Merge branch 'release/v0.1.0'

.gitignore

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+# project data
+data
+data_svm
+saved_models
+threshold_map
+models_info
+
+.python-version
+__pycache__
+
+# by default avoid model files and png files
+*.h5
+*.png
+!saved_models/*.h5
+!saved_models/*.png
+.vscode

LICENCE

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+MIT License
+Copyright (c) <year> <copyright holders>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+

README.md

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+# Noise detection using SVM
+
+## Requirements
+
+```
+pip install -r requirements.txt
+```
+
+## How to use
+
+### Multiple folders and scripts are availables :
+
+
+- **fichiersSVD/\*** : all scene files information (zones of each scene, SVD descriptor files information and so on...).
+- **fichiersSVD_light/\*** : all scene files information (zones of each scene, SVD descriptor files information and so on...) but here with reduction of information for few scenes. Information used in our case.
+- **models/*.py** : all models developed to predict noise in image.
+- **data_svm/\*** : folder which will contain all *.train* & *.test* files in order to train model.
+- **saved_models/*.joblib** : all scikit learn models saved.
+- **models_info/*.md** : all markdown files generated to get quick information about model performance and prediction.
+
+### Scripts for generating data files
+
+Two scripts can be used for generating data in order to fit model :
+- **generate_data_svm.py** : zones are specified and stayed fixed for each scene
+- **generate_data_svm_random.py** : zones are chosen randomly (just a number of zone is specified)
+
+
+**Remark** : Note here that all python script have *--help* command.
+
+```
+python generate_data_svm.py --help
+
+python generate_data_svm.py --output xxxx --interval 0,20  --kind svdne --scenes "A, B, D" --zones "0, 1, 2" --percent 0.7 --sep : --rowindex 1
+```
+
+Parameters explained : 
+- **output** : filename of data (which will be split into two parts, *.train* and *.test* relative to your choices).
+- **interval** : the interval of data you want to use from SVD vector.
+- **kind** : kind of data ['svd', 'sdvn', 'sdvne']; not normalize, normalize vector only and normalize together.
+- **scenes** : scenes choice for training dataset.
+- **zones** : zones to take for training dataset.
+- **percent** : percent of data amount of zone to take (choose randomly) of zone
+- **sep** : output csv file seperator used
+- **rowindex** : if 1 then row will be like that 1:xxxxx, 2:xxxxxx, ..., n:xxxxxx
+
+### Train model
+
+This is an example of how to train a model
+
+```python
+python models/xxxxx.py --data 'data_svm/xxxxx.train' --output 'model_file_to_save'
+```
+
+### Predict image using model
+
+Now we have a model trained, we can use it with an image as input :
+
+```python
+python predict_noisy_image_svd_lab.py --image path/to/image.png --interval "x,x" --model saved_models/xxxxxx.joblib --mode 'svdn'
+```
+
+The model will return only 0 or 1 :
+- 1 means noisy image is detected.
+- 0 means image seem to be not noisy.
+
+### Predict scene using model
+
+Now we have a model trained, we can use it with an image as input :
+
+```python
+python prediction_scene.py --data path/to/xxxx.csv --model saved_model/xxxx.joblib --output xxxxx --scene xxxx
+```
+**Remark** : *scene* parameter expected need to be the correct name of the Scene.
+
+## Others scripts
+
+### Test model on all scene data
+
+In order to see if a model well generalized, a bash script is available :
+
+```bash
+bash testModelByScene.sh '100' '110' 'saved_models/xxxx.joblib' 'svdne'
+```
+
+Parameters list :
+- 1 : Begin of interval of data from SVD to use
+- 2 : End of interval of data from SVD to use
+- 3 : Model we want to test
+- 4 : Kind of data input used by trained model
+
+
+### Get treshold map 
+
+Main objective of this project is to predict as well as a human the noise perception on a photo realistic image. Human threshold is available from training data. So a script was developed to give the predicted treshold from model and compare predicted treshold from the expected one.
+
+```python
+python predict_noisy_image.py --interval "x,x" --model 'saved_models/xxxx.joblib' --mode ["svd", "svdn", "svdne"] --limit_detection xx
+```
+
+Parameters list :
+- **model** : mode file saved to use
+- **interval** : the interval of data you want to use from SVD vector.
+- **mode** : kind of data ['svd', 'sdvn', 'sdvne']; not normalize, normalize vector only and normalize together.
+- **limit_detection** : number of not noisy images found to stop and return threshold (integer).
+
+### Display model performance information
+
+Another script was developed to display into Mardown format the performance of a model.
+
+The content will be divised into two parts :
+- Predicted performance on all scenes
+- Treshold maps obtained from model on each scenes
+
+The previous script need to already have ran to obtain and display treshold maps on this markdown file.
+
+```python
+python save_model_result_in_md.py --interval "xx,xx" --model saved_models/xxxx.joblib --mode ["svd", "svdn", "svdne"]
+```
+
+Parameters list :
+- **model** : mode file saved to use
+- **interval** : the interval of data you want to use from SVD vector.
+- **mode** : kind of data ['svd', 'sdvn', 'sdvne']; not normalize, normalize vector only and normalize together.
+
+
+Markdown file is saved using model name into **models_info** folder.
+
+### Others...
+
+All others bash scripts are used to combine and run multiple model combinations...
+
+## How to contribute
+
+This git project uses [git-flow](https://danielkummer.github.io/git-flow-cheatsheet/) implementation. You are free to contribute to it.

fichiersSVD/Appart1opt02/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone00/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone00/seuilExpe

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+00313

fichiersSVD/Appart1opt02/zone01/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone01/seuilExpe

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+00312

fichiersSVD/Appart1opt02/zone02/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone02/seuilExpe

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fichiersSVD/Appart1opt02/zone03/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone03/seuilExpe

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+00271

fichiersSVD/Appart1opt02/zone04/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone04/seuilExpe

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+00310

fichiersSVD/Appart1opt02/zone05/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone05/seuilExpe

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+00301

fichiersSVD/Appart1opt02/zone06/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone06/seuilExpe

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+00308

fichiersSVD/Appart1opt02/zone07/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone07/seuilExpe

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+00235

fichiersSVD/Appart1opt02/zone08/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone08/seuilExpe

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+00248

fichiersSVD/Appart1opt02/zone09/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone09/seuilExpe

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+00292

fichiersSVD/Appart1opt02/zone10/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10

fichiersSVD/Appart1opt02/zone10/seuilExpe

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+00222

fichiersSVD/Appart1opt02/zone11/config

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+appartAopt_00900.png
+appartAopt_
+00020
+00900
+10