[Bugfix] CAT2000 contained unnecessary files

pysaliency/external_datasets/cat2000.py

@@ -178,7 +178,9 @@ def _get_cat2000_train(name, location):
             # Stimuli
             print('Creating stimuli')
             f = zipfile.ZipFile(os.path.join(temp_dir, 'trainSet.zip'))
-            f.extractall(temp_dir)
+            namelist = f.namelist()
+            namelist = filter_files(namelist, ['Output'])
+            f.extractall(temp_dir, namelist)
 
             stimuli_src_location = os.path.join(temp_dir, 'trainSet', 'Stimuli')
             stimuli_target_location = os.path.join(location, 'Stimuli') if location else None
@@ -304,7 +306,9 @@ def _get_cat2000_train_v1_1(name, location):
             # Stimuli
             print('Creating stimuli')
             f = zipfile.ZipFile(os.path.join(temp_dir, 'trainSet.zip'))
-            f.extractall(temp_dir)
+            namelist = f.namelist()
+            namelist = filter_files(namelist, ['Output'])
+            f.extractall(temp_dir, namelist)
 
             stimuli_src_location = os.path.join(temp_dir, 'trainSet', 'Stimuli')
             stimuli_target_location = os.path.join(location, 'Stimuli') if location else None

tests/test_external_datasets.py

@@ -1,5 +1,6 @@
 import numpy as np
 import pytest
+from pathlib import Path
 from pytest import approx
 from scipy.stats import kurtosis, skew
 
@@ -71,7 +72,7 @@ def test_toronto(location):
 @pytest.mark.download
 @pytest.mark.matlab
 @pytest.mark.skip_octave
-def test_cat2000_train(location, matlab):
+def test_cat2000_train_v1_0(location, matlab):
     real_location = _location(location)
 
     stimuli, fixations = pysaliency.external_datasets.get_cat2000_train(location=real_location)
@@ -83,6 +84,8 @@ def test_cat2000_train(location, matlab):
         assert isinstance(stimuli, pysaliency.FileStimuli)
         assert location.join('CAT2000_train/stimuli.hdf5').check()
         assert location.join('CAT2000_train/fixations.hdf5').check()
+        assert not list ((Path(location) / 'CAT2000_train' / 'Stimuli').glob('**/Output'))
+        assert not list ((Path(location) / 'CAT2000_train' / 'Stimuli').glob('**/*_SaliencyMap.jpg'))
 
     assert len(stimuli.stimuli) == 2000
     assert set(stimuli.sizes) == {(1080, 1920)}
@@ -118,6 +121,59 @@ def test_cat2000_train(location, matlab):
     assert len(fixations) == len(pysaliency.datasets.remove_out_of_stimulus_fixations(stimuli, fixations))
 
 
+@pytest.mark.slow
+@pytest.mark.download
+@pytest.mark.matlab
+@pytest.mark.skip_octave
+def test_cat2000_train_v1_1(location, matlab):
+    real_location = _location(location)
+
+    stimuli, fixations = pysaliency.external_datasets.get_cat2000_train(location=real_location, version='1.1')
+
+    if location is None:
+        assert isinstance(stimuli, pysaliency.Stimuli)
+        assert not isinstance(stimuli, pysaliency.FileStimuli)
+    else:
+        assert isinstance(stimuli, pysaliency.FileStimuli)
+        assert location.join('CAT2000_train_v1.1/stimuli.hdf5').check()
+        assert location.join('CAT2000_train_v1.1/fixations.hdf5').check()
+        assert not list ((Path(location) / 'CAT2000_train_v1.1' / 'Stimuli').glob('**/Output'))
+        assert not list ((Path(location) / 'CAT2000_train_v1.1' / 'Stimuli').glob('**/*_SaliencyMap.jpg'))
+
+    assert len(stimuli.stimuli) == 2000
+    assert set(stimuli.sizes) == {(1080, 1920)}
+    assert set(stimuli.attributes.keys()) == {'category'}
+    assert np.all(np.array(stimuli.attributes['category'][0:100]) == 0)
+    assert np.all(np.array(stimuli.attributes['category'][100:200]) == 1)
+
+    assert len(fixations.x) == 667804
+
+    assert np.mean(fixations.x) == approx(977.048229720098)
+    assert np.mean(fixations.y) == approx(535.7335899455527)
+    assert np.mean(fixations.t) == approx(10.888694886523592)
+    assert np.mean(fixations.lengths) == approx(9.888694886523592)
+
+    assert np.std(fixations.x) == approx(265.7561897117776)
+    assert np.std(fixations.y) == approx(200.47021508760227)
+    assert np.std(fixations.t) == approx(6.8276447542371805)
+    assert np.std(fixations.lengths) == approx(6.8276447542371805)
+
+    assert kurtosis(fixations.x) == approx(0.8314129075001575)
+    assert kurtosis(fixations.y) == approx(0.16001475266665466)
+    assert kurtosis(fixations.t) == approx(0.07131517526032427)
+    assert kurtosis(fixations.lengths) == approx(0.07131517526032427)
+
+    assert skew(fixations.x) == approx(0.07615972876511597)
+    assert skew(fixations.y) == approx(0.2770231691322164)
+    assert skew(fixations.t) == approx(0.5813051491385639)
+    assert skew(fixations.lengths) == approx(0.5813051491385639)
+
+    assert entropy(fixations.n) == approx(10.955097604631638)
+    assert (fixations.n == 0).sum() == 304
+
+    assert len(fixations) == len(pysaliency.datasets.remove_out_of_stimulus_fixations(stimuli, fixations))
+
+
 @pytest.mark.slow
 @pytest.mark.download
 @pytest.mark.skip_octave
@@ -132,6 +188,9 @@ def test_cat2000_test(location):
     else:
         assert isinstance(stimuli, pysaliency.FileStimuli)
         assert location.join('CAT2000_test/stimuli.hdf5').check()
+        assert not list ((Path(location) / 'CAT2000_test' / 'Stimuli').glob('**/Output'))
+        assert not list ((Path(location) / 'CAT2000_test' / 'Stimuli').glob('**/*_SaliencyMap.jpg'))
+
 
     assert len(stimuli.stimuli) == 2000
     assert set(stimuli.sizes) == {(1080, 1920)}