davidmallasen / livechess2fen Goto Github PK

Could the README file include all the library version for the framework dependencies

When #23 has been merged (thus resolving #17), the magic numbers (4 in this case) used here:

I am relatively new to Jetson Nano, and I wanted to install your chess board recognition algorithm. I think I followed the steps pretty well, and in the onnx-tensorrt installation, when I run the make command in the build folder, I get the following error:

CMakeFiles/nvonnxparser.dir/build.make:221: *** target pattern contains no '%'. Stop. CMakeFiles/Makefile2:109: recipe for target 'CMakeFiles/nvonnxparser.dir/all' failed make[1]: *** [CMakeFiles/nvonnxparser.dir/all] Error 2 Makefile:151: recipe for target 'all' failed make: *** [all] Error 2

I do not know how to solve this issue. Can someone help me with this? Any type of help will be appreciated.

(Alternatively, for the setup part, do I need to download all 27 assets in the initial release link?)

Thank you.

Should those 1200s be changed to 1199s?

The third dimension in

I wanted to try it out on my Jetson Nano, which has TRT 7.1. So I have to create the TRT model instead of using the one in Releases. When I run onnx2trt to convert:

./onnx2trt SqueezeNet1p1.onnx -o SqueezeNet1p1.trt

It asks me to provide an optimization profile:

----------------------------------------------------------------
Input filename:   SqueezeNet1p1.onnx
ONNX IR version:  0.0.5
Opset version:    10
Producer name:    keras2onnx
Producer version: 1.6.5
Domain:           onnx
Model version:    0
Doc string:
----------------------------------------------------------------
Parsing model
Building TensorRT engine, FP16 available:1
    Max batch size:     32
    Max workspace size: 1024 MiB
[2021-03-22 22:50:16   ERROR] Network has dynamic or shape inputs, but no optimization profile has been defined.
[2021-03-22 22:50:16   ERROR] Network validation failed.
terminate called after throwing an instance of 'std::runtime_error'
  what():  Failed to create object
Aborted (core dumped)

Could you please help me with this step?

After #39 is merged, add pytest setup for Ubuntu and basic testing instructions in the README.

Given the complexity and possible combinations in the code in lc2fen/infer_pieces.py, it would be extremely beneficial to add some basic testing for (some of) the functions in that file.

To that end, a new test directory could be created in the root of the repository to contain the test scripts. Two good python testing options could be unittest or pytest.

Feel free to leave a comment if you'd like some help/guidance tackling this problem or if you have some additional ideas.

Since the software stack supported by the Jetson Nano is no longer going to be updated, move all of the dependencies and code to a new branch to not hinder the development of new features of the project.

• Check version working on Jetson Nano
• Rename requirements_pc.txt -> requirements.txt
• Reorganize README
• Add pointers to the different branches

Allow users to use miniconda to set up the Python environment and packages.

Per #34, we're going to have two versions, one for Jetson Nano and the other for a "standard desktop," but since the current version in the repo is for the standard desktop, should I go ahead and update the Python version to 3.11 and the TensorFlow version to 2.13.0?

(What about the other version? Should I write "version-agnostic" code so that the code works with both TensorFlow 2.13.0 and TensorFlow 2.5.0? Or do I not worry about the Jetson Nano's version for now?)

Creating a diagram of the project and how the different modules interact with each other would ease the development process. This could be added to the documentation to better navigate the project.

Create a Docker image to simplify setting up the development environment significantly. This can be done by following the setting up documentation for PC (Linux/Windows).