ipsedo / marlclassification Goto Github PK

Are there plans to adapt this code for 3D image volume data? I see that there is a default training argument for dim=2, but when I load a 3D grayscale image (shape = (40,320,320), and set dim = 3 and nb_actions=6, the code throws and error on the return of ./environment/observation.py.

Hi,

Great work!

I have trained a new model with 2 class using the 0 and 1 class images from mnist and got a 90% precision and 90% Recall
but when i do inference on single image always getting predicted class id 0

marl.json

predicted class and the confidence is coming same.

i have trained on custom data as well by increasing the number of agents and observations still same issue.

but at the end of the training the result looks different

Thanks

While running download_minist.sh file I am facing the following error,
Download MNIST png from Kaggle
Traceback (most recent call last):
File "/opt/conda/bin/kaggle", line 5, in
from kaggle.cli import main
File "/opt/conda/lib/python3.7/site-packages/kaggle/init.py", line 23, in
api.authenticate()
File "/opt/conda/lib/python3.7/site-packages/kaggle/api/kaggle_api_extended.py", line 166, in authenticate
self.config_file, self.config_dir))
OSError: Could not find kaggle.json. Make sure it's located in /root/.kaggle. Or use the environment method.
Extract mnistzip.zip
unzip: cannot find or open /kaggle/working/MARLClassification/resources/downloaded/mnistzip.zip, /kaggle/working/MARLClassification/resources/downloaded/mnistzip.zip.zip or /kaggle/working/MARLClassification/resources/downloaded/mnistzip.zip.ZIP.
Create all_png folder
mkdir: cannot create directory ‘/kaggle/working/MARLClassification/resources/downloaded/mnist_png/all_png’: No such file or directory
Copy train img to all_png folder
cp: cannot stat '/kaggle/working/MARLClassification/resources/downloaded/mnist_png/train/': No such file or directory
Copy eval img to all_png folder
cp: cannot stat '/kaggle/working/MARLClassification/resources/downloaded/mnist_png/valid/': No such file or directory

Hi @Ipsedo,

I have gone through your code, and I am able to train the model on the custom dataset, but while doing the inference and evaluation, I am confused with the eval options and main options, state_dict.

it would be helpful if you provide the steps or documentation for doing inference on a single image and testing the model on test dataset.

Thanks in advance.

Hi, the skin cancer dataset link provided is not working https://drive.google.com/drive/folders/17g6zFSbCNXTV3VaDKop73W7Cn-NJlTO7?usp=sharing.

please share the correct link