diff --git a/README.md b/README.md
index d038f9d..6300672 100644
--- a/README.md
+++ b/README.md
@@ -68,7 +68,7 @@ This is not an officially endorsed Google product.
 ## Installation
 1. Clone the repo using the `--recursive` flag 
 ```bash
-git clone --recursive https://github.com/eriksandstroem/splat-slam-private.git
+git clone --recursive https://github.com/eriksandstroem/splat-slam.git
 cd splat-slam-private
 ```
 2. Creating a new conda environment. 
@@ -76,10 +76,10 @@ cd splat-slam-private
 conda create --name splat-slam python=3.10
 conda activate splat-slam
 ```
-3. Install CUDA 11.7 using conda and pytorch 1.12
+3. Install CUDA 11.7 using conda and pytorch 1.13.1
 ```bash
 conda install conda-forge::cudatoolkit-dev=11.7.0
-conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
+conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
 ```
 > Now make sure that "which python" points to the correct python
 executable. Also test that cuda is available
diff --git a/configs/Replica/replica.yaml b/configs/Replica/replica.yaml
index 87d65f3..da15e7d 100755
--- a/configs/Replica/replica.yaml
+++ b/configs/Replica/replica.yaml
@@ -54,4 +54,5 @@ cam:
   W_out: 640
 
 data:
-  output: /cluster/work/cvl/esandstroem/src/splat-slam/output/Replica
\ No newline at end of file
+  image_dir: /home/lbg030/Documents/Dataset/Replica/orig/Replica
+  output: /home/lbg030/Desktop/slam/Splat-SLAM
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 3197598..fb2cd69 100644
--- a/setup.py
+++ b/setup.py
@@ -19,15 +19,19 @@
 ROOT = osp.dirname(osp.abspath(__file__))
 
 setup(
-    name='droid_backends',
+    name='g_droid_backends',
     ext_modules=[
-        CUDAExtension('droid_backends',
-            include_dirs=[osp.join(ROOT, 'thirdparty/eigen')],
+        CUDAExtension('g_droid_backends',
+            include_dirs=[osp.join(ROOT, 'thirdparty/lietorch/eigen')],
             sources=[
-                'src/lib/droid.cpp',
-                'src/lib/droid_kernels.cu',
-                'src/lib/correlation_kernels.cu',
-                'src/lib/altcorr_kernel.cu',
+                # 'src/lib/droid.cpp',
+                # 'src/lib/droid_kernels.cu',
+                # 'src/lib/correlation_kernels.cu',
+                # 'src/lib/altcorr_kernel.cu',
+                'thirdparty/glorie_slam/lib/droid.cpp',
+                'thirdparty/glorie_slam/lib/droid_kernels.cu',
+                'thirdparty/glorie_slam/lib/correlation_kernels.cu',
+                'thirdparty/glorie_slam/lib/altcorr_kernel.cu',
             ],
             extra_compile_args={
                 'cxx': ['-O3'],
diff --git a/src/utils/datasets.py b/src/utils/datasets.py
index a589e31..ad12338 100644
--- a/src/utils/datasets.py
+++ b/src/utils/datasets.py
@@ -110,10 +110,10 @@ def __init__(self, cfg, device='cuda:0'):
             cfg['cam']['distortion']) if 'distortion' in cfg['cam'] else None
 
         # retrieve input folder as temporary folder
-        tmpdir = os.environ.get('TMPDIR')
-        self.input_folder = tmpdir + '/' + cfg['data']['input_folder']
+        # tmpdir = os.environ.get('TMPDIR')
+        img_dir = cfg['data']['image_dir']
+        self.input_folder = os.path.join(img_dir, cfg['data']['input_folder'])
         
-
     def __len__(self):
         return self.n_img
 
diff --git a/thirdparty/glorie_slam/depth_video.py b/thirdparty/glorie_slam/depth_video.py
index c29bb0b..d32fa4b 100644
--- a/thirdparty/glorie_slam/depth_video.py
+++ b/thirdparty/glorie_slam/depth_video.py
@@ -15,7 +15,7 @@
 import numpy as np
 import torch
 import lietorch
-import droid_backends
+import g_droid_backends as droid_backends
 import thirdparty.glorie_slam.geom.ba
 from torch.multiprocessing import Value
 
diff --git a/thirdparty/glorie_slam/modules/droid_net/corr.py b/thirdparty/glorie_slam/modules/droid_net/corr.py
index 2ef6466..e330303 100755
--- a/thirdparty/glorie_slam/modules/droid_net/corr.py
+++ b/thirdparty/glorie_slam/modules/droid_net/corr.py
@@ -15,7 +15,7 @@
 import torch
 import torch.nn.functional as F
 
-import droid_backends
+import g_droid_backends as droid_backends
 
 
 class CorrSampler(torch.autograd.Function):