From 93c8501566649fa7bd3ff67d87ec2b2670f55118 Mon Sep 17 00:00:00 2001
From: ageorge <anjith.george@idiap.ch>
Date: Wed, 1 May 2019 16:35:39 +0200
Subject: [PATCH] mods and clean up
---
.../FASNet_config.py} | 10 +--
.../MCCNN_config.py} | 9 +--
.../mccnn/tifs2018/config/haralick_svm.py | 36 +++++----
.../tifs2018/config/{qm_lr.py => iqm_lr.py} | 2 +-
.../mccnn/tifs2018/extractor/HaralickRDWT.py | 2 -
.../mccnn/tifs2018/script/mean_fusion.py | 4 +-
.../{wmca_FASNet.py => wmca_fasnet.py} | 23 +-----
.../{wmca_mccnn_v1.py => wmca_mccnn.py} | 22 +----
buildout.cfg | 51 ++++++++++--
doc/running_baslines.md | 81 ++++++++++---------
setup.py | 13 +++
11 files changed, 129 insertions(+), 124 deletions(-)
rename bob/paper/mccnn/tifs2018/{extractor/wmca_config_pytorch_extractor_v1_FASNet.py => config/FASNet_config.py} (92%)
rename bob/paper/mccnn/tifs2018/{extractor/wmca_config_pytorch_extractor_v1.py => config/MCCNN_config.py} (95%)
rename bob/paper/mccnn/tifs2018/config/{qm_lr.py => iqm_lr.py} (99%)
rename bob/paper/mccnn/tifs2018/trainer_configs/{wmca_FASNet.py => wmca_fasnet.py} (86%)
rename bob/paper/mccnn/tifs2018/trainer_configs/{wmca_mccnn_v1.py => wmca_mccnn.py} (84%)
diff --git a/bob/paper/mccnn/tifs2018/extractor/wmca_config_pytorch_extractor_v1_FASNet.py b/bob/paper/mccnn/tifs2018/config/FASNet_config.py
similarity index 92%
rename from bob/paper/mccnn/tifs2018/extractor/wmca_config_pytorch_extractor_v1_FASNet.py
rename to bob/paper/mccnn/tifs2018/config/FASNet_config.py
index 210c967..b0f805b 100644
--- a/bob/paper/mccnn/tifs2018/extractor/wmca_config_pytorch_extractor_v1_FASNet.py
+++ b/bob/paper/mccnn/tifs2018/config/FASNet_config.py
@@ -96,17 +96,9 @@ from bob.learn.pytorch.extractor.image import FASNetExtractor
from bob.bio.video.extractor import Wrapper
-MODEL_FILE='/idiap/temp/ageorge/WMCA_FASNet/0_1_2_False_conv1-block1-ffc_3_grandtest-color-50/model_25_0.pth'
+MODEL_FILE= None # Replace with '<PATH_TO_MODEL>'
####################################################################
-ADAPTED_LAYERS= 'conv1-group1-block1-block2-group2-block3-group3-block4-group4-fc-ffc'
-####################################################################
-
-SELECTED_CHANNELS= [0,1,2,3]
-####################################################################
-
-
-NUM_CHANNELS_USED=len(SELECTED_CHANNELS)
_img_transform = transforms.Compose([transforms.ToPILImage(),transforms.Resize(224, interpolation=2),transforms.ToTensor(),transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])])
diff --git a/bob/paper/mccnn/tifs2018/extractor/wmca_config_pytorch_extractor_v1.py b/bob/paper/mccnn/tifs2018/config/MCCNN_config.py
similarity index 95%
rename from bob/paper/mccnn/tifs2018/extractor/wmca_config_pytorch_extractor_v1.py
rename to bob/paper/mccnn/tifs2018/config/MCCNN_config.py
index d8b41f7..71e02fc 100644
--- a/bob/paper/mccnn/tifs2018/extractor/wmca_config_pytorch_extractor_v1.py
+++ b/bob/paper/mccnn/tifs2018/config/MCCNN_config.py
@@ -1,5 +1,3 @@
-
-
# =============================================================================
# define instance of the preprocessor:
@@ -77,7 +75,6 @@ _preprocessor_ir = Wrapper(preprocessor = _image_preprocessor_ir,
_preprocessors[_channel_names[1]] = _preprocessor_ir
-
_preprocessors[_channel_names[2]] = _preprocessor_ir
_preprocessors[_channel_names[3]] = _preprocessor_ir
@@ -91,15 +88,14 @@ preprocessor = VideoFaceCropAlignBlockPatch(preprocessors = _preprocessors,
#====================================================================================
# MC-CNN algorithm
-
from bob.learn.pytorch.extractor.image import MCCNNExtractor
from bob.bio.video.extractor import Wrapper
-MODEL_FILE='/idiap/temp/ageorge/Pytorch_WMCA/MCCNNv1/0_1_2_3_False_conv1-group1-block1-block2-group2-block3-group3-block4-group4-fc-ffc_4/model_25_0.pth'
+MODEL_FILE= None # Replace with '<PATH_TO_MODEL>'
####################################################################
-ADAPTED_LAYERS= 'conv1-group1-block1-block2-group2-block3-group3-block4-group4-fc-ffc'
+ADAPTED_LAYERS= 'conv1-group1-block1-ffc'
####################################################################
SELECTED_CHANNELS= [0,1,2,3]
@@ -110,7 +106,6 @@ NUM_CHANNELS_USED=len(SELECTED_CHANNELS)
_img_transform = transforms.Compose([ChannelSelect(selected_channels = SELECTED_CHANNELS),transforms.ToTensor()])
-
_image_extracor=MCCNNExtractor(num_channels_used=NUM_CHANNELS_USED, transforms=_img_transform, model_file=MODEL_FILE)
extractor = Wrapper(_image_extracor)
diff --git a/bob/paper/mccnn/tifs2018/config/haralick_svm.py b/bob/paper/mccnn/tifs2018/config/haralick_svm.py
index 3b9a04d..d2e1793 100644
--- a/bob/paper/mccnn/tifs2018/config/haralick_svm.py
+++ b/bob/paper/mccnn/tifs2018/config/haralick_svm.py
@@ -13,24 +13,26 @@ from bob.bio.video.utils import FrameSelector
from bob.bio.base.preprocessor import Preprocessor
-import sys
-sys.path.append('/idiap/user/ageorge/WORK/MCCNN/bob.paper.mccnn.tifs2018/baseline_configs/extractor/')
-
-class DummyPreprocessor(Preprocessor):
-
- def __init__(self):
-
-
- Preprocessor.__init__(self)
-
- def __call__(self,image,annotations=None):
- return image
-
-
-_preprocessor=DummyPreprocessor()
-
-preprocessor=Wrapper(_preprocessor)
+FACE_SIZE = 128 # The size of the resulting face
+RGB_OUTPUT_FLAG = False # RGB output
+USE_FACE_ALIGNMENT = True # use annotations
+MAX_IMAGE_SIZE = None # no limiting here
+FACE_DETECTION_METHOD = None # use annotations 'mtcnn' if no annotations available
+MIN_FACE_SIZE = 50 # skip small faces
+ALIGNMENT_TYPE='lightcnn'
+_image_preprocessor = FaceCropAlign(face_size = FACE_SIZE,
+ rgb_output_flag = RGB_OUTPUT_FLAG,
+ use_face_alignment = USE_FACE_ALIGNMENT,
+ alignment_type=ALIGNMENT_TYPE,
+ max_image_size = MAX_IMAGE_SIZE,
+ face_detection_method = FACE_DETECTION_METHOD,
+ min_face_size = MIN_FACE_SIZE)
+
+_frame_selector = FrameSelector(selection_style = "all")
+
+preprocessor = Wrapper(preprocessor = _image_preprocessor,
+ frame_selector = _frame_selector)
#==================== DUmmy
diff --git a/bob/paper/mccnn/tifs2018/config/qm_lr.py b/bob/paper/mccnn/tifs2018/config/iqm_lr.py
similarity index 99%
rename from bob/paper/mccnn/tifs2018/config/qm_lr.py
rename to bob/paper/mccnn/tifs2018/config/iqm_lr.py
index 9c337f6..a3c5e9e 100644
--- a/bob/paper/mccnn/tifs2018/config/qm_lr.py
+++ b/bob/paper/mccnn/tifs2018/config/iqm_lr.py
@@ -7,7 +7,7 @@ The IQM features used in this algorithm/resource are introduced in the following
"""
#=======================================================================================
-sub_directory = 'qm_lr'
+sub_directory = 'iqm_lr'
"""
Sub-directory where results will be placed.
diff --git a/bob/paper/mccnn/tifs2018/extractor/HaralickRDWT.py b/bob/paper/mccnn/tifs2018/extractor/HaralickRDWT.py
index 08e2c9c..30d3ff2 100644
--- a/bob/paper/mccnn/tifs2018/extractor/HaralickRDWT.py
+++ b/bob/paper/mccnn/tifs2018/extractor/HaralickRDWT.py
@@ -8,8 +8,6 @@ import numpy as np
import pywt
import mahotas
-#TODO: Move to paper package, number of directions?, type casting,
-
class HaralickRDWT(Extractor):
"""Calculates RDWT+Haralick feature descriptors for 2D and multi-channel images.
diff --git a/bob/paper/mccnn/tifs2018/script/mean_fusion.py b/bob/paper/mccnn/tifs2018/script/mean_fusion.py
index 04b2df1..730e672 100644
--- a/bob/paper/mccnn/tifs2018/script/mean_fusion.py
+++ b/bob/paper/mccnn/tifs2018/script/mean_fusion.py
@@ -38,7 +38,7 @@ class Mean():
if self.weights is not None:
X=X*self.weights
- prob=np.mean(X,axis=1)#-11.35396267
+ prob=np.mean(X,axis=1)
res=np.vstack((1.0-prob,prob)).T
return res
@@ -101,7 +101,7 @@ def main(cmd_params=None):
if save_path == ".":
- save_path='/idiap/temp/ageorge/WMCA_channels_baseline/mean_fusion/'+protocol+'/fusionmine/'
+ save_path=protocol+'/fusion/'
for group in groups:
diff --git a/bob/paper/mccnn/tifs2018/trainer_configs/wmca_FASNet.py b/bob/paper/mccnn/tifs2018/trainer_configs/wmca_fasnet.py
similarity index 86%
rename from bob/paper/mccnn/tifs2018/trainer_configs/wmca_FASNet.py
rename to bob/paper/mccnn/tifs2018/trainer_configs/wmca_fasnet.py
index f25a774..e16c819 100644
--- a/bob/paper/mccnn/tifs2018/trainer_configs/wmca_FASNet.py
+++ b/bob/paper/mccnn/tifs2018/trainer_configs/wmca_fasnet.py
@@ -34,9 +34,9 @@ from bob.learn.pytorch.datasets import ChannelSelect, RandomHorizontalFlipImage
#==============================================================================
# Initialize the bob database instance
-data_folder_train='/idiap/temp/ageorge/WMCA_channels_baseline/color/preprocessed/'
+data_folder_train='<FASNET_PREPROCESSED_FOLDER>'
-output_base_path='/idiap/temp/ageorge/WMCA_FASNet/'
+output_base_path='<FASNET_CNN_OUTPUT_PATH>'
unseen_protocols=['','-LOO_fakehead','-LOO_flexiblemask','-LOO_glasses','-LOO_papermask','-LOO_prints','-LOO_replay','-LOO_rigidmask']
@@ -138,22 +138,3 @@ output_dir = output_base_path+UID
assert(len(SELECTED_CHANNELS)==NUM_CHANNELS)
network=FASNet(pretrained=True)
-#==============================================================================
-"""
-Note: Running in GPU
-
-jman submit --queue gpu \
---name FASNet \
---log-dir /idiap/temp/ageorge/WMCA_FASNet/logs/ \
---environment="PYTHONUNBUFFERED=1" -- \
-./bin/train_fasnet.py \
-/idiap/user/ageorge/WORK/MCCNN/bob.paper.mccnn.tifs2018/mccnn_configs/configs/trainer/wmca_FASNet.py --use-gpu -vvv
-
-Note: Running in cpu
-
-./bin/train_fasnet.py \
-/idiap/user/ageorge/WORK/MCCNN/bob.paper.mccnn.tifs2018/mccnn_configs/configs/trainer/wmca_FASNet.py -vvv
-
-
-"""
-
diff --git a/bob/paper/mccnn/tifs2018/trainer_configs/wmca_mccnn_v1.py b/bob/paper/mccnn/tifs2018/trainer_configs/wmca_mccnn.py
similarity index 84%
rename from bob/paper/mccnn/tifs2018/trainer_configs/wmca_mccnn_v1.py
rename to bob/paper/mccnn/tifs2018/trainer_configs/wmca_mccnn.py
index 193362c..62c473b 100644
--- a/bob/paper/mccnn/tifs2018/trainer_configs/wmca_mccnn_v1.py
+++ b/bob/paper/mccnn/tifs2018/trainer_configs/wmca_mccnn.py
@@ -34,9 +34,9 @@ from bob.learn.pytorch.datasets import ChannelSelect, RandomHorizontalFlipImage
#==============================================================================
# Initialize the bob database instance
-data_folder_train='/idiap/temp/ageorge/WMCA/preprocessed/'
+data_folder_train='<MCCNN_PREPROCESSED_PATH>'
-output_base_path='/idiap/temp/ageorge/Pytorch_WMCA/MCCNNv1_new_2/'
+output_base_path='<MCCNN_CNN_OUTPUT_PATH>'
unseen_protocols=['','-LOO_fakehead','-LOO_flexiblemask','-LOO_glasses','-LOO_papermask','-LOO_prints','-LOO_replay','-LOO_rigidmask']
@@ -114,21 +114,3 @@ output_dir = output_base_path+UID
assert(len(SELECTED_CHANNELS)==NUM_CHANNELS)
network=MCCNN(num_channels = NUM_CHANNELS)
-#==============================================================================
-"""
-Note: Running in GPU
-
-jman submit --queue gpu \
---name mccnnv2 \
---log-dir /idiap/temp/ageorge/Pytorch_WMCA/MCCNNv2/logs/ \
---environment="PYTHONUNBUFFERED=1" -- \
-./bin/train_mccnn.py \
-/idiap/user/ageorge/WORK/COMMON_ENV_PAD_BATL_DB/src/bob.learn.pytorch/bob/learn/pytorch/config/mccnn/wmca_mccnn.py --use-gpu -vvv
-
-Note: Running in cpu
-
-./bin/train_mccnn.py \
-/idiap/user/ageorge/WORK/COMMON_ENV_PAD_BATL_DB/src/bob.learn.pytorch/bob/learn/pytorch/config/mccnn/wmca_mccnn.py -vvv
-
-"""
-
diff --git a/buildout.cfg b/buildout.cfg
index fbe6a7e..9e6192b 100644
--- a/buildout.cfg
+++ b/buildout.cfg
@@ -1,14 +1,51 @@
-; vim: set fileencoding=utf-8 :
-; Fri Dec 23 13:58:08 CET 2016
-
[buildout]
parts = scripts
-develop = .
-eggs = bob.paper.mccnn.tifs2018
+versions = versions
+
+
extensions = bob.buildout
+ mr.developer
+
+
+auto-checkout = *
+debug = false
newest = false
-verbose = true
+verbose = false
+
+
+eggs = bob.extension
+ bob.measure
+ bob.bio.base
+ bob.ip.base
+ bob.ip.mtcnn
+ bob.learn.pytorch
+ bob.pad.face
+ bob.paper.mccnn.tifs2018
+
+
+develop = src/bob.extension
+ src/bob.measure
+ src/bob.bio.base
+ src/bob.ip.base
+ src/bob.ip.mtcnn
+ src/bob.learn.pytorch
+ src/bob.pad.face
+ src/bob.paper.mccnn.tifs2018
+
+[versions]
+
+
+[sources]
+bob.extension = git git@gitlab.idiap.ch:bob/bob.extension rev=8af04533484c30a90a62bc80116e233d67a72ac6
+bob.measure = git git@gitlab.idiap.ch:bob/bob.measure rev=022f97124a2d512462f64a065269b19de5f62ce6
+bob.bio.base = git git@gitlab.idiap.ch:bob/bob.bio.base rev=d92d0fb9672f95306da8259fef713d459acb5ee6
+bob.ip.base = git git@gitlab.idiap.ch:bob/bob.ip.base rev=a890160bb91ebe24fe92eac75725d99d5a73bb3e
+bob.ip.mtcnn = git git@gitlab.idiap.ch:bob/bob.ip.mtcnn rev=eea537b2fa99d0d52285a1353dc4988b58810f29
+bob.learn.pytorch = git git@gitlab.idiap.ch:bob/bob.learn.pytorch rev=03ca71beaf43219ff1a7a33842bb2a389de6d50b
+bob.pad.face = git git@gitlab.idiap.ch:bob/bob.pad.face rev=a260437b58694b64b61ca674cea4f698a6b674f0
+bob.paper.mccnn.tifs2018 = git git@gitlab.idiap.ch:bob/bob.paper.mccnn.tifs2018
+
[scripts]
recipe = bob.buildout:scripts
-dependent-scripts = true
\ No newline at end of file
+dependent-scripts = true
diff --git a/doc/running_baslines.md b/doc/running_baslines.md
index ea8cec5..a107022 100644
--- a/doc/running_baslines.md
+++ b/doc/running_baslines.md
@@ -2,19 +2,28 @@ Running baselines in grandtest protocol of WMCA
===============================================
In the baseline experiments, initially experiments are done separately for all four channels and score fusion is performed.
-Running experiments for each channel is described below.
+Running experiments for each channel is described below. The feature based baselines implemented are Image Quality Measure + Logistic Regression (IQM+LR),
+Local Binary Pattern + Logistic Regression (LBP+LR), and Haralick-RDWT-SVM (H-SVM).
+For the baselines using Haralick-SVM you need to have mahotas packsge. It is available from conda-forge channel and
+can be installed as
+
+.. code-block:: sh
+
+ conda install -c https://conda.anaconda.org/conda-forge mahotas
+
+The steps to reproduce the results for grandtest protocol are listed below.
Color channel
-----------------
+-------------
1.A.1. IQM - LR
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_color.py \
- <PATH_TO_EXTRACTOR_CONFIG>/qm_lr.py \
+ wmca-color \
+ iqm-lr \
--sub-directory <PATH_TO_BASELINE_RESULTS>/color/ -vvv --grid idiap
python bin/scoring.py -df \
@@ -27,8 +36,8 @@ Color channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_color.py \
- <PATH_TO_EXTRACTOR_CONFIG>/haralick_svm.py \
+ wmca-color \
+ haralick-svm \
--skip-preprocessing \
--preprocessed-directory <PATH_TO_BASELINE_RESULTS>/color/preprocessed \
--sub-directory <PATH_TO_BASELINE_RESULTS>/color/haralicksvm/ -vvv --grid idiap
@@ -47,8 +56,8 @@ B. Depth channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_depth.py \
- <PATH_TO_EXTRACTOR_CONFIG>/lbp_lr_depth.py \
+ wmca-depth \
+ lbp-lr-depth \
--sub-directory <PATH_TO_BASELINE_RESULTS>/depth/ -vvv --grid idiap
python bin/scoring.py -df \
@@ -60,8 +69,8 @@ B. Depth channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_depth.py \
- <PATH_TO_EXTRACTOR_CONFIG>/haralick_svm.py \
+ wmca-depth \
+ haralick-svm \
--skip-preprocessing \
--preprocessed-directory <PATH_TO_BASELINE_RESULTS>/depth/preprocessed \
--sub-directory <PATH_TO_BASELINE_RESULTS>/depth/haralicksvm/ -vvv --grid idiap
@@ -79,8 +88,8 @@ C. Infrared channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_infrared.py \
- <PATH_TO_EXTRACTOR_CONFIG>/lbp_lr_infrared.py \
+ wmca-infrared \
+ lbp-lr-infrared \
--sub-directory <PATH_TO_BASELINE_RESULTS>/infrared/ -vvv --grid idiap
1.C.2 Haralick SVM
@@ -88,8 +97,8 @@ C. Infrared channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_infrared.py \
- <PATH_TO_EXTRACTOR_CONFIG>/haralick_svm.py \
+ wmca-infrared \
+ haralick-svm \
--skip-preprocessing \
--preprocessed-directory <PATH_TO_BASELINE_RESULTS>/infrared/preprocessed \
--sub-directory <PATH_TO_BASELINE_RESULTS>/infrared/haralicksvm/ -vvv --grid idiap
@@ -107,8 +116,8 @@ D. Thermal channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_thermal.py \
- <PATH_TO_EXTRACTOR_CONFIG>/lbp_lr_thermal.py \
+ wmca-thermal \
+ lbp-lr-thermal \
--sub-directory <PATH_TO_BASELINE_RESULTS>/thermal/ -vvv --grid idiap
python bin/scoring.py -df \
@@ -120,8 +129,8 @@ D. Thermal channel
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_thermal.py \
- <PATH_TO_EXTRACTOR_CONFIG>/haralick_svm.py \
+ wmca-thermal \
+ haralick-svm \
--skip-preprocessing \
--preprocessed-directory <PATH_TO_BASELINE_RESULTS>/thermal/preprocessed \
--sub-directory <PATH_TO_BASELINE_RESULTS>/thermal/haralicksvm/ -vvv --grid idiap
@@ -170,8 +179,9 @@ A. color
unseen_protocols=['','-LOO_fakehead','-LOO_flexiblemask','-LOO_glasses','-LOO_papermask','-LOO_prints','-LOO_replay','-LOO_rigidmask']
-PROTOCOL = 'grandtest-color-50'+unseen_protocols[0]
+The protocols can be easily indexed as
+PROTOCOL = 'grandtest-color-50'+unseen_protocols[0]
1.
@@ -179,8 +189,8 @@ PROTOCOL = 'grandtest-color-50'+unseen_protocols[0]
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_color.py \
- <PATH_TO_EXTRACTOR_CONFIG>/qm_lr.py \
+ wmca-color \
+ iqm-lr \
--protocol grandtest-color-50-LOO_fakehead \
--skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files \
--extracted-directory <PATH_TO_BASELINE_RESULTS>/color/extracted/ \
@@ -197,8 +207,8 @@ B. depth
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_depth.py \
- <PATH_TO_EXTRACTOR_CONFIG>/lbp_lr_depth.py \
+ wmca-depth \
+ lbp-lr-depth \
--protocol grandtest-depth-50-LOO_fakehead \
--skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files \
--extracted-directory <PATH_TO_BASELINE_RESULTS>/depth/extracted/ \
@@ -215,8 +225,8 @@ C. Infrared
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_infrared.py \
- <PATH_TO_EXTRACTOR_CONFIG>/lbp_lr_infrared.py \
+ wmca-infrared \
+ lbp-lr-infrared \
--protocol grandtest-infrared-50-LOO_fakehead \
--skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files \
--extracted-directory <PATH_TO_BASELINE_RESULTS>/infrared/extracted/ \
@@ -232,8 +242,8 @@ D. Thermal
.. code-block:: sh
./bin/spoof.py \
- <PATH_TO_DATABASE_CONFIG>/batl_db_thermal.py \
- <PATH_TO_EXTRACTOR_CONFIG>/lbp_lr_thermal.py \
+ wmca-thermal \
+ lbp-lr-thermal \
--protocol grandtest-thermal-50-LOO_fakehead \
--skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files \
--extracted-directory <PATH_TO_BASELINE_RESULTS>/thermal/extracted/ \
@@ -255,7 +265,6 @@ The protocola are, '-LOO_fakehead','-LOO_flexiblemask','-LOO_glasses','-LOO_pape
<PATH_TO_BASELINE_RESULTS>/LOO/color/grandtest-color-50-LOO_fakehead/grandtest-color-50-LOO_fakehead/scores/scores-dev
-
.. code-block:: sh
python bin/scoring.py -df \
@@ -273,19 +282,15 @@ color
-----
.. code-block:: sh
- ./bin/spoof.py <PATH_TO_DATABASE_CONFIG>/batl_db_color.py <PATH_TO_EXTRACTOR_CONFIG>/haralick_svm.py --protocol grandtest-color-50-LOO_fakehead --skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files --extracted-directory <PATH_TO_BASELINE_RESULTS>/color/haralicksvm/extracted/ --grid idiap --sub-directory <PATH_TO_BASELINE_RESULTS>/LOO/color/haralicksvm/grandtest-color-50-LOO_fakehead/
-
+ ./bin/spoof.py wmca-color haralick-svm --protocol grandtest-color-50-LOO_fakehead --skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files --extracted-directory <PATH_TO_BASELINE_RESULTS>/color/haralicksvm/extracted/ --grid idiap --sub-directory <PATH_TO_BASELINE_RESULTS>/LOO/color/haralicksvm/grandtest-color-50-LOO_fakehead/
-All of them together
---------------------
-
-.. code-block:: sh
+Repeat the same procedure for all four channels.
- ./bin/spoof.py <PATH_TO_DATABASE_CONFIG>/batl_db_color.py <PATH_TO_EXTRACTOR_CONFIG>/haralick_svm.py --protocol grandtest-color-50-LOO_fakehead --skip-preprocessing --skip-extraction --skip-extractor-training --allow-missing-files --extracted-directory <PATH_TO_BASELINE_RESULTS>/color/haralicksvm/extracted/ --grid idiap --sub-directory <PATH_TO_BASELINE_RESULTS>/LOO/color/haralicksvm/grandtest-color-50-LOO_fakehead/
+Scorefusion Haralick-SVM
+------------------------
+Once scores from all channels are available. Run the following command.
-scorefusion Haralick
----------------------
.. code-block:: sh
./bin/python bin/mean_fusion.py -c <PATH_TO_BASELINE_RESULTS>/LOO/color/haralicksvm/grandtest-color-50-LOO_fakehead/grandtest-color-50-LOO_fakehead/scores/scores-dev -s <PATH_TO_BASELINE_RESULTS>/mean_fusion/haralick/grandtest-color-50-LOO_fakehead/
@@ -297,4 +302,4 @@ scoring for Haralick Mean fusion
python bin/scoring.py -df <PATH_TO_BASELINE_RESULTS>/mean_fusion/haralick/grandtest-color-50-LOO_fakehead/scores_mean_fused_dev -ef <PATH_TO_BASELINE_RESULTS>/mean_fusion/haralick/grandtest-color-50-LOO_fakehead/scores_mean_fused_eval
-Similarly, repeat the experiment for all protocols.
\ No newline at end of file
+Similarly, repeat the experiment for all LOO sub-protocols.
\ No newline at end of file
diff --git a/setup.py b/setup.py
index ed83cdc..0aab1cf 100644
--- a/setup.py
+++ b/setup.py
@@ -100,6 +100,19 @@ setup(
'mc-face-preprocessor = bob.paper.mccnn.tifs2018.config.preprocessor.mc_preprocessor:mc_preprocessor', # returns Multi channel aligned face images
],
+ 'bob.bio.config': ['wmca-color = bob.paper.mccnn.tifs2018.database.batl_db_color',
+ 'wmca-depth = bob.paper.mccnn.tifs2018.database.batl_db_depth',
+ 'wmca-infrared = bob.paper.mccnn.tifs2018.database.batl_db_infrared',
+ 'wmca-all= bob.paper.mccnn.tifs2018.database.batl_db_rgb_ir_d_t_grandtest',
+ 'wmca-thermal = bob.paper.mccnn.tifs2018.database.batl_db_thermal',
+ #configs
+ 'lbp-lr-infrared = bob.paper.mccnn.tifs2018.config.lbp_lr_infrared',
+ 'lbp-lr-thermal= bob.paper.mccnn.tifs2018.config.lbp_lr_thermal',
+ 'lbp-lr-depth= bob.paper.mccnn.tifs2018.config.lbp_lr_depth',
+ 'fastnet = bob.paper.mccnn.tifs2018.config.FASNet_config',
+ 'mccnn = bob.paper.mccnn.tifs2018.config.MCCNN_config',
+ 'iqm-lr = bob.paper.mccnn.tifs2018.config.iqm_lr',
+ 'haralick-svm = bob.paper.mccnn.tifs2018.config.haralick_svm',]
},
--
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