Commit f1c20894 authored by Cresson Remi's avatar Cresson Remi
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DOC: add Gaetano et al. reference for two-branch CNN net

parent 4984bd44
...@@ -245,7 +245,7 @@ otbcli_TensorflowModelServe \ ...@@ -245,7 +245,7 @@ otbcli_TensorflowModelServe \
It's common that very high resolution products are composed with a panchromatic channel at high-resolution (Pan), and a multispectral image generally at lower resolution (MS). It's common that very high resolution products are composed with a panchromatic channel at high-resolution (Pan), and a multispectral image generally at lower resolution (MS).
This model inputs separately the two sources (Pan and MS) separately. This model inputs separately the two sources (Pan and MS) separately.
Gaetano, R., Ienco, D., Ose, K., & Cresson, R. (2018). A two-branch CNN architecture for land cover classification of PAN and MS imagery. Remote Sensing, 10(11), 1746. See: Gaetano, R., Ienco, D., Ose, K., & Cresson, R. (2018). A two-branch CNN architecture for land cover classification of PAN and MS imagery. Remote Sensing, 10(11), 1746.
<img src ="../doc/images/savedmodel_simple_pxs_fcn.png" /> <img src ="../doc/images/savedmodel_simple_pxs_fcn.png" />
...@@ -290,13 +290,14 @@ otbcli_TensorflowModelServe \ ...@@ -290,13 +290,14 @@ otbcli_TensorflowModelServe \
Here we perform the land cover map at the same resolution as the Pan image. Here we perform the land cover map at the same resolution as the Pan image.
Do do this, we set the Pan image as the first source in the **TensorflowModelServe** application. Do do this, we set the Pan image as the first source in the **TensorflowModelServe** application.
Note that this model can not be applied in a fully convolutional fashion at the Pan image resolution.
We hence perform the processing in patch-based mode.
``` ```
otbcli_TensorflowModelServe \ otbcli_TensorflowModelServe \
-source1.il $pan -source1.rfieldx 32 -source1.rfieldy 32 -source1.placeholder "x2" \ -source1.il $pan -source1.rfieldx 32 -source1.rfieldy 32 -source1.placeholder "x2" \
-source2.il $ms -source2.rfieldx 8 -source2.rfieldy 8 -source2.placeholder "x1" \ -source2.il $ms -source2.rfieldx 8 -source2.rfieldy 8 -source2.placeholder "x1" \
-model.dir $modeldir \ -model.dir $modeldir \
-model.fullyconv on \
-output.names "prediction" \ -output.names "prediction" \
-out $output_classif -out $output_classif
``` ```
...@@ -309,7 +310,5 @@ otbcli_TensorflowModelServe \ ...@@ -309,7 +310,5 @@ otbcli_TensorflowModelServe \
-source2.il $pan -source2.rfieldx 32 -source2.rfieldy 32 -source2.placeholder "x2" \ -source2.il $pan -source2.rfieldx 32 -source2.rfieldy 32 -source2.placeholder "x2" \
-model.dir $modeldir \ -model.dir $modeldir \
-model.fullyconv on \ -model.fullyconv on \
-output.names "prediction" \
-output.spcscale 0.25 \
-out $output_classif -out $output_classif
``` ```
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