Commit 6a334231 authored by Cresson Remi's avatar Cresson Remi
Browse files

DOC: update documentation

parent 0f7c8ff2
......@@ -362,10 +362,13 @@ Then, we use the **TensorflowModelServe** application to produce the **predictio
otbcli_TensorflowModelServe -source1.il spot7.tif -source1.placeholder x1 -source1.rfieldx 16 -source1.rfieldy 16 -model.dir /tmp/my_new_model -output.names prediction -out map.tif uint8
```
## Models
## Begin with provided models
In the `python` folder are provided some ready-to-use deep networks, with documentation and scientific references.
See [here](doc/EXAMPLES.md) to see how to use the provided models.
Feel free to contribute with your own architecture!
## Tutorial
A tutorial is available at [MDL4EO's blog](https://mdl4eo.irstea.fr/2019/01/04/an-introduction-to-deep-learning-on-remote-sensing-images-tutorial/)
......@@ -129,11 +129,11 @@ The output class estimation is performed at pixel level.
### Generate the model
```
python create_model_ienco-m3_patchbased.py --outdir $modeldir
python create_savedmodel_ienco-m3_patchbased.py --outdir $modeldir
```
Note that you can adjust the number of classes for the model with the `--nclasses` option.
Type `python create_model_ienco-m3_patchbased.py --help` to see the other available parameters.
Type `python create_savedmodel_ienco-m3_patchbased.py --help` to see the other available parameters.
### Train the model
......@@ -197,7 +197,7 @@ This fully convolutional model performs binary semantic segmentation of large sc
### Generate the model
```
python create_model_maggiori17_fullyconv.py --outdir $modeldir
python create_savedmodel_maggiori17_fullyconv.py --outdir $modeldir
```
You can change the number of spectral bands of the input image that is processed with the model, using the `--n_channels` option.
......
......@@ -197,3 +197,37 @@ Check that the applications run properly from command line.
otbcli_TensorflowModelServe --help
```
The following output should be displayed:
```
Multisource deep learning classifier using TensorFlow. Change the OTB_TF_NSOURCES environment variable to set the number of sources.
Parameters:
-source1 <group> Parameters for source #1
MISSING -source1.il <string list> Input image (or list to stack) for source #1 (mandatory)
MISSING -source1.rfieldx <int32> Input receptive field (width) for source #1 (mandatory)
MISSING -source1.rfieldy <int32> Input receptive field (height) for source #1 (mandatory)
MISSING -source1.placeholder <string> Name of the input placeholder for source #1 (mandatory)
-model <group> model parameters
MISSING -model.dir <string> TensorFlow model_save directory (mandatory)
-model.userplaceholders <string list> Additional single-valued placeholders. Supported types: int, float, bool. (optional, off by default)
-model.fullyconv <boolean> Fully convolutional (optional, off by default, default value is false)
-output <group> Output tensors parameters
-output.spcscale <float> The output spacing scale, related to the first input (mandatory, default value is 1)
MISSING -output.names <string list> Names of the output tensors (mandatory)
-output.efieldx <int32> The output expression field (width) (mandatory, default value is 1)
-output.efieldy <int32> The output expression field (height) (mandatory, default value is 1)
-optim <group> This group of parameters allows optimization of processing time
-optim.disabletiling <boolean> Disable tiling (optional, off by default, default value is false)
-optim.tilesizex <int32> Tile width used to stream the filter output (mandatory, default value is 16)
-optim.tilesizey <int32> Tile height used to stream the filter output (mandatory, default value is 16)
MISSING -out <string> [pixel] output image [pixel=uint8/uint16/int16/uint32/int32/float/double/cint16/cint32/cfloat/cdouble] (default value is float) (mandatory)
-inxml <string> Load otb application from xml file (optional, off by default)
-progress <boolean> Report progress
-help <string list> Display long help (empty list), or help for given parameters keys
Use -help param1 [... paramN] to see detailed documentation of those parameters.
Examples:
otbcli_TensorflowModelServe -source1.il spot6pms.tif -source1.placeholder x1 -source1.rfieldx 16 -source1.rfieldy 16 -model.dir /tmp/my_saved_model/ -model.userplaceholders is_training=false dropout=0.0 -output.names out_predict1 out_proba1 -out "classif128tgt.tif?&streaming:type=tiled&streaming:sizemode=height&streaming:sizevalue=256"
```
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment