diff --git a/Dockerfile b/Dockerfile
index 7f3a24cbdcfebfecc5e660cc843aeb8db4964597..b2939936309a21771c9f22b8f161bad7c64cdbd6 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -21,6 +21,7 @@ RUN apt-get install --no-install-recommends \
          libopencv-dev \
          libceres-dev \
          python3-pybind11 \
+         git \
          libboost1.71-dev  -y
 
 # 2) set up python module's build environment
@@ -31,18 +32,14 @@ RUN apt install --no-install-recommends \
 # 3) set up python run environment
 # Put everything in some subfolder
 WORKDIR "/monodepth"
-COPY code/ ./
-RUN mkdir data/ && mkdir data/erp_00/
-COPY data/erp_00/0001_rgb.jpg ./data/erp_00/
+COPY . ./
+RUN git submodule update --init
 
-RUN pip3 install -r ./python/requirements.txt
+RUN pip3 install -r ./code/python/requirements.txt
 
 #-- build python cpp module
 # 1) build the cpp project
-RUN cd cpp && mkdir build && cd build && cmake ..  -DCMAKE_BUILD_TYPE=Release && make -j
+RUN cd ./code/cpp && mkdir build && cd build && cmake ..  -DCMAKE_BUILD_TYPE=Release && make -j
 
 # 2) build & install python module
-RUN cd cpp/python/ && python3 ./setup.py build && python3 ./setup.py bdist_wheel && pip3 install dist/instaOmniDepth-0.1.0-cp38-cp38-linux_x86_64.whl
-
-# 3) run test script
-RUN cd /monodepth/python/src/test && python3 ./test_depthmapAlign_module.py --task 1
+RUN cd ./code/cpp/python/ && python3 ./setup.py build && python3 ./setup.py bdist_wheel && pip3 install dist/instaOmniDepth-0.1.0-cp38-cp38-linux_x86_64.whl
diff --git a/code/python/src/utility/depthmap_utils.py b/code/python/src/utility/depthmap_utils.py
index 48c7e23d7dde04cca014f64a1fdab5d4c6640a23..38a8c0f6e09ba8cc86513fc3e57025b10957942b 100644
--- a/code/python/src/utility/depthmap_utils.py
+++ b/code/python/src/utility/depthmap_utils.py
@@ -343,7 +343,7 @@ def boosting_monodepth(rgb_image_data_list):
     from BoostingMonocularDepth.pix2pix.models.pix2pix4depth_model import Pix2Pix4DepthModel
 
     # select device
-    device = torch.device("cpu")
+    device = torch.device("cuda")
     print("device: %s" % device)
 
     whole_size_threshold = 3000  # R_max from the paper