diff --git a/exp/hakugen.py b/exp/hakugen.py
new file mode 100644
--- /dev/null
+++ b/exp/hakugen.py
@@ -0,0 +1,49 @@
+import os
+import time
+import argparse
+import logging as log
+
+import numpy as np
+import keras
+from keras.models import load_model
+from PIL import Image,ImageDraw
+
+from epoint import EPoint
+import exp_config as cfg
+from kerokero.k_util import averageDistance
+
+keras.losses.averageDistance=averageDistance
+keras.metrics.averageDistance=averageDistance
+
+model=load_model(cfg.hakugenModel)
+
+
+def locateGrid(img):
+	t1=time.time()
+	(width,height)=img.size
+	normedImg=img.convert("L")
+	npImg=np.array(normedImg.getdata()).reshape((224,224,1)).astype(np.float32)
+	npImg=npImg/128-1
+
+	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)))
+	t=time.time()-t1
+	log.info("grid located in {0:.3}s".format(t))
+	return points
+
+
+if __name__=="__main__":
+	parser=argparse.ArgumentParser()
+	parser.add_argument("-i","--input",nargs="+")
+	parser.add_argument("-o","--output_dir",required=True)
+	args=parser.parse_args()
+
+	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)))