Comments (1)
I can follow the format in hubconf.py. Is the backbone for the LVIS model also a Resnet101? I'm making something like this, however it is throwing errors:
`
def mdetr_resnet101_lvis(pretrained=False, return_postprocessor=False):
model = _make_detr("resnet101")
if pretrained:
checkpoint = torch.hub.load_state_dict_from_url(
url="https://zenodo.org/record/4721981/files/lvis10_checkpoint.pth",
map_location="cpu",
check_hash=True,
)
model.load_state_dict(checkpoint["model"])
if return_postprocessor:
return model, PostProcess()
return model
`
from mdetr.
Related Issues (20)
- Can you provide the final_vg json files?
- colab sandbox is deactivated HOT 1
- Pre-training question
- Pre-trained model gives nan prediction in Colab HOT 7
- Seems cannot verify the existence of objects HOT 2
- How to define "Negative Tokens" ? HOT 1
- Bbox assertion error when using ENB models (eval & pretrain as well): assert (boxes1[:, 2:] >= boxes1[:, :2]).all() HOT 8
- how to define positive tokens? HOT 1
- ValueError: char_to_token() is not available when using Python based tokenizers HOT 1
- How to generate "tokens_negative" and "tokens_positive" when we convert our own dataset into mdetr annotations? HOT 1
- finetune have bug!!ValueError: char_to_token() is not available when using Python based tokenizers HOT 3
- Cannot find finetune_phrasecut_miniv.json HOT 1
- [Colab Error] InvalidVersion: Invalid version: '0.10.1,<0.11' HOT 2
- With the increase of MDETR training time, GPU memory occupation keeps increasing. After several epoch training, memory explodes,i.e. OOM, out of memory. HOT 1
- issue #44 "I guess its uncompleted project so I gave up this essay" HOT 1
- I would like to know how to use the model in clevr-ref+.
- Weird results while evaluating & reproducing ENB3 model on PhraseCut
- How to decode GQA evaluation results HOT 1
- run
- CLEVR-REF+ training
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from mdetr.