Semaine 2 (Week 2) samedi

~ samedi ~

Textons

Code from online ran in Matlab, but not sure how to get anything out of the resulting matrices to show visually on the image so that I can get the meaning out of it. Looking into code for OpenCV.

OpenCV surprisingly doesn't support loading GIF directly. Found code online to load it, but has artifacts when I just load and store back the image. Decided to use ImageMagick and some shell script to convert the GIF image from JSEG back to JPG, then load into OpenCV matrix. Much easier, since my shell script is already written for JSEG. Just need 1 line of code for using ImageMagick. 


Data
So... although we had thousands of images in a some dozens of food categories automatically queried and downloaded from Flickr, they are quite noisy. We need to clean them.

A snapshot of the categories currently downloaded:
bento, bibimbap, burrito, chowMein, crepes, DimSum, dumpling, fishAndchips, gyro, kebab, macaron, onigiri, PekingDuck, pizza, potAufeu, ramen, redCurry, sashimi, shrimpTempura, spaghetti, steakFrites, stirfry, stollen, sushi, taco, teriyaki, tiramisu, udon, wonton, yakisoba

Currently only working on a subset of sushi images for initial testing, because it has many segmentation regions and ingredients to look for.

TODO: Separate sushi data into easy, medium and hard tests.

Use the easy ones for testing first. They shouldn't have too many segmented sections, so that I can manually label the segments and make the *.labels files

TODO: Pick out 10 images, and hand label those.


Machine Learning

When training the ingredients:

Q: Should we find images with just that ingredient on a single image, and train using those images, or can we hand label the segmented regions, and just train using the regions?

Q: If I label the plate and the table as "unnecessary" and just throw away, or just NOT label them at all. Can I just use a classifier that doesn't always pick one possible, but sees that if a pattern is like nothing it has seen, then discard that data automatically?

When training the cuisines:

Will obviously use the whole image