diff --git a/exp/keras/prepare_data.py b/exp/kerokero/prepare_data.py
copy from exp/keras/prepare_data.py
copy to exp/kerokero/prepare_data.py
--- a/exp/keras/prepare_data.py
+++ b/exp/kerokero/prepare_data.py
@@ -2,20 +2,22 @@ import os
 import sys
 import re
 import random
+import itertools
 
 import numpy as np
 import cv2 as cv
 
-sys.path.append("../exp")
+sys.path.append("..")
+sys.path.append("../../src")
 from annotations import DataFile,computeBoundingBox,Corners
 from geometry import Line
-from keras.transformation_matrices import getIdentity,getRotation,getTranslation,getScale,getMirroring,getProjection
+from kerokero.transformation_matrices import getIdentity,getRotation,getTranslation,getScale,getMirroring,getProjection
 
 random.seed(361)
 
 
 class Sample:
-	SIDE=256
+	SIDE=224
 
 	def __init__(self,img,grid):
 		self.img=img
@@ -33,7 +35,7 @@ class Sample:
 		m=np.matmul(self._computeCrop(m),m)
 		img=cv.warpPerspective(self.img,m,(self.SIDE,self.SIDE))
 		grid=Corners(c.transform(m) for c in self.grid)
-		Sample(img,grid).show()
+		return (img,list(itertools.chain.from_iterable(grid)))
 
 	def _getCenter(self):
 		(a,b,c,d)=self.grid
@@ -76,9 +78,32 @@ def harvestDir(path):
 	boards=annotations["."]
 	for f in files:
 		img=cv.imread(f.path)
+		img=cv.cvtColor(img,cv.COLOR_BGR2GRAY)
 		for b in boards:
 			sample=Sample(img,b.grid)
-			sample.transform()
+			(img,label)=sample.transform()
+			yield (img,label)
+
+
+def loadDataset(root):
+	testRatio=0.1
+	trainRatio=1-testRatio
+	images=[]
+	labels=[]
+	for d in traverseDirs(root):
+		for (img,label) in harvestDir(d):
+			images.append(img)
+			labels.append(label)
+	n=len(images)
+	keys=list(range(n))
+	random.shuffle(keys)
+	images=[images[k] for k in keys]
+	labels=[labels[k] for k in keys]
+	m=int(n*trainRatio)
+	return (
+		(np.uint8(images[:m]),np.float32(labels[:m])),
+		(np.uint8(images[m:]),np.float32(labels[m:]))
+	)
 
 
 def show(img,filename="x"):