Comments (7)
same question... ^_^
from diffusiondet.
Hello, it takes about 39 hours on 8xA100 for DiffusionDet-COCO-Res50.
from diffusiondet.
Hello, it takes about 39 hours on 8xA100 for DiffusionDet-COCO-Res50.
Hi may I know the inference time of each image? for example on 640x640x3 image
from diffusiondet.
Hi @leemengwei ,
We report latency in Table 3 (f) https://arxiv.org/pdf/2211.09788.pdf.
Wish this table could solve your concern.
from diffusiondet.
@ShoufaChen thanks4 reply
Yet as metioned in paper: "The run time is evaluated on a single NVIDIA A100 GPU with a mini-batch size of 1" which achieves about 30fps .... I can say this is not yet something for everyone to use on PC ...
from diffusiondet.
Hello, it takes about 39 hours on 8xA100 for DiffusionDet-COCO-Res50.
Thanks for your information.
from diffusiondet.
Hello, it takes about 39 hours on 8xA100 for DiffusionDet-COCO-Res50.
Hi @ShoufaChen ,
What is the estimated training time for R50 LVIS model? Thanks
from diffusiondet.
Related Issues (20)
- ap=0
- why the dataset only split to train and test? HOT 2
- Detectron's version of cuda
- Questions on box renewal
- 使用提供的训练模型做eval只有32mAP
- train on my datasets,adjust the value of thread
- 复现问题
- RuntimeError: nvrtc: error: invalid value for --gpu-architecture (-arch) ON RTX4090
- random seed 为什么固定了随机种子和参数后,模型的预测框测试出来都一样
- coco dataset
- pre-trained models
- AP is nan
- evaluator
- Used Multi gpus but takes same time with 1 gpu training
- bbox=0
- Too many boxes when using demo.py with --video-input video.mp4
- why the eval result is 0?
- 为什么推理结果为0?
- ddim中对于time生成的程序语句似乎不对?
- Prepare datasets HOT 1
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