diff --git a/4-Object_Detection/RPN/train.py b/4-Object_Detection/RPN/train.py
index b1f72926..d7821915 100644
--- a/4-Object_Detection/RPN/train.py
+++ b/4-Object_Detection/RPN/train.py
@@ -119,12 +119,14 @@ def compute_loss(target_scores, target_bboxes, target_masks, pred_scores, pred_b
 STEPS = 4000
 batch_size = 2
 lambda_scale = 1.
-synthetic_dataset_path="./synthetic_dataset"
+project_directory = os.path.dirname(__file__)
+synthetic_dataset_path=os.path.join(project_directory, "synthetic_dataset")
+weights_path = os.path.join(project_directory, "RPN.h5")
 TrainSet = DataGenerator(synthetic_dataset_path, batch_size)
 
 model = RPNplus()
 optimizer = tf.keras.optimizers.Adam(lr=1e-4)
-writer = tf.summary.create_file_writer("./log")
+writer = tf.summary.create_file_writer(os.path.join(project_directory, "log"))
 global_steps = tf.Variable(0, trainable=False, dtype=tf.int64)
 
 for epoch in range(EPOCHS):
@@ -145,7 +147,7 @@ def compute_loss(target_scores, target_bboxes, target_masks, pred_scores, pred_b
             tf.summary.scalar("score_loss", score_loss, step=global_steps)
             tf.summary.scalar("boxes_loss", boxes_loss, step=global_steps)
         writer.flush()
-    model.save_weights("RPN.h5")
+    model.save_weights(weights_path)
 
 
 
diff --git a/4-Object_Detection/YOLOV3/core/config.py b/4-Object_Detection/YOLOV3/core/config.py
index f23265ca..a3a49eb7 100644
--- a/4-Object_Detection/YOLOV3/core/config.py
+++ b/4-Object_Detection/YOLOV3/core/config.py
@@ -12,6 +12,7 @@
 #================================================================
 
 from easydict import EasyDict as edict
+import os
 
 
 __C                           = edict()
@@ -23,8 +24,10 @@
 __C.YOLO                      = edict()
 
 # Set the class name
-__C.YOLO.CLASSES              = "./data/classes/coco.names"
-__C.YOLO.ANCHORS              = "./data/anchors/basline_anchors.txt"
+project_directory             = os.path.dirname(os.path.dirname(__file__))
+
+__C.YOLO.CLASSES              = os.path.join(project_directory, "data/classes/coco.names")
+__C.YOLO.ANCHORS              = os.path.join(project_directory, "data/anchors/basline_anchors.txt")
 __C.YOLO.STRIDES              = [8, 16, 32]
 __C.YOLO.ANCHOR_PER_SCALE     = 3
 __C.YOLO.IOU_LOSS_THRESH      = 0.5
@@ -32,7 +35,7 @@
 # Train options
 __C.TRAIN                     = edict()
 
-__C.TRAIN.ANNOT_PATH          = "./data/dataset/yymnist_train.txt"
+__C.TRAIN.ANNOT_PATH          = os.path.join(project_directory, "data/dataset/yymnist_train.txt")
 __C.TRAIN.BATCH_SIZE          = 4
 # __C.TRAIN.INPUT_SIZE            = [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
 __C.TRAIN.INPUT_SIZE          = [416]
@@ -47,11 +50,11 @@
 # TEST options
 __C.TEST                      = edict()
 
-__C.TEST.ANNOT_PATH           = "./data/dataset/yymnist_test.txt"
+__C.TEST.ANNOT_PATH           = os.path.join(project_directory, "data/dataset/yymnist_test.txt")
 __C.TEST.BATCH_SIZE           = 2
 __C.TEST.INPUT_SIZE           = 544
 __C.TEST.DATA_AUG             = False
-__C.TEST.DECTECTED_IMAGE_PATH = "./data/detection/"
+__C.TEST.DECTECTED_IMAGE_PATH = os.path.join(project_directory, "data/detection/")
 __C.TEST.SCORE_THRESHOLD      = 0.3
 __C.TEST.IOU_THRESHOLD        = 0.45