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Your app kinda sucks now, but the detection is great. You could also do food identification as a service... I'm trying to use fatsecret/myfitnesspal for counti

by swah 10y ago

Your app kinda sucks now, but the detection is great. You could also do food identification as a service... I'm trying to use fatsecret/myfitnesspal for counting calories. Something like this could make it much easier! To me, a better workflow would be: take pictures of everything you eat and classify later (at night, maybe on the PC). Of course, this software would simplify the classification, the user would only fix any errors and adjust sizes. This workflow would be well suited to your app, which operates on a server? (my understanding). Congrats, I understand the relevance of AI for simple apps now ;)

subcosmos 10y ago
Ive been thinking of that 'classify later' workflow. I think of it kind of like facebooks photo tagging, and it might even be better as web app that you get email reminders for to complete entries. It would also work nicely for background geolocation services, since if the photograph was taken near a restaurant the service could extrapolate those things. Anyways, I might make this project opensource and build a nice community around it. Depends on whether or not that model would best support my research goals.
- swah 10y ago
  Great! And think about using the new data from the users to improve the system (that should probably be in your terms). How well does it work on plates with multiple foods "kinda mixed"?
  - subcosmos 10y ago
    Thats another huge design challenge Ive faced, specifically because it really complicates the data model and UI. Implicitly, since the app presents a list of possible identified foods, and the user can easily check multiple boxes, thats straightforward, but then having the app pull each of those items AND ask the user to estimate portions for each .... gets a little messy. So I put that complexity off for v2. That use case in particular would also be best off for a web-interface, I think.
    - swah 10y ago
      What about dividing the whole plate weight by the foods detected? (in Brazil there are many restaurants where you pay by weight, thats why I'm suggesting..)
      - subcosmos 10y ago
        Theres a company in the bay area trying this approach actually! They look really interesting: https://getsmartplate.com/ https://getsmartplate.com/ Cant compete with that awesomesauce!

by swah 10y ago

subcosmos 10y ago

Ive been thinking of that 'classify later' workflow. I think of it kind of like facebooks photo tagging, and it might even be better as web app that you get email reminders for to complete entries. It would also work nicely for background geolocation services, since if the photograph was taken near a restaurant the service could extrapolate those things. Anyways, I might make this project opensource and build a nice community around it. Depends on whether or not that model would best support my research goals.

swah 10y ago
Great! And think about using the new data from the users to improve the system (that should probably be in your terms). How well does it work on plates with multiple foods "kinda mixed"?
- subcosmos 10y ago
  Thats another huge design challenge Ive faced, specifically because it really complicates the data model and UI. Implicitly, since the app presents a list of possible identified foods, and the user can easily check multiple boxes, thats straightforward, but then having the app pull each of those items AND ask the user to estimate portions for each .... gets a little messy. So I put that complexity off for v2. That use case in particular would also be best off for a web-interface, I think.
  - swah 10y ago
    What about dividing the whole plate weight by the foods detected? (in Brazil there are many restaurants where you pay by weight, thats why I'm suggesting..)
    - subcosmos 10y ago
      Theres a company in the bay area trying this approach actually! They look really interesting: https://getsmartplate.com/ https://getsmartplate.com/ Cant compete with that awesomesauce!