFAI_APP_SECRET, UA_KEY,
UA_SECRET)
app = Flask(__name__)
db = MongoClient()["betim"]
airship = ua.Airship(UA_KEY, UA_SECRET)
clarifai_api = ClarifaiApi(app_id=CLARIFAI_APP_ID,
app_secret=CLARIFAI_APP_SECRET)
def jsonify(data):
return Response(json_util.dumps(data), mimetype='application/json')
@app.route("/images", methods=['GET'])
def get_images():
result = db.images.find({"comment": None}).sort([['date_creation', -1]])
return jsonify({
'images': [{
'id': str(image.get('_id')),
'description': image.get('description'),
'url': image.get('url'),
def test_embed_one_image(self):
image_url = 'http://clarifai-img.s3.amazonaws.com/test/toddler-flowers.jpeg'
api = ClarifaiApi()
response = api.embed_image_urls(image_url)
self.assertTrue(response)
self.assertTrue(response['results'][0]['url'] == image_url)
def main(argv):
clarifai_api = ClarifaiApi() # assumes environment variables are set.
result1 = clarifai_api.tag_images(open(r'TL.jpg', 'rb'))
result2 = clarifai_api.tag_images(open(r'TM.jpg', 'rb'))
result3 = clarifai_api.tag_images(open(r'TR.jpg', 'rb'))
result4 = clarifai_api.tag_images(open(r'ML.jpg', 'rb'))
result5 = clarifai_api.tag_images(open(r'MM.jpg', 'rb'))
result6 = clarifai_api.tag_images(open(r'MR.jpg', 'rb'))
result7 = clarifai_api.tag_images(open(r'LL.jpg', 'rb'))
result8 = clarifai_api.tag_images(open(r'LM.jpg', 'rb'))
result9 = clarifai_api.tag_images(open(r'LR.jpg', 'rb'))
p1 = result1['results'][0]['result']['tag']['classes']
p2 = result2['results'][0]['result']['tag']['classes']
p3 = result3['results'][0]['result']['tag']['classes']
p4 = result4['results'][0]['result']['tag']['classes']
p5 = result5['results'][0]['result']['tag']['classes']
p6 = result6['results'][0]['result']['tag']['classes']
p7 = result7['results'][0]['result']['tag']['classes']
p8 = result8['results'][0]['result']['tag']['classes']
p9 = result9['results'][0]['result']['tag']['classes']
f = open("tag", "r")
myItem = f.read()
p = open("pos", "r")
pos = p.read().split('|')
x0 = int(pos[0].split(',')[0])
y0 = int(pos[0].split(',')[1])
x1 = int(pos[1].split(',')[0])
y1 = int(pos[1].split(',')[1])
x2 = int(pos[2].split(',')[0])
y2 = int(pos[2].split(',')[1])
x3 = int(pos[3].split(',')[0])
y3 = int(pos[3].split(',')[1])
x4 = int(pos[4].split(',')[0])
y4 = int(pos[4].split(',')[1])
x5 = int(pos[5].split(',')[0])
y5 = int(pos[5].split(',')[1])
x6 = int(pos[6].split(',')[0])
y6 = int(pos[6].split(',')[1])
x7 = int(pos[7].split(',')[0])
y7 = int(pos[7].split(',')[1])
x8 = int(pos[8].split(',')[0])
y8 = int(pos[8].split(',')[1])
if myItem in p1:
click(x0, y0)
print("TopLeft")
if myItem in p2:
click(x1, x1)
print("TopMiddle")
if myItem in p3:
click(x2, x2)
print("TopRight")
if myItem in p4:
click(x3, x3)
print("MiddleLeft")
if myItem in p5:
click(x4, x4)
print("MiddleMiddle")
if myItem in p6:
click(x5, x5)
print("MiddleRight")
if myItem in p7:
click(x6, x6)
print("LeftLeft")
if myItem in p8:
click(x7, y7)
print("LeftMiddle")
if myItem in p9:
click(x8, y8)
print("LeftRight")
click(x8, y8 + 60)
from clarifai.client import ClarifaiApi
app = ClarifaiApi()
result = app.tag_image_urls('http://images.hellogiggles.com/uploads/2015/11/30/o-DAWSONS-CREEK-REUNION-facebook.jpg')
print(result)
def test_tag_one_video(self):
api = ClarifaiApi()
response = api.tag_image_urls(self.video_url)
self.assertTrue(response)
self.assertTrue(response['results'][0]['url'] == self.video_url)
import time import RPi.GPIO as io io.setmode(io.BCM) import sys, os, requests import picamera import glob from clarifai.client import ClarifaiApi #from urllib2 import Request, urlopen #import unirest #import json clarifai_api = ClarifaiApi() # assumes environment variables are set. pir_pin = 18 io.setup(pir_pin, io.IN) # activate input category = ['car','auto','cars','vehicle','girl','boy','man','woman','human'] DIR = '../test_images/' length_category = len(category) camera = picamera.PiCamera() camera.ISO = 1000 camera.hflip = True camera.vflip = True #camera.framerate = 0.01 camera.shutter_speed = 30000 camera.awb_mode ='auto' camera.meter_mode = 'average'
def test_get_info(self):
api = ClarifaiApi()
response = api.get_info()
self.assertTrue(response.get('api_version'))
self.assertTrue(len(response) > 0)
def get_client(self, *args, **kwargs): return ClarifaiApi()
from clarifai.client import ClarifaiApi
from tkinter.filedialog import askopenfilename
from nltk.util import ngrams
import webbrowser
app_id = '6XIVPtSr1oEE6WeFi5RPARxZP52jTZ99GJ8Dz9du'
client_secret = '2A-b8xB6kzmeZJp7suqstJ3L67BzmMcoc-ehOT9b'
clarifai_api = ClarifaiApi(app_id, client_secret)
n = input('File or URL?\n')
if n.lower() == 'file':
filename = askopenfilename()
result = clarifai_api.tag_images(open(filename, "rb"))
else:
filename2 = input("Enter URL")
result = clarifai_api.tag_image_urls(filename2)
classes = result['results'][0]['result']['tag']['classes']
p = int(input("Enter the level of precision 2-5\n"))
ng = ngrams(classes, p)
templist = []
for ik in ng:
templist.append(ik)
nresults = int(input("How many results would you like to see?"))
nsites = input("ebay or Amazon or both?")
def test_api_connection(self): api = ClarifaiApi() self.assertTrue(api)
B = o
print o, d, A
if B > 0.4:
D[S].append(E)
return D
def Cb(F, D):
i = D.keys()
for k in i:
for s in D[k]:
F.file_move(s['id'], k + "/" + s['id'][s['id'].rfind("/") + 1:])
print "Welcome to Mirage!"
x = ClarifaiApi()
m = U(F, y)
c, ca, sd = CF(m, 5)
print ca
t = Cy(m, ca, 5)
Cm(t)
h = CE("clusters/", "sample_photos_new/")
for i in h.items():
print i
Cb(F, h)
Cr(5)
if CV(F.metadata("sample_photos_new/")["contents"]) != 0:
m = U(F, "sample_photos_new/")
c, ca, sd = CF(m, 2)
print ca
t = Cy(m, ca, 2)
