1. Distinguishing floor plan image
(1) (input)64x64x3 ---> conv + pool
(2) 32x32x32 ---> conv + pool
(3) 16x16x64 ---> flatten + conv
2. Extracting the truth part
(1) (input)64x64x3 ---> conv + pool
(2) 32x32x32 ---> conv + pool
(3) 16x16x64 ---> transpose, stride = 2
(4-2) 32x32x32 ---> transpose, stride = 2
pred = sess.run(annotation_pred,feed_dict)
pred = np.squeeze(pred,axis=3)
CUTOUT_FCN.py train, need the 8layer model from RECG_CNN2.py.
或
或