Automated Card Grading - Surface

[Goudey]

Originally Posted by kevinlenane

Attachment 417880

Here is the perspective normalization I was referencing for those who are interested.... basically this ensures that we have the right angle on the card to evaluate appropriately. Otherwise minor changes in camera angle would produce dramatically unacceptable grades...

Leon who else is working on this? Would love to compare notes

Hi Kevin, question for you: how does your normalization not affect the pixel vectors of the original scan? Given it probably affects the values you have for raw images ( assuming you're not reducing dimensions). Question 2: how do you deal with different size/complexity of scans to "grade"? seems like they could be all different size vectors. Super cool work

[bnorth]

Great video. I wish you the best and hope to see this being used ASAP to grade cards.

[JollyElm]

Here's a question. Is your scanning effective if a card is already graded and sitting in a slab? Because it would be really cool if you were able to scan 10, 20, 50, whatever, different graded examples of the very same card where each received the exact same grade (say PSA 7), and were able to tell which ones were 'accurately' (for lack of a better word) graded and which were not. It'd be a helluva interesting undertaking. Of course, you would need a lot of volunteers to send you their cards.

[Lobo Aullando]

Originally Posted by JollyElm

Here's a question. Is your scanning effective if a card is already graded and sitting in a slab? Because it would be really cool if you were able to scan 10, 20, 50, whatever, different graded examples of the very same card where each received the exact same grade (say PSA 7), and were able to tell which ones were 'accurately' (for lack of a better word) graded and which were not. It'd be a helluva interesting undertaking. Of course, you would need a lot of volunteers to send you their cards.

Everybody loves a distribution! The big question is skewed-left or skewed-right.

[kevinlenane]

Hey all - so we've managed to get the remaining sub-grades implemented and we have it working well in head-to-heads with human graders within an average of .23 their sub-grade averages. Next step is building out additional set support and modern set support before building the API and/or mobile app.

https://www.youtube.com/watch?v=qXSkoFBvcDY

Definitely getting exciting - we'll have some additional unique features including visual sub-grade justification which will put to rest any accuracy questions. I dont have the business model or distribution figured out just yet but we have some strong first moves in mind.

[swarmee]

Nice update. Interested to see where this goes. Please don't let someone buy the technology just to bury it.

[mattglet]

The overlay feedback is going to be, as the kids say, lit.

Very exciting.

[hcv123]

Figured it was time to pop this thread to the top.

Congratulations Kevin!