Add/Remove images

README.md

@@ -37,20 +37,22 @@ To create puzzle from image use `create_puzzle` script.
 i.e.
 
 ```bash
-$ create_puzzle images/butterfly.jpg --size=28 --destination=puzzle.jpg
-```
+$ create_puzzle images/pillars.jpg --size=48 --destination=puzzle.jpg
 
-will create puzzle from `lena.jpg` where each puzzle piece is 28x28 pixels.
-Run `create_puzzle --help` for detailed help.
+[SUCCESS] Puzzle created with 420 pieces
+
+```
 
-Puzzle is created from input image by shuffling pieces.
+will create puzzle with `420` pieces from `images/pillars.jpg` where each piece is 48x48 pixels.
 
 <div align="center">
-  <img src="images/butterfly.jpg" alt="original" width="250" height="180" />
+  <img src="images/pillars.jpg" alt="original" width="250" height="180" />
   &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
-  <img src="images/demo_puzzle.jpg" alt="original" width="250" height="180" />
+  <img src="images/demo_puzzle.jpg" alt="puzzle" width="250" height="180" />
 </div>
 
+Run `create_puzzle --help` for detailed help.
+
 __NOTE__ *Created puzzle dimensions may be smaller then original image depending on
 given puzzle piece size. Maximum possible rectangle is cropped from original image.*
 
@@ -61,10 +63,10 @@ In order to solve puzzles, use `gaps` script.
 i.e.
 
 ```bash
-$ gaps --image=puzzle.jpg --size=28 --generations=20 --population=300
+$ gaps --image=puzzle.jpg --size=48 --generations=20 --population=600
 ```
 
-This will start genetic algorithm with initial population of 300 and 20 generations.
+This will start genetic algorithm with initial population of 600 and 20 generations.
 
 Following options are provided:
 

gaps/genetic_algorithm.py

@@ -9,13 +9,12 @@
 
 
 class GeneticAlgorithm(object):
-    ELITISM_FACTOR = 0.02
 
-    def __init__(self, image, piece_size, population_size, generations):
+    def __init__(self, image, piece_size, population_size, generations, elite_size=2):
         self._image = image
         self._piece_size = piece_size
         self._generations = generations
-        self._elite_size = int(population_size * self.ELITISM_FACTOR)
+        self._elite_size = elite_size
         pieces, rows, columns = image_helpers.flatten_image(image, piece_size, indexed=True)
         self._population = [Individual(pieces, rows, columns) for _ in range(population_size)]
         self._pieces = pieces