nearestImage is better

mosiac.py

@@ -13,8 +13,10 @@ from PIL import Image
 
 class Mosiac():
 	def __init__(self):
-		self.imageBank = {}
 		self.numClusters = 8
+		self.tolerance = 0.5
+
+		self.imageBank = {}
 		self.clusters = []
 		self.clusterMeans = []
 
@@ -96,16 +98,6 @@ class Mosiac():
 		for cluster in self.clusters:
 			mean = tuple(np.mean(list(cluster.keys()), axis=(0)))
 			self.clusterMeans.append(mean)
-		"""
-		indexs = list(range(len(self.images)))
-		step = len(self.images) // self.numClusters
-		self.clusters = [indexs[i*step : (i+1)*step] for i in
-			range(self.numClusters)]
-		for cluster in self.clusters:
-			means = [self.means[i] for i in cluster]
-			mean = tuple(np.mean(means, axis=(0)))
-			self.clusterMeans.append(mean)
-		"""
 		print(f"initClusters took: {time.time()-then} seconds.")
 
 
@@ -123,17 +115,12 @@ class Mosiac():
 
 		nodes = np.array(list(cluster.keys()))
 		dist = np.sum((nodes - np.array(pixel))**2, axis=1)
-		# return np.argmin(dist)  # closet value
+		tol = int(len(dist) * self.tolerance)
-		dist.argsort()[:10]
+		tol += int(tol == 0)
-		return random.choice(list(dist))
+		indexs = dist.argsort()[:tol]
-		"""
+		# choice = dist.argmin()  # closet value
-		dists = []
+		choice = random.choice(indexs)
-		for mean in cluster.keys():
+		return cluster[tuple(nodes[choice])]
-			dist = np.linalg.norm(np.array(pixel)-np.array(mean))
-			dists.append(dist)
-		"""
-		# choice = random.choice(sorted(dists)[:10])
-		# return cluster[dists.index(choice)]
 
 
 	def buildMatrix(self):
@@ -141,12 +128,6 @@ class Mosiac():
 		Build the image matrix.
 		"""
 		then = time.time()
-		# for row in range(self.smallImage.size[1]):
-		# 	new_row = []
-		# 	for col in range(self.smallImage.size[0]):
-		# 		image = self.nearestImage(self.smallImage.getpixel((col, row)))
-		# 		new_row.append(image)
-		# 	self.imageMatrix.append(new_row)
 		pixels = list(self.smallImage.getdata())
 		for pixel in pixels:
 			image = self.nearestImage(pixel)