new tutorial

CHANGELOG.md

@@ -1,6 +1,8 @@
 # Changelog
 
 * 0.2.22 (dev):
+  * Enhancement: New [Tutorial](notebooks/Tutorial.ipynb).
+  * Bugfix: `SaliencyMapModel.AUC` failed if some images didn't have any fixations.
   * Feature: `StimulusDependentSaliencyMapModel`
   * Bugfix: The NUSEF dataset scaled some fixations not correctly to image coordinates. Also, we now account for some typos in the
     dataset source data.

README.md

@@ -11,37 +11,6 @@ Pysaliency can evaluate most commonly used saliency metrics, including AUC, sAUC
 image-based KL divergence, fixation based KL divergence and SIM for saliency map models and
 log likelihoods and information gain for probabilistic models.
 
-Pysaliency provides several important datasets:
-
-* MIT1003
-* MIT300
-* CAT2000
-* Toronto
-* Koehler
-* iSUN
-* SALICON (both the 2015 and the 2017 edition and each with both the original mouse traces and the inferred fixations)
-* FIGRIM
-* OSIE
-* NUSEF (the part with public images)
-
-and some influential models:
-* AIM
-* SUN
-* ContextAwareSaliency
-* BMS
-* GBVS
-* GBVSIttiKoch
-* Judd
-* IttiKoch
-* RARE2012
-* CovSal
-
-
-These models are using the original code which is often matlab.
-Therefore, a matlab licence is required to make use of these models, although quite some of them
-work with octave, too (see below).
-
-
 Installation
 ------------
 
@@ -54,7 +23,7 @@ Quickstart
 ----------
 
     import pysaliency
-    
+
     dataset_location = 'datasets'
     model_location = 'models'
 
@@ -72,6 +41,40 @@ If you already have saliency maps for some dataset, you can import them into pys
     my_model = pysaliency.SaliencyMapModelFromDirectory(mit_stimuli, '/path/to/my/saliency_maps')
     auc = my_model.AUC(mit_stimuli, mit_fixations)
 
+Check out the [Tutorial](notebooks/Tutorial.ipynb) for a more detailed introduction!
+
+Included datasets and models
+----------------------------
+
+Pysaliency provides several important datasets:
+
+* MIT1003
+* MIT300
+* CAT2000
+* Toronto
+* Koehler
+* iSUN
+* SALICON (both the 2015 and the 2017 edition and each with both the original mouse traces and the inferred fixations)
+* FIGRIM
+* OSIE
+* NUSEF (the part with public images)
+
+and some influential models:
+* AIM
+* SUN
+* ContextAwareSaliency
+* BMS
+* GBVS
+* GBVSIttiKoch
+* Judd
+* IttiKoch
+* RARE2012
+* CovSal
+
+These models are using the original code which is often matlab.
+Therefore, a matlab licence is required to make use of these models, although quite some of them
+work with octave, too (see below).
+
 
 Using Octave
 ------------