- Identify meaningful categories/groups of categories whose images can be used for training T242969
- Download images for categories
- Test accuracy and performance of image classifiers (pretrained or trained from scratch) for various sets of categories T242970
- Report on results in terms of accuracy and GPU performances T242970
- [Optional] test different DL architectures
Description
Description
| Status | Subtype | Assigned | Task | ||
|---|---|---|---|---|---|
| Open | Miriam | T155538 General image classifier for commons | |||
| Open | Miriam | T215413 Image Classification Research and Development | |||
| Invalid | Miriam | T228441 Design a pipeline for image classification | |||
| Resolved | Miriam | T242229 Test the feasibility of a classifier trained on Commons categories | |||
| Resolved | Miriam | T242969 A list of meaningful Commons Categories whose images can be used to train image classifiers | |||
| Resolved | Miriam | T242970 A set of prototypes of image classifiers trained on images from Commons Categories | |||
| Resolved | Miriam | T242971 A report on accuracy and performance of the classification models |
Event Timeline
Comment Actions
Weekly update:
- downloaded the list of coco-stuff classes which include highly generic categories of people, animals, and things which exist in the visual world: https://github.com/nightrome/cocostuff
- downloaded the list of categories in Commons, with the counts of the number of images per categories.
- to create the initial seed of categories we want to consider for object categorization in Commons, I computed fasttext vectors on both COCO categories and Commons Categories, and I am checking what are the commons categories that we can use to represent COCO categories.
Comment Actions
Report available here: https://meta.wikimedia.org/wiki/Research:Prototypes_of_Image_Classifiers_Trained_on_Commons_Categories
It highlights milestones and areas of improvement to design our own in-house image classifiers. Reports on accuracy and GPU performance. Links to some qualitative results of classification on a new set of images..