3 ms·

I stopped reading when I got to the camera resolution... 324x324 px. Are they serious? Either it should run at 1k fps or the board should cost $10. Also the wh

I stopped reading when I got to the camera resolution... 324x324 px. Are they serious? Either it should run at 1k fps or the board should cost $10. Also the whole Edge TPU, the implied promise was that this is a beginning. That there will be more powerfull "TPUs" available in future as well as the current Edge TPU was supposed to be available as a generic electronic component one can buy and incorporate in ones own designs for cheap. I never saw one in stock.

rgovostes 3y ago
Many convolutional neural networks for image classification work on 299x299 inputs. If it had a higher resolution camera, it would just need to scale down every frame. You can see input sizes of pre-trained models from Google: https://coral.ai/models/image-classification/ https://coral.ai/models/image-classification/
- mkl 3y ago
  Most listed there are even smaller, 224×224px. These are models for Coral, though, right? It also says "These are not production-quality models; they are for demonstration purposes only."; the resolution may be part of the reason for that.
  - rgovostes 3y ago
    The CNN architectures are really designed to operate on such small inputs, even if you run them on RTX 4090s. It makes sense: even with 224x224 pixels you would find it easy to identify the subject of an image. Having a 50MP image of a chair doesn't really help you figure out what it is, and even makes it harder if you're only looking at one zoomed in region of the image at a time. "Not production-quality models" might refer to: Training was not done for as many epochs as you might want to achieve peak accuracy, or different quantization methods might yield better performance, etc. Or, it's just a disclaimer that if you decide to sell a product using one of these models, don't blame them if it is bad at detecting hot dog vs not hot dog.

3 ms·

I stopped reading when I got to the camera resolution... 324x324 px. Are they serious? Either it should run at 1k fps or the board should cost $10. Also the wh

by Roark66 3y ago

rgovostes 3y ago
Many convolutional neural networks for image classification work on 299x299 inputs. If it had a higher resolution camera, it would just need to scale down every frame. You can see input sizes of pre-trained models from Google: https://coral.ai/models/image-classification/ https://coral.ai/models/image-classification/
- mkl 3y ago
  Most listed there are even smaller, 224×224px. These are models for Coral, though, right? It also says "These are not production-quality models; they are for demonstration purposes only."; the resolution may be part of the reason for that.
  - rgovostes 3y ago
    The CNN architectures are really designed to operate on such small inputs, even if you run them on RTX 4090s. It makes sense: even with 224x224 pixels you would find it easy to identify the subject of an image. Having a 50MP image of a chair doesn't really help you figure out what it is, and even makes it harder if you're only looking at one zoomed in region of the image at a time. "Not production-quality models" might refer to: Training was not done for as many epochs as you might want to achieve peak accuracy, or different quantization methods might yield better performance, etc. Or, it's just a disclaimer that if you decide to sell a product using one of these models, don't blame them if it is bad at detecting hot dog vs not hot dog.