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@cancan101
cancan101 / get_state_v1.py
Last active Aug 29, 2015
Get Solid-Filled Image for State Map v1
View get_state_v1.py
def get_state_v1(state):
url = make_url(state)
IN = load_gif_url(url)
#Drop the text at the top
IN = IN[150:]
#Convert 3 color channels to 1
IN_bw = get_bw(IN)
@cancan101
cancan101 / load_gif_url.py
Last active Aug 29, 2015
OpenCV Load GIF URL
View load_gif_url.py
from PIL import Image
import requests
import tempfile
def load_gif_url(url):
with tempfile.NamedTemporaryFile(suffix=".gif") as f:
f.write(requests.get(url).content)
f.flush()
img = Image.open(f.name)
@cancan101
cancan101 / image_utils.py
Last active Aug 29, 2015
OpenCV Image Utilities
View image_utils.py
def get_bw(src):
return cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
def show_color(src):
plt.imshow(cv2.cvtColor(src, cv2.COLOR_BGR2RGB))
_ = plt.xticks([]), plt.yticks([])
def show_bw(bw):
plt.imshow(bw, cmap='gray')
_ = plt.xticks([]), plt.yticks([])
@cancan101
cancan101 / get_state_v0.py
Last active Aug 29, 2015
Get Solid-Filled Image for State Map v0
View get_state_v0.py
def get_state_v0(state):
url = make_url(state)
IN = load_gif_url(url)
#Drop the text at the top
IN = IN[150:]
#Convert 3 color channels to 1
IN_bw = get_bw(IN)
@cancan101
cancan101 / Map Recognition.ipynb
Last active Aug 29, 2015
Notebook Demonstrating Technique to Identify US State Maps
View Map Recognition.ipynb
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@cancan101
cancan101 / MLP Hu.ipynb
Created Jul 21, 2014
Notebook Demonstrating Using MLPs to Classify State Map Images
View MLP Hu.ipynb
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View Linear Interpolator Test Pub.ipynb
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@cancan101
cancan101 / .numpy-site.cfg
Created Aug 14, 2014
numpy-site.cfg for building against openblas
View .numpy-site.cfg
[default]
library_dirs = /usr/local/lib
[atlas]
atlas_libs = openblas
library_dirs = /usr/local/lib
[lapack]
lapack_libs = openblas
library_dirs = /usr/local/lib
[openblas]
libraries = openblas
View broken_convfft.py
import os
os.environ['THEANO_FLAGS']="optimizer_including=conv_fft_valid:conv_fft_full"
from pylearn2.config import yaml_parse
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
import numpy as np
train_str = """!obj:pylearn2.train.Train {
dataset: &train !import '__main__ .train_set',
View CuIFFT_issue.py
import os
os.environ['THEANO_FLAGS']="optimizer_including=conv_fft_valid:conv_fft_full"
from pylearn2.config import yaml_parse
from pylearn2.datasets.dense_design_matrix import DenseDesignMatrix
import numpy as np
train_str = """!obj:pylearn2.train.Train {
dataset: &train !import '__main__ .train_set',
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