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)