diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index bd41bbf9a6151e4c3b0f47b7eab4147f0aa263d4..17526bf73ddc1c463d4545161832e17b4e1d047f 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -24,7 +24,7 @@ image: $BRANCH_IMAGE
workflow:
rules:
- if: $CI_MERGE_REQUEST_ID || $CI_COMMIT_REF_NAME =~ /master/ # Execute jobs in merge request context, or commit in master branch
-
+
stages:
- Build
- Static Analysis
@@ -36,7 +36,7 @@ stages:
.docker_build_base:
allow_failure: false
- tags: [godzilla]
+ tags: [ godzilla ]
image: docker:latest
services:
- name: docker:dind
@@ -45,7 +45,7 @@ stages:
timeout: 10 hours
-docker image:
+dev docker image build:
extends: .docker_build_base
stage: Build
except:
@@ -94,14 +94,21 @@ docker image:
stage: Static Analysis
allow_failure: true
-flake8:
+
+.py_static_analysis_base:
extends: .static_analysis_base
+ rules:
+ - changes:
+ - otbtf/**/*
+
+flake8:
+ extends: .py_static_analysis_base
script:
- sudo pip install flake8
- flake8 $OTBTF_SRC/otbtf --exclude=tensorflow_v1x
pylint:
- extends: .static_analysis_base
+ extends: .py_static_analysis_base
script:
- sudo pip install pylint
- pylint $OTBTF_SRC/otbtf --ignore=tensorflow_v1x
@@ -115,38 +122,49 @@ codespell:
cppcheck:
extends: .static_analysis_base
+ rules:
+ - changes:
+ - app/**/*
+ - include/**/*
script:
- sudo apt update && sudo apt install cppcheck -y
- cd $OTBTF_SRC/ && cppcheck --enable=all --error-exitcode=1 -I include/ --suppress=missingInclude --suppress=unusedFunction .
-.doc_base:
+pages:
stage: Documentation
+ variables:
+ PTH: "public_test"
+ rules:
+ - changes:
+ - doc/**/*
+ - "*.{md,txt}"
+ - mkdocs.yml
+ - .readthedocs.yaml
+ - if: $CI_COMMIT_REF_NAME == /master/
+ variables:
+ PTH: "public"
before_script:
- pip install -r doc/doc_requirements.txt
- artifacts:
- paths:
- - public
- - public_test
-
-pages_test:
- extends: .doc_base
- except:
- - master
- script:
- - mkdocs build --site-dir public_test
-
-pages:
- extends: .doc_base
- only:
- - master
script:
- - mkdocs build --site-dir public
+ - mkdocs build --site-dir $PTH
artifacts:
paths:
- - public
+ - $PTH
.tests_base:
- tags: [godzilla]
+ tags: [ godzilla ]
+ rules:
+ - changes:
+ - app/**/*
+ - include/**/*
+ - otbtf/**/*
+ - test/**/*
+ - tools/**/*
+ - .gitlab-ci.yml
+ - Dockerfile
+ - otb-module.cmake
+ - CMakeLists.txt
+ - setup.py
artifacts:
paths:
- $ARTIFACT_TEST_DIR/*.*
@@ -157,7 +175,7 @@ ctest:
extends: .tests_base
stage: Test
script:
- - sudo apt update && sudo apt install -y git-lfs
+ - sudo apt update && sudo apt install -y git-lfs
- cd /src/otb/otb && sudo git lfs fetch --all && sudo git lfs pull
- cd $OTB_BUILD/
- sudo ctest -L OTBTensorflow
@@ -183,7 +201,7 @@ crc_book:
- TMPDIR=$CRC_BOOK_TMP python -m pytest --junitxml=$CI_PROJECT_DIR/report_tutorial.xml $OTBTF_SRC/test/tutorial_unittest.py
after_script:
- cp $CRC_BOOK_TMP/*.* $ARTIFACT_TEST_DIR/
-
+
sr4rs:
extends: .applications_test_base
script:
@@ -260,7 +278,7 @@ deploy_cpu-dev-testing:
extends: .docker_build_base
stage: Ship
only:
- - master
+ - tags
deploy_cpu:
extends: .ship base
diff --git a/doc/app_sampling.md b/doc/app_sampling.md
index b79ba7f4653e5c1951c85757571430b17fa63580..9a9fc047e2c85d4b3f410d28271b9e15c4ffa8d3 100644
--- a/doc/app_sampling.md
+++ b/doc/app_sampling.md
@@ -84,7 +84,7 @@ specific field of the input vector data.
Typically, the *class* field can be used to generate a dataset suitable for a
model that performs pixel wise classification.
-
+
The application description can be displayed using:
diff --git a/doc/app_training.md b/doc/app_training.md
index eb3f4708f37121d5f63181eb2c2b08a783da9df9..c1e731ef65b69f936291a74a5377a25c3e8d238f 100644
--- a/doc/app_training.md
+++ b/doc/app_training.md
@@ -47,7 +47,7 @@ patches images, a convenient method consist in reading patches images as numpy
arrays using OTB applications (e.g. `ExtractROI`) or GDAL, then do a
`numpy.reshape` to the dimensions wanted.
-
+
The application description can be displayed using:
diff --git a/doc/docker_use.md b/doc/docker_use.md
index 81211066432c95f60e546ae815ec31acaca8f593..323e42683848fc136051e08a68fa350853e9cd69 100644
--- a/doc/docker_use.md
+++ b/doc/docker_use.md
@@ -21,16 +21,18 @@ Read more in the following sections.
Here is the list of the latest OTBTF docker images hosted on
[dockerhub](https://hub.docker.com/u/mdl4eo).
Since OTBTF >= 3.2.1 you can find the latest docker images on
-[gitlab.irstea.fr](https://gitlab.irstea.fr/remi.cresson/otbtf/container_registry).
-
-| Name | Os | TF | OTB | Description | Dev files | Compute capability |
-|------------------------------------------------------------------------------------| ------------- |-------|-------| ---------------------- | --------- | ------------------ |
-| **mdl4eo/otbtf:4.3.1-cpu** | Ubuntu Jammy | r2.14 | 9.0.0 | CPU, no optimization | no | 5.2,6.1,7.0,7.5,8.6|
-| **mdl4eo/otbtf:4.3.1-cpu-dev** | Ubuntu Jammy | r2.14 | 9.0.0 | CPU, no optimization (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
-| **mdl4eo/otbtf:4.3.1-gpu** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU, no optimization | no | 5.2,6.1,7.0,7.5,8.6|
-| **mdl4eo/otbtf:4.3.1-gpu-dev** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU, no optimization (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
-| **gitlab.irstea.fr/remi.cresson/otbtf/container_registry/otbtf:4.3.1-gpu-opt** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU with opt. | no | 5.2,6.1,7.0,7.5,8.6|
-| **gitlab.irstea.fr/remi.cresson/otbtf/container_registry/otbtf:4.3.1-gpu-opt-dev** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU with opt. (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
+[gitlab.irstea.fr](https://gitlab.irstea.fr/remi.cresson/otbtf/container_registry)
+(before otbtf 4.3.0) and [forgemia](https://forgemia.inra.fr/orfeo-toolbox/otbtf/container_registry)
+(since otbtf 4.3.1).
+
+| Name | Os | TF | OTB | Description | Dev files | Compute capability |
+|---------------------------------------------------------------------| ------------- |-------|-------| ---------------------- | --------- | ------------------ |
+| **mdl4eo/otbtf:4.3.1-cpu** | Ubuntu Jammy | r2.14 | 9.0.0 | CPU, no optimization | no | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf:4.3.1-cpu-dev** | Ubuntu Jammy | r2.14 | 9.0.0 | CPU, no optimization (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf:4.3.1-gpu** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU, no optimization | no | 5.2,6.1,7.0,7.5,8.6|
+| **mdl4eo/otbtf:4.3.1-gpu-dev** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU, no optimization (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
+| **registry.forgemia.inra.fr/orfeo-toolbox/otbtf:4.3.1-gpu-opt** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU with opt. | no | 5.2,6.1,7.0,7.5,8.6|
+| **registry.forgemia.inra.fr/orfeo-toolbox/otbtf:4.3.1-gpu-opt-dev** | Ubuntu Jammy | r2.14 | 9.0.0 | GPU with opt. (dev) | yes | 5.2,6.1,7.0,7.5,8.6|
The list of older releases is available [here](#older-images).
diff --git a/otbtf/examples/tensorflow_v1x/__init__.py b/otbtf/examples/tensorflow_v1x/__init__.py
index c77256a480843e5f109dfe04174daac4d76b44fb..796e4cbd9cd41936aef2c63a42a001a5c194dedc 100644
--- a/otbtf/examples/tensorflow_v1x/__init__.py
+++ b/otbtf/examples/tensorflow_v1x/__init__.py
@@ -38,7 +38,7 @@ Predicted label is a single pixel, for an input patch of size 16x16 (for an inpu
The learning rate of the training operator can be adjusted using the *lr* placeholder.
The following figure summarizes this architecture.
-<img src ="https://gitlab.irstea.fr/remi.cresson/otbtf/-/raw/develop/doc/images/savedmodel_simple_cnn.png" />
+<img src ="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/raw/develop/doc/images/savedmodel_simple_cnn.png" />
## Generate the model
@@ -143,7 +143,7 @@ otbcli_TensorflowModelServe \\
The `create_savedmodel_simple_fcn.py` script enables you to create a fully
convolutional model which does not use any stride.
-<img src ="https://gitlab.irstea.fr/remi.cresson/otbtf/-/raw/develop/doc/images/savedmodel_simple_fcnn.png" />
+<img src ="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/raw/develop/doc/images/savedmodel_simple_fcnn.png" />
Thanks to that, once trained this model can be applied on the image to produce
a landcover map at the same resolution as the input image, in a fully
@@ -208,7 +208,7 @@ available parameters.
Let's train the M3 model from time series (TS) and Very High Resolution
Satellite (VHRS) patches images.
-<img src ="https://gitlab.irstea.fr/remi.cresson/otbtf/-/raw/develop/doc/images/model_training.png" />
+<img src ="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/raw/develop/doc/images/model_training.png" />
First, tell OTBTF that we want two sources: one for time series + one for
VHR image
@@ -255,7 +255,7 @@ otbcli_TensorflowModelTrain \\
Let's produce a land cover map using the M3 model from time series (TS) and
Very High Resolution Satellite image (VHRS)
-<img src ="https://gitlab.irstea.fr/remi.cresson/otbtf/-/raw/develop/doc/images/classif_map.png" />
+<img src ="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/raw/develop/doc/images/classif_map.png" />
Since we provide time series as the reference source (*source1*), the output
classes are estimated at the same resolution. This model can be run in
@@ -363,7 +363,7 @@ 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 ="https://gitlab.irstea.fr/remi.cresson/otbtf/-/raw/develop/doc/images/savedmodel_simple_pxs_fcn.png" />
+<img src ="https://forgemia.inra.fr/orfeo-toolbox/otbtf/-/raw/develop/doc/images/savedmodel_simple_pxs_fcn.png" />
Use `create_savedmodel_pxs_fcn.py` to generate this model.
diff --git a/setup.py b/setup.py
index 8519fb1132c1f889eb2edb6853132ff08c747538..c1a6294a84652766e30b1d698bda6f935671d051 100644
--- a/setup.py
+++ b/setup.py
@@ -12,7 +12,7 @@ setuptools.setup(
description="OTBTF: Orfeo ToolBox meets TensorFlow",
long_description=long_description,
long_description_content_type="text/markdown",
- url="https://gitlab.irstea.fr/remi.cresson/otbtf",
+ url="https://github.com/remicres/otbtf",
classifiers=[
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",