tifffile | Read and write TIFF files | Computer Vision library

I beleive I had the following things wrong that prevented me from using Cuda. Despite having cuda installed the nvcc --version command indicated that Cuda was not installed and so what I did was add it to the path using this answer.

Despite doing that and deleting my original conda environment and using the conda install pytorch torchvision torchaudio cudatoolkit=11.3 matplotlib scipy opencv -c pytorch command again I still got False when evaluating torch.cuda.is_available().

I then used this command conda install pytorch torchvision torchaudio cudatoolkit=10.2 matplotlib scipy opencv -c pytorch changing cudatoolkit from verison 11.3 to version 10.2 and then it worked!

Now torch.cuda.is_available() evaluates to True

Unfortunately, Cuda version 10.2 was incompatible with my RTX 3060 gpu (and I'm assuming it is not compatible with all RTX 3000 cards). Cuda version 11.0 was giving me errors and Cuda version 11.3 only installs the CPU only versions for some reason. Cuda version 11.1 worked perfectly though!

This is the command I used to get it to work in the end: pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html

The error error: [Errno 2] No such file or directory: '/opt/anaconda3/lib/python3.8/site-packages/rtree/lib' was caused by py2app trying to build the program bundle using a non-existent interpreter. This means that even if you try to uninstall a manager like Anaconda, it still has option logs somewhere on your mac.

The fix:

1. Open the terminal and type the command type -a python.

• You will see similar lines

Your image is 4-channels of 32-bits each. PIL doesn’t support such images - see Available Modes here.

I would suggest tifffile or OpenCV’s cv2.imread(…, cv2.IMREAD_UNCHANGED)

Just to share, not sure it will help you. However it shows that in standard conditions it is possible to use the conda gcc as described in the documentation instead of the system gcc.

Build tags in you environment.yml are quite strict requirements to satisfy and most often not needed. In your case, changing the yml file to

In a uint8 image, all the pixels lie in the range 0..255. In a uint16 image, all the pixels lie in the range 0..65535.

So, the brightest pixel (255) in your input image will only be 255*100/65535 or 0.4% bright, also known as nearly black in your output image.

You will probably want to scale your image, multiplying by 255 or shifting left 8 bits to give it a comparable brightness.

Note there is no benefit of increased luminosity resolution as a result of your operation - so I hope there is some other unmentioned purpose to moving to 16-bit.

Looks like this is part of an actively tracked issue with Tkinter in PyCharm. You can find the reference on the Pycharm's developer's issue tracker. The issue is undiagnosed, but if looking at similar problems with Tk on StackOverflow, one can see that it's an issue with thread safety and/or multithreading.

All I can do is speculate as to the cause, which is not helpful, however, I can at least collate the suggested workarounds:

1. Switch to a different Matplotlib backend (See docs: What is a backend?). Such as Qt5, but you will need to make sure they are available in your environment.

   This approach is the most promising as other backends are better able to deal with not being the main thread or are explicitly safe for multi-threading. It's also the simplest unless you have a really specific reason for preferring TkAgg.

2. Do not use the debugger with interactive plots.

3. Set "Variables Loading Policy" to "Synchronously" in Debugger as suggested by a PyCharm dev in the linked issue.

4. Enable "Scientific mode" in Pycharm.

5. More esoteric workarounds such as closing your figures within the code before drawing the second one. Example, after plotting the first figure:

PerkinElmer QPI metadata are stored as XML in the ImageDescription TIFF tags. To read the XML metadata, use the tifffile.TiffFile class, e.g.:

The string you got here turns out to be encoded as xml. You can have a look here on how to convert an xml-string to dict: How to convert an XML string to a dictionary?

Using one of the answers there, I did the following: