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self_taught_loc_test.py
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self_taught_loc_test.py
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import numpy as np
from skimage.data import imread
import unittest
from imgsegmentation import *
from configuration import *
from network import *
from self_taught_loc import *
class SelfTaughtLocTest(unittest.TestCase):
def setUp(self):
root = "/home/ironfs/scratch/vlg/Data/Images/ILSVRC2012/caffe_model_141118"
conf = Configuration(root=root)
netParams = NetworkCaffe1114Params(conf.caffe_model_spec, \
conf.caffe_model, \
conf.caffe_wnids_words, \
conf.caffe_avg_image, \
center_only = True,\
wnid_subset = [])
# instantiate network
self.net = Network.create_network(netParams)
# choose segmentation method (Matlab wrapper Felz through SS)
img_segmenter = ImgSegmMatWraper()
# instantiate STL object
self.stl_grayout = SelfTaughtLoc_Grayout(self.net, img_segmenter, \
min_sz_segm = 5, topC = 5,\
alpha = 1/3.0*np.ones((3,)), \
obfuscate_bbox = True, \
function_stl = 'similarity')
# instantiate STL object
self.stl_grayout_2 = SelfTaughtLoc_Grayout(self.net, img_segmenter, \
min_sz_segm = 5, topC = 5,\
alpha = 1/4.0*np.ones((4,)), \
obfuscate_bbox = True, \
function_stl = 'similarity+cnnfeature')
# instantiate STL object
self.stl_grayout_3 = SelfTaughtLoc_Grayout(self.net, img_segmenter, \
min_sz_segm = 5, topC = 5,
alpha = 1/4.0*np.ones((4,)), \
obfuscate_bbox = True, \
function_stl = 'similarity+cnnfeature', \
padding = 0.2)
def tearDown(self):
self.stl_grayout = None
self.stl_grayout_2 = None
self.stl_grayout_3 = None
def test_extract_stl_u(self):
# read image
img = imread('test_data/ILSVRC2012_val_00000001_n01751748.JPEG')
# resize image to fit the net input
image_resz = skimage.transform.resize(img,\
(self.net.get_input_dim(), self.net.get_input_dim()))
image_resz = skimage.img_as_ubyte(image_resz)
img_width, img_height = np.shape(image_resz)[0:2]
# perform stl unsupervised
segment_lists = self.stl_grayout.extract_greedy(image_resz)
# Control some elements
self.assertEqual(np.shape(segment_lists)[0], 4)
self.assertEqual(np.shape(segment_lists[0])[0], 217)
self.assertEqual(np.shape(segment_lists[1])[0], 123)
self.assertEqual(np.shape(segment_lists[2])[0], 93)
self.assertEqual(np.shape(segment_lists[3])[0], 47)
self.assertEqual(segment_lists[0][100]['mask'][0,0], False)
self.assertEqual(segment_lists[1][50]['mask'][10,10], True)
self.assertEqual(segment_lists[2][65]['mask'][0,0], False)
self.assertEqual(segment_lists[3][33]['mask'][30,10], True)
self.assertEqual(segment_lists[0][100]['bbox'].xmin, 87)
self.assertEqual(segment_lists[1][50]['bbox'].xmin, 41)
self.assertEqual(segment_lists[2][65]['bbox'].xmin, 9)
self.assertEqual(segment_lists[3][33]['bbox'].xmin, 73)
def test_extract_stl_u_cnnfeature(self):
# read image
img = imread('test_data/ILSVRC2012_val_00000001_n01751748.JPEG')
# resize image to fit the net input
image_resz = skimage.transform.resize(img,\
(self.net.get_input_dim(), self.net.get_input_dim()))
image_resz = skimage.img_as_ubyte(image_resz)
img_width, img_height = np.shape(image_resz)[0:2]
# perform stl unsupervised
segment_lists = self.stl_grayout_2.extract_greedy(image_resz)
# Control some elements
self.assertEqual(np.shape(segment_lists)[0], 4)
self.assertEqual(np.shape(segment_lists[0])[0], 217)
self.assertEqual(np.shape(segment_lists[1])[0], 123)
self.assertEqual(np.shape(segment_lists[2])[0], 93)
self.assertEqual(np.shape(segment_lists[3])[0], 47)
self.assertEqual(segment_lists[0][100]['mask'][0,0], False)
self.assertEqual(segment_lists[1][50]['mask'][10,10], True)
self.assertEqual(segment_lists[2][65]['mask'][0,0], False)
self.assertEqual(segment_lists[3][33]['mask'][30,10], False)
self.assertEqual(segment_lists[0][100]['bbox'].xmin, 87)
self.assertEqual(segment_lists[1][50]['bbox'].xmin, 41)
self.assertEqual(segment_lists[2][65]['bbox'].xmin, 170)
self.assertEqual(segment_lists[3][33]['bbox'].xmin, 0)
def test_extract_stl_u_cnnfeature_pad(self):
# read image
img = imread('test_data/ILSVRC2012_val_00000001_n01751748.JPEG')
# resize image to fit the net input
image_resz = skimage.transform.resize(img,\
(self.net.get_input_dim(), self.net.get_input_dim()))
image_resz = skimage.img_as_ubyte(image_resz)
img_width, img_height = np.shape(image_resz)[0:2]
# perform stl unsupervised
segment_lists = self.stl_grayout_3.extract_greedy(image_resz)
# Control some elements
self.assertEqual(np.shape(segment_lists)[0], 4)
self.assertEqual(np.shape(segment_lists[0])[0], 217)
self.assertEqual(np.shape(segment_lists[1])[0], 123)
self.assertEqual(np.shape(segment_lists[2])[0], 93)
self.assertEqual(np.shape(segment_lists[3])[0], 47)
self.assertEqual(segment_lists[0][100]['mask'][0,0], False)
self.assertEqual(segment_lists[1][50]['mask'][10,10], True)
self.assertEqual(segment_lists[2][65]['mask'][0,0], False)
self.assertEqual(segment_lists[3][33]['mask'][30,10], False)
self.assertEqual(segment_lists[0][100]['bbox'].xmin, 87)
self.assertEqual(segment_lists[1][50]['bbox'].xmin, 41)
self.assertEqual(segment_lists[2][65]['bbox'].xmin, 82)
self.assertEqual(segment_lists[3][33]['bbox'].xmin, 47)
# ------------ perform test ------------ #
if __name__ == '__main__':
unittest.main()