added dark bg option

Social-Evolution-and-Behavior · Jan 17, 2021 · 93408c5 · 93408c5
1 parent ed12ea6
commit 93408c5
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Showing 11 changed files with 35 additions and 10 deletions.
diff --git a/antrax/classifier.py b/antrax/classifier.py
@@ -336,6 +336,8 @@ def predict_images_file(self, imagefile, outfile=None, usepassed=False, report=F
 
             names += [tracklet]
 
+        f.close()
+
         if outfile is None:
             outfile = os.path.join(self.outdir, 'autoids_' + str(m) + '.csv')
 

diff --git a/antrax/cli.py b/antrax/cli.py
@@ -377,7 +377,7 @@ def solve(explist, *, glist: parse_movlist=None, movlist: parse_movlist=None, cl
 
 def train(classdir,  *, name='classifier', scratch=False, ne=5, unknown_weight=20, multi_weight=0.1, arch='small', modelfile=None,
           target_size: to_int=None, crop_size: to_int=None, hsymmetry=False, aug_options='', hpc=False, hpc_options: parse_hpc_options={},
-          dry=False):
+          background='white', dry=False):
     """Train a blob classifier"""
     hpc = hpc or ANTRAX_HPC
 
@@ -402,7 +402,7 @@ def train(classdir,  *, name='classifier', scratch=False, ne=5, unknown_weight=2
             f = glob(examplesdir + '/*/*.png')[0]
             target_size = max(imread(f).shape)
 
-        c = axClassifier(name, nclasses=n, target_size=target_size, crop_size=crop_size, hsymmetry=hsymmetry,
+        c = axClassifier(name, nclasses=n, target_size=target_size, crop_size=crop_size, hsymmetry=hsymmetry, background=background,
                          unknown_weight=unknown_weight, multi_weight=multi_weight, modeltype=arch, json=modelfile)
 
         c.save(classfile)

diff --git a/bin/antrax_maci64_mcr_interface.app/Contents/MacOS/antrax_maci64_mcr_interface b/bin/antrax_maci64_mcr_interface.app/Contents/MacOS/antrax_maci64_mcr_interface
diff --git a/matlab/@tracklet/add_examples.m b/matlab/@tracklet/add_examples.m
@@ -41,7 +41,12 @@ function add_examples(trj,varargin)
 
 ims = trj.get_image(tt);
 msk = repmat(max(ims,[],3)==0,[1,1,3,1]);
-ims(msk)=255;
+
+if trj.Trck.get_param('segmentation_invert')
+    ims(msk)=0;
+else
+    ims(msk)=255;
+end
 
 for i=1:size(ims,4)
 

diff --git a/matlab/@trhandles/default_params.m b/matlab/@trhandles/default_params.m
@@ -51,6 +51,7 @@
 prmtrs.segmentation_illum_correct = false;
 prmtrs.segmentation_illum_correct_level = 0.9;
 
+prmtrs.segmentation_invert = false;
 prmtrs.segmentation_threshold = 0.14;
 
 prmtrs.segmentation_IntensityFilter = false;

diff --git a/matlab/apps/antrax.mlapp b/matlab/apps/antrax.mlapp
diff --git a/matlab/apps/validate_classifications.mlapp b/matlab/apps/validate_classifications.mlapp
diff --git a/matlab/misc/applyMasktoIm.m b/matlab/misc/applyMasktoIm.m
@@ -1,4 +1,4 @@
-function MaskedIm = applyMasktoIm(Im,Mask)
+function MaskedIm = applyMasktoIm(Im,Mask,fillval)
 % jonathan saragosti 
 % 02/18/15
 % apply a binary mask to an image,

diff --git a/matlab/misc/create_backgrounds.m b/matlab/misc/create_backgrounds.m
@@ -85,6 +85,8 @@ function create_backgrounds(Trck, pb)
 switch method
     case 'max'
         bg = max(frames,[],4);
+    case 'min'
+        bg = min(frames,[],4);
     case 'median'
         bg = median(frames,4);
     otherwise

diff --git a/matlab/tracking/detect_blobs.m b/matlab/tracking/detect_blobs.m
@@ -52,8 +52,14 @@ function detect_blobs(Trck,varargin)
 
 %% Image segmentation
 
-Z = imsubtract(BGS,frame_single);
+if Trck.get_param('segmentation_invert')
+    Z = imsubtract(frame_single,BGS);
+else
+    Z = imsubtract(BGS,frame_single);
+end
+
 Z = Z.*single(mask);
+
 %Z = applyMasktoIm(Z,mask);
 
 if Trck.get_param('segmentation_local_z_scaling')   
@@ -69,7 +75,11 @@ function detect_blobs(Trck,varargin)
 % threshold the image
 if Trck.get_param('segmentation_use_max_rgb')
     ZGRY = max(Z,[],3);
-    FGRY = min(frame,[],3);
+    if Trck.get_param('segmentation_invert')
+        FGRY = max(frame,[],3);
+    else
+        FGRY = min(frame,[],3);
+    end
 else
     ZGRY = rgb2gray(Z);
     FGRY = rgb2gray(frame);
@@ -223,7 +233,7 @@ function detect_blobs(Trck,varargin)
 sqsz = Trck.get_param('sqsz');
 
 padded_label = padarray(ab.LABEL,[sqsz/2,sqsz/2]);
-if Trck.get_param('segmentation_color_correction_for_classification')
+if Trck.get_param('segmentation_color_correction_for_classification') && ~Trck.get_param('segmentation_invert')
     padded_frame = padarray(frame_corrected,[sqsz/2,sqsz/2]);
 else
     padded_frame = padarray(frame_orig,[sqsz/2,sqsz/2]);

diff --git a/scripts/classifier_test_jobfile.sh b/scripts/classifier_test_jobfile.sh
@@ -1,11 +1,16 @@
 #!/bin/bash
 #SBATCH --job-name=ctest
-#SBATCH --output=/ru-auth/local/home/agal/ctest1_%a.log
+#SBATCH --output=/ru-auth/local/home/agal/logs/class_test_NAME__%a.log
 #SBATCH --ntasks=1
 #SBATCH --cpus-per-task=8
 #SBATCH --mail-type=ALL
 #SBATCH --mail-user=agal@rockefeller.edu
-#SBATCH --array=0-50%100
+#SBATCH --array=1-NREP_%100
 
+NAME="NAME_"
+N="N_"
+LOG="LOG_"
+CLASSDIR="CLASSDIR_"
+NE="NE_"
 
-srun python /ru-auth/local/home/agal/code/anTraX/scripts/classifier_test.py  /ru-auth/local/home/agal/scratch/Classifiers/A36_classifier_analysis -n 2000 --name n2000 --ne 100 --logfile /ru-auth/local/home/agal/classifier_test.log
+srun python /ru-auth/local/home/agal/code/anTraX/scripts/classifier_test.py  $CLASSDIR -n $N --name $NAME --ne $NE --logfile $LOGFILE