Hello,
I’m running the entire classification process in the notebook and I’m getting the onnx model. After resolving the error “Initializer onnx::MatMul_3870 appears in graph inputs and will not be treated as a constant value/weight.” with remove_initializer_from_input.py,
I’m unable to correctly classify images presented to the camera.
I substituted the TAO onnx model with the “resnet18-v1-7” model from onnx, and my program works fine. It classifies everything I present to it.
I checked the model’s input:
input_1, Shape: [‘batch’, 3, 224, 224]
and the image format I’m passing to it.
(np.shape(frame_normalized)
1, 3, 224, 224)
So I’m wondering if the problem is known, and what solution I could implement.
Thank’s
Sylvain Bolduc
Hi @sylvain.bolduc I’ve moved this to the Tao forum so the right team can help you out.
Best,
Sophie
1 Like
Which notebook did you run? Can you share logs or .ipynb? The notebook should run smoothly instead of error.
Hello,
I created a share point with the fully executed notebook, along with all the useful files.
TAO_classification
I understand that the model gives a slightly higher than 50% correct answer in the evaluation. But when I try to use it, it only gives one answer. Everything is a dog. But when I use the Resnet model and its classes, the little program works well. The TAO philosophy appeals to me a lot because I’m not an AI expert, but I’d like to use it for simple applications, as does the idea of working with pre-trained networks and finetuning them. Thank you.