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import urllib.request | |
import json | |
from pymongo import MongoClient | |
import time | |
from multiprocessing import Pool | |
DEEP_DRESS_WGET = 'http://localhost/wget/?url=' | |
DEEP_DRESS_PREDICT = 'http://localhost/predict/' | |
def wget_deep_dress(url): | |
serviceurl = DEEP_DRESS_WGET + url | |
response = urllib.request.urlopen(serviceurl) | |
f = response.read() | |
j = json.loads(f.decode('utf-8')) | |
return(j['file_id']) | |
def predict_deep_dress(file_id, top_n): | |
serviceurl = DEEP_DRESS_PREDICT + '?file_id=' + file_id + '&top_n=' + top_n | |
response = urllib.request.urlopen(serviceurl) | |
f = response.read() | |
j = json.loads(f.decode('utf-8')) | |
return(j) | |
client = MongoClient() | |
db = client.DeepDress | |
instagram = db.InstagramV4 | |
matches = db.MatchesV4 | |
# already tagged | |
ids = set([m['_id'] for m in matches.find()]) | |
def match_and_save(i): | |
try: | |
if (i['_id'] not in ids): | |
file_id = wget_deep_dress(i['image']) | |
preds = predict_deep_dress(file_id, '3') | |
result = matches.insert({'_id' : i['_id'], 'prediction' : preds}) | |
time.sleep(1) # Be nice | |
return(1) | |
except: | |
return(0) | |
pool = Pool(processes=5) # Don't make this too high - rate limits | |
totals = pool.map(match_and_save, instagram.find()) | |
print(sum(totals), len(totals)) |
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