• Divide students in a group of 5 and choose 5 objects.(lets say: leaves, flowers, plants, trees, animals).
• Assign 4 labels to each group. Each group should click 20 photos of each label. (for instance: group 1 get 4 labels: leaves, flowers, trees, animals. Group 1 together should click 80 pictures in total of the 4 labels defined).
• Finally, ask every student of the group to try to click a unique as possible photo of the 5th label (unassigned label)(Now all the kids of group one should try to click a unique photo of plants)
• Train the model on 80 images and let the model predict any 5 images. The group which produces the images which remains undetected or get the lowest sum of confidence wins for clicking the most unique photos.

The outline

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