Changes

=== Summary ===

=== Summary ===

[https://dataforgood.fr/ DataForGood] is an association that mobilize tech to help citizen projects. We are part of [https://dataforgood.fr/projects/tags/saison-10 season #10], this is our 4th season.

[https://dataforgood.fr/ DataForGood] is a French "association" that mobilizes tech to help citizen projects. We are part of [https://dataforgood.fr/projects/tags/saison-10 season #10], this is our 4th season.

Main focus this year is on using machine learning to automatically categorize products so as to enable computing Nutri-Score and Éco-Score.

Main focus this year is on using machine learning to automatically categorize products so as to enable computing Nutri-Score and Éco-Score.

'''Expected outcomes''': Have a new machine learning model, ready to deploy in production:

'''Expected outcomes''': Have a new machine learning model, ready to deploy in production:

* That use more features to predict category: OCR data, nutritional information, eventually images or any feature

* That uses more features to predict category: OCR data, nutritional information, eventually images or any feature.

* Precision should be very high to be able to apply category automatically but the model should use it's confidence to ask for user when needed

* Precision should be very high to be able to apply category automatically but the model should use its confidence to ask the user whenever needed.

'''Impact:''' augment massively the number of Eco-Score and Nutri-Score we are able to provide on the platform.

'''Impact:''' massively increase the number of Eco-Scores and Nutri-Scores we are able to provide on the Open Food Facts platform.

Categorization is also important in many way, for example to compare nutrition data with other products of same category (rank among category).

Categorization is also important in many ways, for example to compare nutrition data with other products of same category (rank within a category).

'''Timeline''':

'''Timeline''':

* 2022-03-12 launch at Data for good launch event

* 2022-03-12: Data 4 Good kickoff event

* 2022-03-16 project kickoff (first working session)

* 2022-03-16: Actual project kickoff (first working session)

* 2022-06-12 theoretical end of the project

* 2022-06-12: Planned end of the project (Data 4 Good Demo Day)

=== Resources / Contributing ===

=== Resources / Contributing ===

The weekly meeting for this project is every Wednesday 20.00. We have a meeting room at https://meet.jit.si/DFG-OPENFOODFACTS

The weekly meeting for this project is Wednesdays at 20.00 (French time). We have a meeting room at https://meet.jit.si/DFG-OPENFOODFACTS

You should also join data-for-good slack. To be invited, use https://dataforgood.fr/join/

You should also join the Open Food Facts and Data 4 Good slacks. To be invited, use https://dataforgood.fr/join/ and https://slack.openfoodfacts.org

'''Main repos'''

'''Main GitHub repositories'''

* [https://github.com/openfoodfacts/robotoff/ robotoff]: Our program that handles predictions / insights: good to read : https://openfoodfacts.github.io/robotoff/introduction/architecture/

* [https://github.com/openfoodfacts/robotoff/ robotoff]: Robotoff, our program that handles predictions / insights

* [https://github.com/openfoodfacts/robotoff-ann/ robotoff-ann] is a complement to robotoff that focus on logo detection and embedding (we use nearest neighbors to classify logos)  

  * good to read : https://openfoodfacts.github.io/robotoff/introduction/architecture/

* last training of category model (using only title and ingredients): https://github.com/kulizhsy/off-category-classification

* [https://github.com/openfoodfacts/robotoff-ann/ robotoff-ann] is a complement to robotoff that focuses on logo detection and embedding (we use nearest neighbors to classify logos)  

* Last training of category model (using only title and ingredients as features): https://github.com/kulizhsy/off-category-classification

* All trained models are published as "releases" on https://github.com/openfoodfacts/openfoodfacts-ai

* All trained models are published as "releases" on https://github.com/openfoodfacts/openfoodfacts-ai

* [https://openfoodfacts.github.io/api-documentation/ openfoodfacts API documentation]

* [https://openfoodfacts.github.io/api-documentation/ Open Food Facts API documentation]

=== Archives ===

=== Archives ===

* [https://docs.google.com/presentation/d/1fMN4di6AN1vz4sC3HYsA1PTya0mDGJYZ9htQYyqkLZQ/edit Data4Good launch presentation (google docs)]

* [https://docs.google.com/presentation/d/1fMN4di6AN1vz4sC3HYsA1PTya0mDGJYZ9htQYyqkLZQ/edit Data4Good launch presentation (Google Docs)]

[[Category:Project]]

[[Category:Project]]

[[Category:Robotoff]]

[[Category:Robotoff]]