diff --git a/live-recognition/live_recognition.py b/live-recognition/live_recognition.py
new file mode 100644
index 0000000..93fdf99
--- /dev/null
+++ b/live-recognition/live_recognition.py
@@ -0,0 +1,40 @@
+import cv2
+from darkflow.net.build import TFNet
+import numpy as np
+import time
+
+options = {
+    'model': 'cfg/tiny-yolo-voc-1c.cfg',
+    'load': 'bin/tiny-yolo-voc.weights',
+    'threshold': 0.7,
+    'gpu': 1.0
+}
+
+tfnet = TFNet(options)
+colors = [tuple(255 * np.random.rand(3)) for _ in range(10)]
+
+capture = cv2.VideoCapture(0)
+capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
+capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
+
+while True:
+    stime = time.time()
+    ret, frame = capture.read()
+    if ret:
+        results = tfnet.return_predict(frame)
+        for color, result in zip(colors, results):
+            tl = (result['topleft']['x'], result['topleft']['y'])
+            br = (result['bottomright']['x'], result['bottomright']['y'])
+            label = result['label']
+            confidence = result['confidence']
+            text = '{}: {:.0f}%'.format(label, confidence * 100)
+            frame = cv2.rectangle(frame, tl, br, color, 5)
+            frame = cv2.putText(
+                frame, text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
+        cv2.imshow('frame', frame)
+        print('FPS {:.2f}'.format(1 / (time.time() - stime)))
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+capture.release()
+cv2.destroyAllWindows()