Hi group, the work I would like to do for this great course is a food dish calories calculation, I still have no idea how to calculate the volume and size in a flat image but that will be for later. Right now I want to use what I learned in Lesson 1 for the recognition of dishes, and I have a problem.
I have a dataset food-101, The data is organized as follows:
- food-101
- images
- fried-calamari
- 10896.jpg
- …
- fried rice
- 17569.jpg
- …
- fried-calamari
- meta
- train.txt => [“156743.jpg”, “564378.jpg” …]
- test.txt => [“176743.jpg”, “984378.jpg” …]
- images
I was able to change the names (I know, for you it’s very easy), now I don’t know how to organize the folders. At first I thought:
os.makedirs(’~/food-101/train’, exist_ok=True)
os.makedirs(’~/food-101/valid’, exist_ok=True)
os.makedirs(’~/food-101/test’, exist_ok=True)
and in each of these folders a for to create a folder for each of the food dishes .
and then transfer each image to those folders using the files in the meta folder, but I know that there must be a better way for the network to accept the data, any suggestions?, you would be very helpful, thank you.
and another thing, I have the file train. txt, I can split the names in training and validation from the file itself or I must upload the images first.