diff --git a/realTime.py b/realTime.py
new file mode 100644
index 0000000000000000000000000000000000000000..45264fdc21e577ca1bf6facddc321b9d4b57bc05
--- /dev/null
+++ b/realTime.py
@@ -0,0 +1,201 @@
+import pyautogui
+import time
+import actgui
+
+import cv2
+import numpy as np
+from unified_detector import Fingertips
+from hand_detector.detector import SOLO, YOLO
+
+
+def main():
+ hand_detection_method = 'yolo'
+
+ if hand_detection_method is 'solo':
+ hand = SOLO(weights='weights/solo.h5', threshold=0.8)
+ elif hand_detection_method is 'yolo':
+ hand = YOLO(weights='weights/yolo.h5', threshold=0.8)
+ else:
+ assert False, "'" + hand_detection_method + \
+ "' hand detection does not exist. use either 'solo' or 'yolo' as hand detection method"
+
+ fingertips = Fingertips(weights='weights/fingertip.h5')
+
+ cam = cv2.VideoCapture(0)
+ print('Unified Gesture & Fingertips Detection')
+
+
+ while True:
+ time.sleep(0.2)
+ ret, image = cam.read()
+ ################################################
+ # openCV CAM flip
+ ################################################
+ image = cv2.flip(image,1)
+ ################################################
+ if ret is False:
+ break
+
+ # hand detection
+ tl, br = hand.detect(image=image)
+
+ if tl and br is not None:
+ cropped_image = image[tl[1]:br[1], tl[0]: br[0]]
+ height, width, _ = cropped_image.shape
+
+ # gesture classification and fingertips regression
+ prob, pos = fingertips.classify(image=cropped_image)
+ pos = np.mean(pos, 0)
+
+ # post-processing
+ prob = np.asarray([(p >= 0.2) * 1.0 for p in prob])
+ for i in range(0, len(pos), 2):
+ pos[i] = pos[i] * width + tl[0]
+ pos[i + 1] = pos[i + 1] * height + tl[1]
+
+
+#########################################################
+ # start gui
+#########################################################
+
+ # hand check
+ case = actgui.hand_check(prob)
+ print(case)
+ actgui.store_pos(pos)
+
+ # 좌표 초기화
+ actgui.initialize_coordinate()
+
+ # 변수 초기화
+ actgui.initialize_variable()
+
+ # 종료 확인
+ bool = actgui.terminate_check()
+ if bool: break
+
+ ##########################
+ # 작동
+ actgui.act_gui()
+
+#########################################################
+ # end gui
+#########################################################
+ # drawing
+ index = 0
+ color = [(15, 15, 240), (15, 240, 155), (240, 155, 15), (240, 15, 155), (240, 15, 240)]
+ # 손 범위
+ image = cv2.rectangle(image, (tl[0], tl[1]), (br[0], br[1]), (235, 26, 158), 2)
+ # 원 그리기
+ for c, p in enumerate(prob):
+ if p > 0.5:
+ image = cv2.circle(image, (int(pos[index]), int(pos[index + 1])), radius=12,
+ color=color[c], thickness=-2)
+ index = index + 2
+
+ if cv2.waitKey(1) & 0xff == 27:
+ break
+
+ # display image
+ image = cv2.resize(image, dsize=(0, 0), fx=0.3, fy=0.3, interpolation=cv2.INTER_AREA)
+ cv2.imshow('Unified Gesture & Fingertips Detection', image)
+
+ cam.release()
+ cv2.destroyAllWindows()
+
+
+def mainleft():
+ hand_detection_method = 'yolo'
+
+ if hand_detection_method is 'solo':
+ hand = SOLO(weights='weights/solo.h5', threshold=0.8)
+ elif hand_detection_method is 'yolo':
+ hand = YOLO(weights='weights/yolo.h5', threshold=0.8)
+ else:
+ assert False, "'" + hand_detection_method + \
+ "' hand detection does not exist. use either 'solo' or 'yolo' as hand detection method"
+
+ fingertips = Fingertips(weights='weights/fingertip.h5')
+
+ cam = cv2.VideoCapture(0)
+ print('Unified Gesture & Fingertips Detection')
+
+
+ while True:
+ time.sleep(0.2)
+ ret, image = cam.read()
+ ################################################
+
+ ################################################
+ if ret is False:
+ break
+
+ # hand detection
+ tl, br = hand.detect(image=image)
+
+ if tl and br is not None:
+ cropped_image = image[tl[1]:br[1], tl[0]: br[0]]
+ height, width, _ = cropped_image.shape
+
+ # gesture classification and fingertips regression
+ prob, pos = fingertips.classify(image=cropped_image)
+ pos = np.mean(pos, 0)
+
+ # post-processing
+ prob = np.asarray([(p >= 0.2) * 1.0 for p in prob])
+ for i in range(0, len(pos), 2):
+ pos[i] = pos[i] * width + tl[0]
+ pos[i + 1] = pos[i + 1] * height + tl[1]
+
+
+#########################################################
+ # start gui
+#########################################################
+
+ # hand check
+ case = actgui.hand_check(prob)
+ print(case)
+ actgui.store_pos(pos)
+
+ # 좌표 초기화
+ actgui.initialize_coordinate()
+
+ # 변수 초기화
+ actgui.initialize_variable()
+
+ # 종료 확인
+ bool = actgui.terminate_check()
+ if bool: break
+
+ ##########################
+ # 작동
+ actgui.act_gui()
+
+#########################################################
+ # end gui
+#########################################################
+ # drawing
+ index = 0
+ color = [(15, 15, 240), (15, 240, 155), (240, 155, 15), (240, 15, 155), (240, 15, 240)]
+ # 손 범위
+ image = cv2.rectangle(image, (tl[0], tl[1]), (br[0], br[1]), (235, 26, 158), 2)
+ # 원 그리기
+ for c, p in enumerate(prob):
+ if p > 0.5:
+ image = cv2.circle(image, (int(pos[index]), int(pos[index + 1])), radius=12,
+ color=color[c], thickness=-2)
+ index = index + 2
+
+ if cv2.waitKey(1) & 0xff == 27:
+ break
+
+ # display image
+ image = cv2.resize(image, dsize=(0, 0), fx=0.3, fy=0.3, interpolation=cv2.INTER_AREA)
+ cv2.imshow('Unified Gesture & Fingertips Detection', image)
+
+ cam.release()
+ cv2.destroyAllWindows()
+
+
+
+if __name__=="__main__":
+ main()