diff --git a/.gitignore b/.gitignore
index 6056764..9a70cc7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,18 +1,10 @@
 __pycache__/
-.ipynb_checkpoints/
-src/__pycache__/
-dataset/conv/
-dataset/Dusk/
-dataset/fall/
-dataset/model/
-dataset/output_database/
-dataset/output_query/
-dataset/Rain/
-dataset/spring/
-dataset/summer/
-dataset/Sun/
-dataset/winter/
-dataset/event.csv/
-models/VPRTempo78415685001.pth
-models/VPRTempoQuant78415685001.pth
-VPRTempo.egg-info/
+.pyest_cache/
+vprtempo/__pycache__/
+vprtempo/dataset/fall/
+vprtempo/dataset/spring/
+vprtempo/dataset/summer/
+vprtempo/dataset/winter/
+vprtempo/dataset/event.csv
+vprtempo/output/
+vprtempo/src/__pycache__/
diff --git a/README.md b/README.md
index 4244cda..a22dcc7 100644
--- a/README.md
+++ b/README.md
@@ -56,7 +56,7 @@ Once downloaded, please install the required dependencies to run the network thr
 Dependencies for VPRTempo can downloaded from our [PyPi package](https://pypi.org/project/VPRTempo/).
 
 ```python
-pip3 install VPRTempo
+pip install vprtempo
 ```
 If you wish to enable CUDA, please follow the instructions on the [PyTorch - Get Started](https://pytorch.org/get-started/locally/) page to install the required software versions for your hardware and operating system.
 
diff --git a/dataset/event.csv b/dataset/event.csv
deleted file mode 100644
index d39b74a..0000000
--- a/dataset/event.csv
+++ /dev/null
@@ -1,160 +0,0 @@
-Image_names,Index
-match_0245.png,0
-match_0247.png,1
-match_0248.png,2
-match_0249.png,3
-match_0250.png,4
-match_0251.png,5
-match_0253.png,6
-match_0256.png,7
-match_0329.png,8
-match_0332.png,9
-match_0333.png,10
-match_0334.png,11
-match_0337.png,12
-match_0338.png,13
-match_0345.png,14
-match_0346.png,15
-match_0347.png,16
-match_0348.png,17
-match_0349.png,18
-match_0350.png,19
-match_0351.png,20
-match_0352.png,21
-match_0354.png,22
-match_0355.png,23
-match_0356.png,24
-match_0357.png,25
-match_0358.png,26
-match_0359.png,27
-match_0361.png,28
-match_0362.png,29
-match_0363.png,30
-match_0364.png,31
-match_0365.png,32
-match_0366.png,33
-match_0367.png,34
-match_0368.png,35
-match_0369.png,36
-match_0370.png,37
-match_0371.png,38
-match_0372.png,39
-match_0373.png,40
-match_0374.png,41
-match_0375.png,42
-match_0376.png,43
-match_0377.png,44
-match_0378.png,45
-match_0379.png,46
-match_0380.png,47
-match_0381.png,48
-match_0382.png,49
-match_0383.png,50
-match_0384.png,51
-match_0385.png,52
-match_0386.png,53
-match_0387.png,54
-match_0388.png,55
-match_0389.png,56
-match_0390.png,57
-match_0391.png,58
-match_0392.png,59
-match_0393.png,60
-match_0394.png,61
-match_0395.png,62
-match_0396.png,63
-match_0397.png,64
-match_0398.png,65
-match_0399.png,66
-match_0400.png,67
-match_0401.png,68
-match_0402.png,69
-match_0403.png,70
-match_0404.png,71
-match_0405.png,72
-match_0491.png,73
-match_0492.png,74
-match_0494.png,75
-match_0538.png,76
-match_0539.png,77
-match_0540.png,78
-match_0541.png,79
-match_0542.png,80
-match_0543.png,81
-match_0544.png,82
-match_0545.png,83
-match_0546.png,84
-match_0547.png,85
-match_0548.png,86
-match_0549.png,87
-match_0550.png,88
-match_0551.png,89
-match_0552.png,90
-match_0553.png,91
-match_0554.png,92
-match_0555.png,93
-match_0720.png,94
-match_0790.png,95
-match_0792.png,96
-match_0793.png,97
-match_0794.png,98
-match_0795.png,99
-match_0796.png,100
-match_0797.png,101
-match_0798.png,102
-match_0799.png,103
-match_0800.png,104
-match_0801.png,105
-match_0802.png,106
-match_0803.png,107
-match_0804.png,108
-match_0805.png,109
-match_0806.png,110
-match_0807.png,111
-match_0808.png,112
-match_0809.png,113
-match_0810.png,114
-match_0811.png,115
-match_0812.png,116
-match_0813.png,117
-match_0814.png,118
-match_0815.png,119
-match_0816.png,120
-match_0817.png,121
-match_0818.png,122
-match_0819.png,123
-match_0820.png,124
-match_0821.png,125
-match_0822.png,126
-match_0823.png,127
-match_0824.png,128
-match_0825.png,129
-match_0826.png,130
-match_0827.png,131
-match_0828.png,132
-match_0829.png,133
-match_0830.png,134
-match_0831.png,135
-match_0832.png,136
-match_0833.png,137
-match_0834.png,138
-match_0835.png,139
-match_0840.png,140
-match_0880.png,141
-match_0881.png,142
-match_0882.png,143
-match_0883.png,144
-match_0884.png,145
-match_0885.png,146
-match_0886.png,147
-match_0887.png,148
-match_0888.png,149
-match_0889.png,150
-match_0890.png,151
-match_0911.png,152
-match_0914.png,153
-match_0919.png,154
-match_0921.png,155
-match_0922.png,156
-match_0924.png,157
-match_0925.png,158
diff --git a/dataset/test/images-00202.png b/dataset/test/images-00202.png
deleted file mode 100644
index 56ae0ca..0000000
Binary files a/dataset/test/images-00202.png and /dev/null differ
diff --git a/dataset/test/images-07028.png b/dataset/test/images-07028.png
deleted file mode 100755
index 9d5bc63..0000000
Binary files a/dataset/test/images-07028.png and /dev/null differ
diff --git a/main.py b/main.py
index a5cb8c0..753163e 100644
--- a/main.py
+++ b/main.py
@@ -23,17 +23,16 @@
 '''
 Imports
 '''
-import argparse
 import sys
-sys.path.append('./src')
-sys.path.append('./vprtempo')
+import argparse
+
 import torch.quantization as quantization
 
-from VPRTempoTrain import VPRTempoTrain, generate_model_name, check_pretrained_model, train_new_model
-from VPRTempo import VPRTempo, run_inference
-from VPRTempoQuantTrain import VPRTempoQuantTrain, generate_model_name_quant, train_new_model_quant
-from VPRTempoQuant import VPRTempoQuant, run_inference_quant
-from loggers import model_logger, model_logger_quant
+from vprtempo.VPRTempo import VPRTempo, run_inference
+from vprtempo.src.loggers import model_logger, model_logger_quant
+from vprtempo.VPRTempoQuant import VPRTempoQuant, run_inference_quant
+from vprtempo.VPRTempoQuantTrain import VPRTempoQuantTrain, generate_model_name_quant, train_new_model_quant
+from vprtempo.VPRTempoTrain import VPRTempoTrain, generate_model_name, check_pretrained_model, train_new_model
 
 def initialize_and_run_model(args,dims):
     # If user wants to train a new network
@@ -109,7 +108,7 @@ def parse_network(use_quantize=False, train_new_model=False):
     # Define the dataset arguments
     parser.add_argument('--dataset', type=str, default='nordland',
                             help="Dataset to use for training and/or inferencing")
-    parser.add_argument('--data_dir', type=str, default='./dataset/',
+    parser.add_argument('--data_dir', type=str, default='./vprtempo/dataset/',
                             help="Directory where dataset files are stored")
     parser.add_argument('--num_places', type=int, default=500,
                             help="Number of places to use for training and/or inferencing")
diff --git a/setup.py b/setup.py
index 616f7b9..8552819 100644
--- a/setup.py
+++ b/setup.py
@@ -21,7 +21,7 @@
 # define the setup
 setup(
     name="VPRTempo",
-    version="1.1.2",
+    version="1.1.3",
     description='VPRTempo: A Fast Temporally Encoded Spiking Neural Network for Visual Place Recognition',
     long_description=long_description,
     long_description_content_type='text/markdown',
diff --git a/src/.DS_Store b/src/.DS_Store
deleted file mode 100644
index 1e5c5df..0000000
Binary files a/src/.DS_Store and /dev/null differ
diff --git a/vprtempo/VPRTempo.py b/vprtempo/VPRTempo.py
index 18f4d17..6a0a2f0 100644
--- a/vprtempo/VPRTempo.py
+++ b/vprtempo/VPRTempo.py
@@ -26,22 +26,16 @@
 
 import os
 import torch
-import gc
-import sys
-sys.path.append('./src')
-sys.path.append('./models')
-sys.path.append('./output')
-sys.path.append('./dataset')
-
-import blitnet as bn
+
 import numpy as np
 import torch.nn as nn
+import vprtempo.src.blitnet as bn
 
-from dataset import CustomImageDataset, ProcessImage
-from torch.utils.data import DataLoader
 from tqdm import tqdm
 from prettytable import PrettyTable
-from metrics import recallAtK
+from torch.utils.data import DataLoader
+from vprtempo.src.metrics import recallAtK
+from vprtempo.src.dataset import CustomImageDataset, ProcessImage
 
 class VPRTempo(nn.Module):
     def __init__(self, dims, args=None, logger=None):
@@ -60,7 +54,7 @@ def __init__(self, dims, args=None, logger=None):
 
         self.logger = logger
         # Set the dataset file
-        self.dataset_file = os.path.join('./dataset', self.dataset + '.csv')  
+        self.dataset_file = os.path.join('./vprtempo/dataset', self.dataset + '.csv')  
 
         # Layer dict to keep track of layer names and their order
         self.layer_dict = {}
@@ -220,7 +214,7 @@ def run_inference(models, model_name):
                              persistent_workers=True)
 
     # Load the model
-    models[0].load_model(models, os.path.join('./models', model_name))
+    models[0].load_model(models, os.path.join('./vprtempo/models', model_name))
 
     # Retrieve layer names for inference
     layer_names = list(models[0].layer_dict.keys())
diff --git a/vprtempo/VPRTempoQuant.py b/vprtempo/VPRTempoQuant.py
index f616289..b667923 100644
--- a/vprtempo/VPRTempoQuant.py
+++ b/vprtempo/VPRTempoQuant.py
@@ -26,26 +26,17 @@
 
 import os
 import torch
-import subprocess
-import sys
-sys.path.append('./src')
-sys.path.append('./models')
-sys.path.append('./output')
-sys.path.append('./dataset')
-
-import blitnet as bn
+
 import numpy as np
 import torch.nn as nn
-import torch.quantization as quantization
+import vprtempo.src.blitnet as bn
 
-from loggers import model_logger_quant
-from VPRTempoQuantTrain import generate_model_name_quant
-from dataset import CustomImageDataset, ProcessImage
-from torch.utils.data import DataLoader
-from torch.ao.quantization import QuantStub, DeQuantStub
 from tqdm import tqdm
 from prettytable import PrettyTable
-from metrics import recallAtK
+from torch.utils.data import DataLoader
+from vprtempo.src.metrics import recallAtK
+from torch.ao.quantization import QuantStub, DeQuantStub
+from vprtempo.src.dataset import CustomImageDataset, ProcessImage
 
 #from main import parse_network
 
@@ -59,7 +50,7 @@ def __init__(self, dims, args=None, logger=None):
             setattr(self, arg, getattr(args, arg))
         setattr(self, 'dims', dims)
         # Set the dataset file
-        self.dataset_file = os.path.join('./dataset', self.dataset + '.csv')
+        self.dataset_file = os.path.join('./vprtempo/dataset', self.dataset + '.csv')
 
         # Set the model logger and return the device
         self.logger = logger
@@ -240,7 +231,7 @@ def run_inference_quant(models, model_name, qconfig):
                              persistent_workers=True)
 
     # Load the model
-    models[0].load_model(models, os.path.join('./models', model_name))
+    models[0].load_model(models, os.path.join('./vprtempo/models', model_name))
 
     # Use evaluate method for inference accuracy
     with torch.no_grad():
diff --git a/vprtempo/VPRTempoQuantTrain.py b/vprtempo/VPRTempoQuantTrain.py
index 6c2448a..451420a 100644
--- a/vprtempo/VPRTempoQuantTrain.py
+++ b/vprtempo/VPRTempoQuantTrain.py
@@ -26,23 +26,17 @@
 
 import os
 import torch
-import gc
-import sys
-sys.path.append('./src')
-sys.path.append('./models')
-sys.path.append('./output')
-sys.path.append('./dataset')
 
-import blitnet as bn
 import numpy as np
 import torch.nn as nn
+import vprtempo.src.blitnet as bn
 import torch.quantization as quantization
 import torchvision.transforms as transforms
 
-from dataset import CustomImageDataset, ProcessImage
+from tqdm import tqdm
 from torch.utils.data import DataLoader
 from torch.ao.quantization import QuantStub, DeQuantStub
-from tqdm import tqdm
+from vprtempo.src.dataset import CustomImageDataset, ProcessImage
 
 class VPRTempoQuantTrain(nn.Module):
     def __init__(self, args, dims, logger):
@@ -61,7 +55,7 @@ def __init__(self, args, dims, logger):
         self.logger = logger
 
         # Set the dataset file
-        self.dataset_file = os.path.join('./dataset', self.dataset + '.csv')
+        self.dataset_file = os.path.join('./vprtempo/dataset', self.dataset + '.csv')
 
         # Add quantization stubs for Quantization Aware Training (QAT)
         self.quant = QuantStub()
@@ -288,4 +282,4 @@ def train_new_model_quant(models, model_name, qconfig):
         # After training the current layer, add it to the list of trained layer
 
     # Save the model
-    model.save_model(trained_models,os.path.join('./models', model_name))   
\ No newline at end of file
+    model.save_model(trained_models,os.path.join('./vprtempo/models', model_name))   
\ No newline at end of file
diff --git a/vprtempo/VPRTempoTrain.py b/vprtempo/VPRTempoTrain.py
index 077ccf3..de3d449 100644
--- a/vprtempo/VPRTempoTrain.py
+++ b/vprtempo/VPRTempoTrain.py
@@ -25,23 +25,18 @@
 '''
 
 import os
-import torch
 import gc
-import sys
-sys.path.append('./src')
-sys.path.append('./models')
-sys.path.append('./output')
-sys.path.append('./dataset')
+import torch
 
-import blitnet as bn
 import numpy as np
 import torch.nn as nn
+import vprtempo.src.blitnet as bn
 import torchvision.transforms as transforms
 
-from loggers import model_logger
-from dataset import CustomImageDataset, ProcessImage
-from torch.utils.data import DataLoader
 from tqdm import tqdm
+from torch.utils.data import DataLoader
+from vprtempo.src.loggers import model_logger
+from vprtempo.src.dataset import CustomImageDataset, ProcessImage
 
 class VPRTempoTrain(nn.Module):
     def __init__(self, args, dims, logger):
@@ -59,7 +54,7 @@ def __init__(self, args, dims, logger):
         self.logger = logger
 
         # Set the dataset file
-        self.dataset_file = os.path.join('./dataset', self.dataset + '.csv')
+        self.dataset_file = os.path.join('./vprtempo/dataset', self.dataset + '.csv')
 
         # Layer dict to keep track of layer names and their order
         self.layer_dict = {}
@@ -293,4 +288,4 @@ def train_new_model(models, model_name):
     for model in models:
         model.eval()
     # Save the model
-    model.save_model(models,os.path.join('./models', model_name))    
\ No newline at end of file
+    model.save_model(models,os.path.join('./vprtempo/models', model_name))    
\ No newline at end of file
diff --git a/vprtempo/__init__.py b/vprtempo/__init__.py
index 8aafc8b..d61c457 100644
--- a/vprtempo/__init__.py
+++ b/vprtempo/__init__.py
@@ -1,2 +1,6 @@
-from .VPRTempo import VPRTempo
-from .VPRTempoQuantTrain import VPRTempoQuantTrain
\ No newline at end of file
+from . import dataset
+from . import models
+from . import output
+from . import src
+
+__version__ = '1.1.3'
\ No newline at end of file
diff --git a/dataset/.DS_Store b/vprtempo/dataset/.DS_Store
similarity index 100%
rename from dataset/.DS_Store
rename to vprtempo/dataset/.DS_Store
diff --git a/dataset/nordland.csv b/vprtempo/dataset/nordland.csv
similarity index 100%
rename from dataset/nordland.csv
rename to vprtempo/dataset/nordland.csv
diff --git a/dataset/orc.csv b/vprtempo/dataset/orc.csv
similarity index 100%
rename from dataset/orc.csv
rename to vprtempo/dataset/orc.csv
diff --git a/models/.DS_Store b/vprtempo/models/.DS_Store
similarity index 100%
rename from models/.DS_Store
rename to vprtempo/models/.DS_Store
diff --git a/models/.gitkeep b/vprtempo/models/.gitkeep
similarity index 100%
rename from models/.gitkeep
rename to vprtempo/models/.gitkeep
diff --git a/output/.gitkeep b/vprtempo/src/__init__.py
similarity index 100%
rename from output/.gitkeep
rename to vprtempo/src/__init__.py
diff --git a/src/blitnet.py b/vprtempo/src/blitnet.py
similarity index 100%
rename from src/blitnet.py
rename to vprtempo/src/blitnet.py
diff --git a/src/dataset.py b/vprtempo/src/dataset.py
similarity index 99%
rename from src/dataset.py
rename to vprtempo/src/dataset.py
index 9ed9112..976dbf2 100644
--- a/src/dataset.py
+++ b/vprtempo/src/dataset.py
@@ -5,7 +5,6 @@
 import pandas as pd
 import numpy as np
 import torch.nn.functional as F
-import torch.quantization as tq
 
 from torchvision.io import read_image
 from torch.utils.data import Dataset
diff --git a/src/loggers.py b/vprtempo/src/loggers.py
similarity index 97%
rename from src/loggers.py
rename to vprtempo/src/loggers.py
index eace9ef..3081a02 100644
--- a/src/loggers.py
+++ b/vprtempo/src/loggers.py
@@ -9,7 +9,7 @@ def model_logger():
     Configure the model logger
     """   
     now = datetime.now()
-    output_folder = './output/' + now.strftime("%d%m%y-%H-%M-%S")
+    output_folder = './vprtempo/output/' + now.strftime("%d%m%y-%H-%M-%S")
     
     os.mkdir(output_folder)
     # Create the logger
@@ -54,7 +54,7 @@ def model_logger_quant():
     """   
 
     now = datetime.now()
-    output_folder = './output/' + now.strftime("%d%m%y-%H-%M-%S")
+    output_folder = './vprtempo/output/' + now.strftime("%d%m%y-%H-%M-%S")
     
     os.mkdir(output_folder)
     # Create the logger
diff --git a/src/metrics.py b/vprtempo/src/metrics.py
similarity index 100%
rename from src/metrics.py
rename to vprtempo/src/metrics.py
diff --git a/src/nordland.py b/vprtempo/src/nordland.py
similarity index 100%
rename from src/nordland.py
rename to vprtempo/src/nordland.py