def get_sift_dict(training_imgs, base_folder = TRAINING_PATH):
''' given a list of image names (`training_imgs`) contained in the folder `base_folder`, return a dictionary mapping each image filename to its sift matrix (a matrix of keypoints) '''
sift = Sift()
sift_dict = {}
mat_indices = {}
for i, img in enumerate(training_imgs):
sift_dict[img] = sift.extract_sift(os.path.join(base_folder, img))
return sift_dict
def __init__(self,
train_loader,
test_loader,
valida_folder,
validation=False,
sift_size=1152,
n_classes=10,
dropOut=True,
bestModel_allLR=False,
lrPair=[0.05, 0.05, 0.01],
epochNum=350):
self.model = None
self.train_loader = train_loader
self.test_loader = test_loader
self.valida_folder = valida_folder
self.validation = validation
self.dropOut = dropOut
self.global_loss = 100000000.0
self.global_acc = 0
self.global_model_path = './'
self.lr = 0
self.cuda = torch.cuda.is_available()
self.train_batch_size = 256
self.test_batch_size = 64
self.best_loss = float("inf")
self.best_epoch = -1
self.dataset_path = './cifar10'
self.gsync_save = True
self.bestModel_allLR = bestModel_allLR
self.lrPair = lrPair
self.epochNum = epochNum
self.sift_size = sift_size
self.n_classes = n_classes
self.sift = Sift()
def cv_sift():
data = request.get_json(silent=True)
image = data['image']
img = Sift(image)
with open('./output/' + image[:-4] + '/' + image[:-4] + '.jpg', 'rb') as f:
f = f.read()
img_stream = base64.b64encode(f).decode()
return img_stream
def __init__(self, distrDir): Sift.__init__(self, distrDir) self.thresh=500 self.octaves=4 self.layers=2
def __init__(self, distrDir):
Sift.__init__(self, distrDir)
def __init__(self, distrDir):
Sift.__init__(self, distrDir)
# ~mikey
#rss_tools
from sift import Sift
#imports
import feedparser
from bs4 import BeautifulSoup
import sqlite3
from sqlite3 import Error
import requests
#rss.app currently Broken
rss_urls = [
r"http://rss.slashdot.org/Slashdot/slashdotMain", #Slashdot
r"https://www.popsci.com/arcio/rss/", #Popsci
r"https://www.motherjones.com/feed/", #Mother Jones
r"http://science.sciencemag.org/rss/express.xml", #Science Magazine
#r"https://rss.app/feeds/JyMVgKu36v8JT4H0.xml", #ny times business
#r"https://rss.app/feeds/uVCDwng32TgGk0nJ.xml", # ny times world
#r"https://rss.app/feeds/fHPzIIzHJVqtIjr3.xml", #Entrpreneur
#r"https://rss.app/feeds/1Pqsw7njparMZi7B.xml", #wired
#r"https://rss.app/feeds/feANofWEfawQKkQr.xml", #Fast Company
r"https://plato.stanford.edu/rss/sep.xml", #Philosophy Encyclopedia
r"http://feeds.feedburner.com/tedtalks_video", #ted Talk RSS Feed
r"",
r""
]
for feed in rss_urls:
Sift(feed, 'wordsort.db')