From a4006ea4f7024fe850543be7975fc6b8c845e39d Mon Sep 17 00:00:00 2001 From: inglada <jordi.inglada@cesbio.eu> Date: Fri, 8 Jun 2018 23:19:34 +0200 Subject: [PATCH] Typo in command line example --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 15b1c35..350281d 100644 --- a/README.md +++ b/README.md @@ -327,7 +327,7 @@ otbcli_PatchesExtraction -in spot7.tif -patchsizex 16 -patchsizey 16 -vec sample That's it. Now we have two images for patches and labels. If we wanna, we can split them to distinguish test/validation groups (with the **ExtractROI** application for instance). But here, we will just perform some fine tuning of our model, located in the `outmodel` directory. Our model is quite basic. It has two input placeholders, **x1** and **y1** respectively for input patches (with size 16x16) and input reference labels (with size 1x1). We named **prediction** the tensor that predict the labels and the optimizer that perform the stochastic gradient descent is an operator named **optimizer**. We perform the fine tuning and we export the new model variables in the `newvars` folder. Let's use our **TensorflowModelTrain** application to perform the training of this existing model. ``` -otbcli_TensorflowModelTrain -model.dir /path/to/oursavedmodel -training.targetnodesnames optimizer -training.source1.il samp_patches.tif -training.source1.fovx 16 -training.source1.fovy 16 -training.source1.placeholder x1 -training.source2.il samp_labels.tif -training.source2.fovx 1 -training.source2.fovy 1 -training.source2.placeholder -y1 -model.saveto newvars +otbcli_TensorflowModelTrain -model.dir /path/to/oursavedmodel -training.targetnodesnames optimizer -training.source1.il samp_patches.tif -training.source1.fovx 16 -training.source1.fovy 16 -training.source1.placeholder x1 -training.source2.il samp_labels.tif -training.source2.fovx 1 -training.source2.fovy 1 -training.source2.placeholder y1 -model.saveto newvars ``` Note that we could also have performed validation in this step. In this case, the `validation.source2.placeholder` would be different than the `training.source2.placeholder`, and would be **prediction**. This way, the program know what is the target tensor to evaluate. -- GitLab