Comments (1)
In order to do that, you can check the way we extract image and recipe embeddings in test.py and then run rank.py. If you want to perform this multiple times, I recommend you to extract all the recipe embeddings first and save them. Then every time you want to get the best match in terms of recipe given an image, you just need to extract the image embedding and computing the distance against each recipe embedding you saved.
from im2recipe-pytorch.
Related Issues (20)
- ONNX Version? HOT 1
- does the repository contains instructions to train the model on skip-instructions. HOT 1
- training on skip-instructions/only ingredients HOT 1
- food101_classes_renamed.txt HOT 3
- IndexError on attempt to run pertained model
- I got Cuda Error when I run test.py ,And My soft environment is ubuntu16.04 python3.7 cpu HOT 3
- Index error when running test HOT 1
- Registration to access dataset results in error HOT 4
- DB Download link not working HOT 11
- How can I test pretrained model? HOT 2
- Dataset Inaccessible, error mentions missing email? HOT 1
- `TypeError: file must have 'read' and 'readline' attributes` when loading training data
- Extract Word Embedding for a single recipe
- Pretrained model link broken HOT 1
- Error installing torchwordemb
- setup.py
- Pre-trained model can't not find test_lmdb HOT 1
- im2recipe-Pytorch issue HOT 1
- "recipe1M" dataset HOT 3
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from im2recipe-pytorch.