Closed qiaogh97 closed 3 years ago
Hey @qiao1025566574 , I'm glad you liked it!
That's a good question! I remember that I had put a comment to explain why n * 5 but I don't know why it's not there; my fault!
The reason is that the dataset has 5 captions for each image; so when computing the similarities, every 5 entries in dot_similarity point to same image. In order to show n different images in the plot, I'm skipping every 5 entry with [::5]
in the next line.
I admit that I did this not optimally. A better way was to only put the unique images in the CSV file for visualization purposes.
I hope this explains that part.
Great!I know it! I'm pleasantly surprised by your timely reply, thanks a lot. I will close this issue.
Hi @moein-shariatnia ! Thank you for your contribution! I really enjoy your article. There is something I can't understand about this code https://github.com/moein-shariatnia/OpenAI-CLIP/blob/8fda94c1f85f956bdadb2e796938356fd79ae336/inference.py#L46 I mean if you want to choose the top5, why not
torch.topk(dot_similarity.squeeze(0), 5)
?