Comments (12)
Sure, we'll try to provide as soon as possible, probably tomorrow :)
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Hello,
I was busy last week, thanks for waiting! The nearest neighbors and evaluation files are here.
You can find the datastores on HF.
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Hi,
Those ids correspond to the ids of the images. As in your example, id 67 can be found in captions_val2014_new.json
:
{"id": 67, "width": 0, "height": 0, "file_name": "1018148011.jpg"... }
This means the id 67 corresponds to the Flickr30k image "1018148011.jpg".
All the validation images and test images are in the captions_val2014_new.json
. So please ignore the captions_test2014_new
.
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Hi @dongwhfdyer, glad to hear you've been able to reproduce the COCO-index results. @RitaRamo and I will follow up on your main request shortly.
For now I can clarify that datastore/coco_index_captions.json
is just a file containing the captions (the actual text) associated with datastore/coco_index
(which only contains vectors). You can see here that both of these files are created with reference to just the COCO dataset.
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That's great! And will you release the augmented datastore in the future?
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@dongwhfdyer the easiest way to reproduce the results from the table above would be for us to share the retrieved neighbors with you (the equivalent to data/retrieved_caps_resnet50x64.json
for each datastore and dataset combination in the table).
If you need the actual index for each of the datastore configurations, we can also provide that, although some of the files will be quite large, so we have to see where we can host them for sharing.
If the trouble you are facing is just with the actual evaluation script (i.e. with adapting the coco-captions metric computation to the other datasets), let us know and we'll share the relevant files with you.
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Thank you! I think I need both. 😄
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Just to make sure, of the three things I mentioned: nearest neighbors, indexes, and evaluation files, which ones do you need?
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I need nearst neighbors, indexes, and evaluation files.
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@RitaRamo
Hello,
Thank you for your fantastic work!
I would appreciate it if you could share nearest neighbors, indexes, and evaluation files with me.
from smallcap.
Thank you a lot!! We are trying to reproduce your work on other datasets now. ☺
But when it comes to flick30k, I feel rather confused about its nns file (setup_in_domain.json
, setup_in_domain_web.json
, etc) and its index file(captions_test2014_new.json
,captions_val2014_new.json
). Their indexes don't match with each other. For example, for image files listed in captions_test2014_new.json
, I can't find their corresponding retrieved captions, which I can easily do that on coco datasets with your provided dataset_coco.json
and retrieved_caps_resnet50x64.json
.
Or, can you explain what these indexes that I highlighted refers to in setup_in_domain.json
?
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Hi~ Thanks for sharing data!
Could you share the msrvtt frame mentioned in captions_val2014_new.json? or pseudo code?
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Related Issues (18)
- VisionEncoderDecoderModel not found HOT 1
- train_chunk_ids.json not found
- No retrieve_caps function in retrieve_caps.py HOT 2
- Why there is no code for evaluation?
- About Seq2SeqTrainer in train.py HOT 1
- About data leakeage when using COCO captions as datastore HOT 1
- sorry, wrong attempt, please delete the issue
- how long is "retrieving neighors" gonna take? HOT 1
- how to use 'opt' or 'xglm' HOT 1
- problems encountered when evaluating SPICE HOT 3
- Stanford models for computing SPICE HOT 2
- How to get hidden_state value? HOT 2
- 1
- How to create my own datastore
- Questions about TrainDataset (src/utils.py L54) HOT 1
- Some notes about Transformers integration
- Possible errors in the source code /file: train.py; function: main
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