# Clarifai
CLARIFAI_APP_ID = YOUR_CLARIFAI_APP_ID
CLARIFAI_APP_SECRET = YOUR_CLARIFAI_APP_SECRET
clarifai_api = ClarifaiApi(app_id=CLARIFAI_APP_ID, app_secret=CLARIFAI_APP_SECRET)
#results = clarifai_api.tag_image_urls('http://d21vu35cjx7sd4.cloudfront.net/dims3/MMAH/thumbnail/645x380/quality/90/?url=http%3A%2F%2Fs3.amazonaws.com%2Fassets.prod.vetstreet.com%2F3a%2F54%2F5ae8bfcc41b381c27a792e0dd891%2FAP-KWDHXS-645sm8113.jpg')
#results = clarifai_api.tag_urls("http://d21vu35cjx7sd4.cloudfront.net/dims3/MMAH/thumbnail/645x380/quality/90/?url=http%3A%2F%2Fs3.amazonaws.com%2Fassets.prod.vetstreet.com%2F3a%2F54%2F5ae8bfcc41b381c27a792e0dd891%2FAP-KWDHXS-645sm8113.jpg")
#results = clarifai_api.tag_urls("http://www.midtownhotelnyc.com/resourcefiles/homeimages/hilton-garden-inn-new-york-manhattan-midtown-east-home1-top.jpg")
userInput = input('Please enter your image URL: ')
results = clarifai_api.tag_urls(userInput)
for result in results.get('results'):
tag = result['result']['tag']['classes']
break
# debug
#print(tag)
# debug
#print (tag)
taglist = list()
i = 0
for t in tag:
if (i==5):
break
| df.image_url.str.contains('.png'))][[
'image_order', 'image_url'
]].sort_values(['image_order'
])['image_url'].tolist()
count = len(
df[(df.gender == gender) & (df.name == name) &
(df.clarifai_status == 'OK') & (df.predicted != '-')])
begin = 0
print(gender, name, count, len(urls))
while count < args.count and begin < len(urls):
need = args.count - count
if args.batch and need > args.batch:
need = args.batch
sel_urls = urls[begin:begin + need]
try:
result = clarifai_api.tag_urls(sel_urls)
for r in result['results']:
url = r['url'].encode('utf-8')
status = r['status_code']
try:
_id = df[(df.gender == gender)
& (df.name == name) &
(df.image_url == url)].index[0]
df.loc[_id, 'clarifai_status'] = status
if status == 'OK':
tags = r['result']['tag']['classes']
probs = r['result']['tag']['probs']
msum = 0
fsum = 0
for t in ['man', 'men', 'boy', 'actor']:
try:
try:
for gender in df['gender'].unique():
names = df[df.gender == gender].name.unique().tolist()
for name in names:
urls = df[(df.gender == gender) & (df.name == name) & df.clarifai_status.isnull() & (df.image_url.str.contains('.jpg') | df.image_url.str.contains('.jpeg') | df.image_url.str.contains('.png'))][['image_order', 'image_url']].sort_values(['image_order'])['image_url'].tolist()
count = len(df[(df.gender == gender) & (df.name == name) & (df.clarifai_status == 'OK') & (df.predicted != '-')])
begin = 0
print(gender, name, count, len(urls))
while count < args.count and begin < len(urls):
need = args.count - count
if args.batch and need > args.batch:
need = args.batch
sel_urls = urls[begin:begin+need]
try:
result = clarifai_api.tag_urls(sel_urls)
for r in result['results']:
url = r['url'].encode('utf-8')
status = r['status_code']
try:
_id = df[(df.gender == gender) & (df.name == name) & (df.image_url == url)].index[0]
df.loc[_id, 'clarifai_status'] = status
if status == 'OK':
tags = r['result']['tag']['classes']
probs = r['result']['tag']['probs']
msum = 0
fsum = 0
for t in ['man', 'men', 'boy', 'actor']:
try:
idx = tags.index(t)
msum += probs[idx]
