Comments (1)
Take a look at the helper.py method get_test_output line 101. There the FCNN is used for inference.
im_softmax = sess.run(
[tf.nn.softmax(logits)],
{keep_prob: 1.0, image_pl: [image]})
im_softmax = im_softmax[0][:, 1].reshape(image_shape[0], image_shape[1])
segmentation = (im_softmax > 0.5).reshape(image_shape[0], image_shape[1], 1)
mask = np.dot(segmentation, np.array([[0, 255, 0, 127]]))
mask = scipy.misc.toimage(mask, mode="RGBA")
street_im = scipy.misc.toimage(image)
street_im.paste(mask, box=None, mask=mask)
This code is provided by Udacity.
from carnd-semantic-segmentation-p2.
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