Comments (12)
We have released the focal-large checkpoint and config, feel free to play with it.
from segment-everything-everywhere-all-at-once.
As you may noticed, this one is still training. Expected 1-2 days to be finished without interrupt.
from segment-everything-everywhere-all-at-once.
As you may noticed, this one is still training. Expected 1-2 days to be finished without interrupt.
Thanks for letting me know. Looking forward to it!
from segment-everything-everywhere-all-at-once.
Hi @MaureenZOU! Is there any chance that you guys will release the large model as well? :)
from segment-everything-everywhere-all-at-once.
The checkpoint is different, you could see the RED highlight in the HTML webpage of your running table. We release seem_focalt_v1.pt and the demo we are running is on large model : )
from segment-everything-everywhere-all-at-once.
Same question. Is there an estimated time for the release of your larger models? Thanks!
from segment-everything-everywhere-all-at-once.
Same question. Is there an estimated time for the release of your larger models? Thanks!
from segment-everything-everywhere-all-at-once.
I am running a large model with publishable checkpoint. But expected to be slightly worse than the demo checkpoint.
from segment-everything-everywhere-all-at-once.
I am running a large model with publishable checkpoint. But expected to be slightly worse than the demo checkpoint.
Thanks for your information! Is this model performing better than the released tiny model?
from segment-everything-everywhere-all-at-once.
That would be better than focalt checkpoint. It is trained with in21k pretrained focal-large-xdecoder.
from segment-everything-everywhere-all-at-once.
That would be better than focalt checkpoint. It is trained with in21k pretrained focal-large.
Great! Could you please release this one first? Thanks a lot for your help!
from segment-everything-everywhere-all-at-once.
We have released the focal-large checkpoint and config, feel free to play with it.
Thanks a lot for your prompt help!
from segment-everything-everywhere-all-at-once.
Related Issues (20)
- The results of online and local demos are inconsistent. HOT 1
- Actual batch size with multiple GPUs
- Support for video segmentation demo without referring image HOT 1
- bbox prediction
- How to build caption_class_similarity.pth?
- Multi-object interaction support
- Multi-gpu training HOT 1
- what does `grounding_hash ` mean?
- Scripts for Interactive Validation on COCO HOT 4
- Local inference for an image given point prompt coordinates HOT 2
- What is the relationship with Semantic-SAM?
- The demo website can't be accessed HOT 2
- Bug when getting the neg_mask HOT 1
- When I was running "pip install -r assets/requirements/requirements.txt", I got the following errors. Could you please tell me what should I do? HOT 5
- ValueError: Unknown scheme for proxy URL URL('socks://localhost:10808/') HOT 1
- The demo website can't be accessed HOT 2
- How to change the size of the training set?
- GPU Out of Memory Issue HOT 5
- Config Issue - Load pretrained sam_vit_l_0b3195.pth
- How to train your own dataset HOT 5
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from segment-everything-everywhere-all-at-once.