[1/36] conv1_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 1026, 1368, 64)
/usr/lib/pymodules/python2.7/matplotlib/collections.py:548: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
if self._edgecolors == 'face':
[2/36] relu1_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 1026, 1368, 64)
[3/36] conv1_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 1026, 1368, 64)
[4/36] relu1_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 1026, 1368, 64)
[5/36] pool1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 513, 684, 64)
[6/36] conv2_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 513, 684, 128)
[7/36] relu2_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 513, 684, 128)
[8/36] conv2_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 513, 684, 128)
[9/36] relu2_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 513, 684, 128)
[10/36] pool2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 128)
[11/36] conv3_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[12/36] relu3_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[13/36] conv3_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[14/36] relu3_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[15/36] conv3_3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[16/36] relu3_3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[17/36] conv3_4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[18/36] relu3_4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 257, 342, 256)
[19/36] pool3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 256)
[20/36] conv4_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[21/36] relu4_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[22/36] conv4_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[23/36] relu4_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[24/36] conv4_3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[25/36] relu4_3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[26/36] conv4_4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[27/36] relu4_4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 129, 171, 512)
[28/36] pool4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[29/36] conv5_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[30/36] relu5_1
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[31/36] conv5_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[32/36] relu5_2
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[33/36] conv5_3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[34/36] relu5_3
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[35/36] conv5_4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)
[36/36] relu5_4
Type of 'features' is <type 'numpy.ndarray'>
Shape of 'features' is (1, 65, 86, 512)