Ciro Santilli @cirosantilli 40

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activatedgeek/LeNet-5 use ONNX for inference Updated 2025-07-16

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Now let's try and use the trained ONNX file for inference on some manually drawn images on GIMP:

Figure 1.
Number 9 drawn with mouse on GIMP by Ciro Santilli (2023)
.

Note that:

the images must be drawn with white on black. If you use black on white, it the accuracy becomes terrible. This is a good very example of brittleness in AI systems!
images must be converted to 32x32 for lenet.onnx, as that is what training was done on. The training step converted the 28x28 images to 32x32 as the first thing it does before training even starts

We can try the code adapted from thenewstack.io/tutorial-using-a-pre-trained-onnx-model-for-inferencing/ at lenet/infer.py:

cd lenet
cp ~/git/LeNet-5/lenet.onnx .
wget -O 9.png https://raw.githubusercontent.com/cirosantilli/media/master/Digit_9_hand_drawn_by_Ciro_Santilli_on_GIMP_with_mouse_white_on_black.png
./infer.py 9.png

and it works pretty well! The program outputs:

as desired.

We can also try with images directly from Extract MNIST images.

infer_mnist.py lenet.onnx mnist_png/out/testing/1/*.png

and the accuracy is great as expected.

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Activation energy Updated 2025-07-16

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Perl HOWTO Updated 2025-07-16

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Gift vs Grant vs Contract in the United Kingdom Updated 2025-07-16

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OpenClassrooms Updated 2025-07-16

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openclassrooms.com/

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Monero mining Updated 2025-11-05

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JPEG file signature Updated 2025-07-16

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Functional Analysis course of the University of Oxford Updated 2025-07-16

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Schrödinger equation for a one dimensional particle Updated 2025-07-16

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We select for the general Equation "Schrodinger equation":

$x = x$ , the linear cartesian coordinate in the x direction
$\hat{H} = - \frac{ℏ ^{2}}{2 m} \frac{\partial ^{2}}{\partial x ^{2}} + V (x, t)$ , which analogous to the sum of kinetic and potential energy in classical mechanics