diff --git a/SSH/test.py b/SSH/test.py
index 4c3c755..26581db 100644
--- a/SSH/test.py
+++ b/SSH/test.py
@@ -7,9 +7,10 @@ from ssh_detector import SSHDetector
 
 long_max = 1200
 t = 2
+detector = SSHDetector('./model/e2ef', 0)
 
 
-f = 't2.jpg'
+f = '../sample-images/t2.jpg'
 if len(sys.argv)>1:
   f = sys.argv[1]
 img = cv2.imread(f)
@@ -18,7 +19,6 @@ if img.shape[0]>long_max or img.shape[1]>long_max:
   scale = float(long_max) / max(img.shape[0], img.shape[1])
   img = cv2.resize(img, (0,0), fx=scale, fy=scale)
   print('resize to', img.shape)
-detector = SSHDetector('./model/e2ef', 0)
 for i in xrange(t-1): #warmup
   faces = detector.detect(img)
 timea = datetime.datetime.now()
diff --git a/alignment/alignment.py b/alignment/alignment.py
new file mode 100644
index 0000000..a2c264c
--- /dev/null
+++ b/alignment/alignment.py
@@ -0,0 +1,42 @@
+import argparse
+import cv2
+import numpy as np
+import sys
+import mxnet as mx
+import datetime
+
+class Alignment:
+  def __init__(self, prefix, epoch, ctx_id=0):
+    print('loading',prefix, epoch)
+    ctx = mx.gpu(ctx_id)
+    sym, arg_params, aux_params = mx.model.load_checkpoint(prefix, epoch)
+    all_layers = sym.get_internals()
+    sym = all_layers['heatmap_output']
+    image_size = (128, 128)
+    self.image_size = image_size
+    model = mx.mod.Module(symbol=sym, context=ctx, label_names = None)
+    #model = mx.mod.Module(symbol=sym, context=ctx)
+    model.bind(for_training=False, data_shapes=[('data', (1, 3, image_size[0], image_size[1]))])
+    model.set_params(arg_params, aux_params)
+    self.model = model
+  
+  def get(self, img):
+    rimg = cv2.resize(img, (self.image_size[1], self.image_size[0]))
+    img = cv2.cvtColor(rimg, cv2.COLOR_BGR2RGB)
+    img = np.transpose(img, (2,0,1)) #3*112*112, RGB
+    input_blob = np.zeros( (1, 3, self.image_size[1], self.image_size[0]),dtype=np.uint8 )
+    input_blob[0] = img
+    data = mx.nd.array(input_blob)
+    db = mx.io.DataBatch(data=(data,))
+    self.model.forward(db, is_train=False)
+    alabel = self.model.get_outputs()[-1].asnumpy()[0]
+    ret = np.zeros( (alabel.shape[0], 2), dtype=np.float32)
+    for i in xrange(alabel.shape[0]):
+      a = cv2.resize(alabel[i], (self.image_size[1], self.image_size[0]))
+      ind = np.unravel_index(np.argmax(a, axis=None), a.shape)
+      #ret[i] = (ind[0], ind[1]) #h, w
+      ret[i] = (ind[1], ind[0]) #w, h
+    return ret
+
+
+
diff --git a/alignment/test.py b/alignment/test.py
new file mode 100644
index 0000000..273ed4c
--- /dev/null
+++ b/alignment/test.py
@@ -0,0 +1,41 @@
+import cv2
+import sys
+import numpy as np
+import datetime
+from alignment import Alignment
+sys.path.append('../SSH')
+from ssh_detector import SSHDetector
+
+long_max = 1200
+t = 2
+
+detector = SSHDetector('../SSH/model/e2ef', 0)
+alignment = Alignment('./model/3d_I5', 12)
+
+f = '../sample-images/t2.jpg'
+if len(sys.argv)>1:
+  f = sys.argv[1]
+img = cv2.imread(f)
+print(img.shape)
+if img.shape[0]>long_max or img.shape[1]>long_max:
+  scale = float(long_max) / max(img.shape[0], img.shape[1])
+  img = cv2.resize(img, (0,0), fx=scale, fy=scale)
+  print('resize to', img.shape)
+for i in xrange(t-1): #warmup
+  faces = detector.detect(img)
+timea = datetime.datetime.now()
+faces = detector.detect(img)
+timeb = datetime.datetime.now()
+diff = timeb - timea
+print('detection uses', diff.total_seconds(), 'seconds')
+print('find', faces.shape[0], 'faces')
+
+for face in faces:
+  w = face[2] - face[0]
+  h = face[3] - face[1]
+  size = int(max(w, h)*1.3)
+  wc = int( (face[2]+face[0])/2 )
+  hc = int( (face[3]+face[1])/2 )
+  ebox = cv2.getRectSubPix(img, (size, size), (wc, hc))
+  landmark = alignment.get(ebox)
+  print(landmark.shape)
diff --git a/sample-images/t2.jpg b/sample-images/t2.jpg
new file mode 100644
index 0000000..dcca930
Binary files /dev/null and b/sample-images/t2.jpg differ