diff --git a/face/face.py b/face/face.py
index 4dc874f..8501957 100644
--- a/face/face.py
+++ b/face/face.py
@@ -1,16 +1,46 @@
-from facenet_pytorch import MTCNN
-import cv2
-from PIL import Image, ImageDraw, ImageColor
-import numpy as np
-from matplotlib import pyplot as plt
+import os
+import sys
 
-mtcnn = MTCNN(keep_all=True)
+from facenet_pytorch import MTCNN, InceptionResnetV1
+from PIL import Image
 
-img = Image.open("face.jpg")
 
-boxes, _ = mtcnn.detect(img)
-draw = ImageDraw.Draw(img)
-for i, box in enumerate(boxes):
-    draw.rectangle(((box[0], box[1]), (box[2], box[3])), outline="red")
-img.save("detected.jpg")
-#print(face)
+def detect(input_dir, output_dir):
+    mtcnn = MTCNN(keep_all=True)
+    resnet = InceptionResnetV1(pretrained='vggface2').eval()
+    for f in os.listdir(input_dir):
+        with Image.open(input_dir + "/" + f) as img:
+            # if img.filename != "input/P7260028.jpg":
+            #     continue
+            print(img.filename)
+            for m in mtcnn(img):
+                print(resnet(m))
+            
+            # embedding = resnet(mtcnn(img))
+            # print(len(embedding[0]))
+            
+            # boxes, _ = mtcnn.detect(img)
+            # for i, box in enumerate(boxes):
+            #     cropped = img.crop(box)
+            #     cropped.save(output_dir + "/" + str(i) + "_" + f)
+
+
+def classify(input_dir, output_dir):
+    mtcnn = MTCNN()
+    resnet = InceptionResnetV1(pretrained='vggface2').eval()
+    for f in os.listdir(input_dir):
+        with Image.open(input_dir + "/" + f) as img:
+            print(img.filename)            
+            embedding = resnet(mtcnn(img))
+            print(len(embedding[0]))
+    
+
+def main():
+    if sys.argv[1] == "detect":
+        detect(sys.argv[2], sys.argv[3])
+    else:
+        classify(sys.argv[2], sys.argv[3])
+
+
+if __name__ == "__main__":
+    main()