Skip to main content

helps to analyse integrated circuit die images (for example from siliconpr0n.org) with the help of ai.

Project description

Installation

Install from source:

pip install --upgrade .

Install from pip:

pip install --upgrade silicon-analyser

Information

Code will use your graphic card for acceleration. (but only if correct pytorch is installed, see "Additional info" below)

Frameworks/Libraries used:

Small example

  • start
  • select image
  • add grid
  • press mouse down on image and drag your rectangle for your grid
  • adjust x,y,cols,rows,width,height manualy to fit
  • add label (while grid is selected)
    • give it a random name
  • with that label selected, select cells for that label (for example cells that mark a "1")
  • select grid (for example "grid_0" again)
  • add another label (while grid is selected)
    • give it a random name
  • with that label selected, select cells for that label (for example cells that mark a "0")
  • with enough "1" and "0" labels drawn, click the "Compute" button
    • ai will find images in the grid that have the same properties
    • click "stop" once the results are satisfied
      • maximum for "acc" and "val_acc" is 1.00, the closer you are to those values, the better are the results
      • results depend on many factors:
        • the amount of cells you selected
        • how good your grid matches the current image
        • the quality of your image
        • ...
      • "acc" stands for "accuracy", "val" for "validation"
  • found ai-cells will be drawn green

Additional info

  • you might need to install cuda-specific PyTorch for accelerated computing
    • check your graphic driver version for compatible cuda version!

Keys

  • Use up/down/left/right to navigate
  • Hold shift to move faster
  • Scroll-wheel to zoom out
  • Click on minimap to get directly to a position
  • Right click on tree-items (left navigation menu) for additional options

image

TODO

  • show loading screen on start (pytorch with cuda support takes a bit to load)
  • option to calculate/classify by decision tree
  • auto-compute to calculate in background while you are selecting new cells for your labels
  • ai-model configuration
  • possibility to rotate grid
  • maybe store your model on a public place? (for others to use)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

silicon_analyser-1.0.8.tar.gz (26.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

silicon_analyser-1.0.8-py3-none-any.whl (32.9 kB view details)

Uploaded Python 3

File details

Details for the file silicon_analyser-1.0.8.tar.gz.

File metadata

  • Download URL: silicon_analyser-1.0.8.tar.gz
  • Upload date:
  • Size: 26.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.11.4

File hashes

Hashes for silicon_analyser-1.0.8.tar.gz
Algorithm Hash digest
SHA256 1fe95e2be5a5aecd2a049b15a105421ce759f1fff94dfb0a9ef6b5396f8511d3
MD5 b5c3a13645f3ca5cc4e7788126af7e68
BLAKE2b-256 f7e8fff64966ef8d385989b9d317837fb61c8888709181b7dfa8ca5b32ce5f3f

See more details on using hashes here.

File details

Details for the file silicon_analyser-1.0.8-py3-none-any.whl.

File metadata

File hashes

Hashes for silicon_analyser-1.0.8-py3-none-any.whl
Algorithm Hash digest
SHA256 2a3a938b3c6c9ae45d5b251182beb9afeedfc30b2be2bf98028a514d9a8c5ef6
MD5 88dbe790049f913af4201077e262e6ae
BLAKE2b-256 d07c07212278666749b87555a708193cfff820cfb83b4fbef55647de8a09bde0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page