diff --git a/docs/environment_setup.txt b/docs/environment_setup.txt
index 0c6226e..6b69fb9 100644
--- a/docs/environment_setup.txt
+++ b/docs/environment_setup.txt
@@ -1,32 +1,28 @@
 SETUP OF ENVIRONMENT
 --------------------
-Instruction below is for the setup on Win 10 using CUDA v10.1. Setup will be different depending on
-operating system.
+Instruction below is for the setup on Win 10. Different versions may be used, but the following setup has been tested.
+Setup will be different depending on operating system.
 
 1. Update GPU drivers
 2. Install visual studio + individual components:
 	a) MSVC v142 - VS 2019 C++ x64/x86 build tools
 	b) Windows 10 SDK (10.0.18362.0)
-3. Download CUDA toolkit 10.1 Update 2
+3. Download CUDA (here v11.4)
 	a) install only 'Developer' and 'Runtime' modules
-4. Download CuDNN 7.6.5 for CUDA 10.1
-	a) unpack to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\
+4. Download CuDNN v8.2.1.32 for CUDA 11.4
+	a) unpack to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4\
 5. Add system variables (Control panel > Edit system environment variables):
 	   [NAME & PATH]
-	a) INCLUDE C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include
-	b) LIB C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\lib\x64
+	a) INCLUDE C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4\include
+	b) LIB C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.4\lib\x64
 6. Create Python/Anaconda environment
-	a) Packages:
-	    tensorflow-gpu==2.3.1
-	    jupyter-tensorboard
-	    nodejs==0.1.1
-	    npm==0.1.1
-	    pybind11==2.5.0
-	    gputools==0.2.9
-	    stardist
-	    numpy
-	    pandas
-	    pathlib
-	    tifffile
-	b) on Windows, install PyOpenCL from pre-made binary:
-	   https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl
\ No newline at end of file
+	a) 1. conda create -n stardistenv python=3.9
+	   2. conda activate stardistenv
+	       -------OR-------
+	   1. python -m virtualenv stardistenv
+	   2. stardistenv\Scripts\activate
+
+	b) Install packages:
+	   pip install tensorflow jupyter-tensorboard nodejs npm pybind11 gputools stardist pandas pathlib tifffile scikit-tensor-py3 pyopencl
+	!!! on Windows, install PyOpenCL from pre-made binary (https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl):
+	   i.e. above, in pip install-command change pyopencl to path\to\pyopencl.whl
\ No newline at end of file
diff --git a/docs/requirements.txt b/docs/requirements.txt
index 2498e3f..b6b927f 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,11 +1,15 @@
-tensorflow-gpu          # ==2.3.1
+tensorflow
 jupyter-tensorboard
-nodejs                  # ==0.1.1
-npm                     # ==0.1.1
-pybind11                # ==2.5.0
-gputools                # ==0.2.9
+nodejs
+npm
+pybind11
+gputools
 stardist
 pandas
 pathlib
 tifffile
+scikit-tensor-py3
 pyopencl
+
+# pip install tensorflow jupyter-tensorboard nodejs npm pybind11 gputools stardist pandas pathlib tifffile scikit-tensor-py3 pyopencl
+# ON WIN10 REPLACE PYOPENCL WITH path\to\pyopencl.whl
\ No newline at end of file
diff --git a/predictSD/labelCollect.py b/predictSD/labelCollect.py
index 9c44549..09594c8 100644
--- a/predictSD/labelCollect.py
+++ b/predictSD/labelCollect.py
@@ -140,7 +140,7 @@ def _get_intensities(self, notnull: tuple) -> dict:
         if self.image.channels is not None:
             return {f"Intensity Mean_Ch={ch}": self.image.get_channels(ch)[notnull]
                     for ch in np.arange(0, self.image.channels)}
-        return {"Intensity": self.image.img[notnull]}
+        return {"Intensity Mean": self.image.img[notnull]}
 
     def _test_img_shapes(self) -> None:
         """Assert that image and label file shapes match."""
diff --git a/readme.md b/readme.md
index cc008cc..6e686ae 100644
--- a/readme.md
+++ b/readme.md
@@ -8,7 +8,7 @@ each label in the segmentation images is marked by a single, unique value.
 ## Installation
 PredictSD requires an environment that is capable of running StarDist. For the creation of such environment, see
 [StarDist's GitHub-page](https://github.com/stardist/stardist/). Required packages are listed in
-'predictSD/docs/requirements.txt'. For installation on Win10 using CUDA 10.1, see
+'predictSD/docs/requirements.txt'. For installation on Win10 using CUDA 11.4, see
 'predictSD/docs/environment_setup.txt'.
 
 ## labelCollect.py