diff --git a/exp/dochi.py b/exp/dochi.py
--- a/exp/dochi.py
+++ b/exp/dochi.py
@@ -3,12 +3,12 @@ import time
 import argparse
 import logging as log
 
+import cv2 as cv
 import numpy as np
 import keras
 from keras.models import load_model
-from PIL import Image,ImageDraw
+from PIL import Image
 
-from epoint import EPoint
 import exp_config as cfg
 from kerokero.k_util import averageDistance
 
@@ -16,6 +16,7 @@ keras.losses.averageDistance=averageDist
 keras.metrics.averageDistance=averageDistance
 
 model=load_model(cfg.dochiModel)
+SIDE=224
 
 
 def locateGrid(img):
@@ -28,7 +29,7 @@ def locateGrid(img):
 	label=model.predict(np.reshape(npImg,(1,224,224,1)))
 	points=[]
 	for i in range(4):
-		points.append(EPoint((label[0][i][0]+1)*(width/2),(label[0][i][1]+1)*(height/2)))
+		points.append([(label[0][i][0]+1)*(width/2),(label[0][i][1]+1)*(height/2)])
 	t=time.time()-t1
 	log.info("grid located in {0:.3}s".format(t))
 	return points
@@ -43,7 +44,10 @@ if __name__=="__main__":
 	for image_path in args.input:
 		image=Image.open(image_path)
 		points=locateGrid(image)
-		drawer=ImageDraw.Draw(image)
-		for p in points:
-			drawer.ellipse((p.x-2,p.y-2,p.x+2,p.y+2),fill="#00ff00")
-		image.save(os.path.join(args.output_dir,os.path.basename(image_path)))
+		x1=SIDE*0.1
+		x2=SIDE*0.9
+		destPoints=[(x1,x1),(x1,x2),(x2,x2),(x2,x1)]
+		m=cv.getPerspectiveTransform(np.float32(points),np.float32(destPoints))
+		img=cv.warpPerspective(np.uint8(image),m,(SIDE,SIDE))
+		img=cv.cvtColor(img,cv.COLOR_BGR2RGB)
+		cv.imwrite(os.path.join(args.output_dir,os.path.basename(image_path)),img)