akhundelar

5 ms·

1. 1.▲
   by akhundelar 8mo ago

   Not a duckdb user, but I use polars a lot (mentioned in the article). Depends on your definition of medium sized, but for tables of hundreds of thousands of rows and ~30 columns, these tools are fast enough to run queries instantly or near
2. 2.▲
   by akhundelar 5y ago

   Interesting, I did not encounter such discrepancies in my work with these tools. There could be multiple reasons for the degraded performance: - Are we comparing apples to apples here (heh), e.g. ResNet-50 vs ResNet-50? - Was the ONNX model
3. 3.▲
   by akhundelar 5y ago

   > It is fairly trivial to generate invisible noise that makes an input image get an entirely different hash. What I had in mind when referring to 'basic evasion' was 'cropping or rotating', as per your original commen
4. 4.▲
   by akhundelar 5y ago

   ONNX != onnxjs ONNX is a representation format for ML models (mostly neural networks). onnxjs is a just a browser runtime for ONNX models. While it may be true that onnxjs is neglected, please note that the 'main' runtime, onnxrun
5. 5.▲
   by akhundelar 5y ago

   As far as my understanding goes, you can apply a distance measure on the (neural)hashes of the input image and the reference image. A proximity threshold will determine if it's a variant of the original image or not. So, it should prob