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I am trying to give text inputs for the image_demo, however for some reason when I use 'pedestrian' as a text input it is not recognised as a noun_phrase.
Example:
```
python demo/image_demo.py i…
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Hi, 感谢你们开创性的工作!我注意到 CogCom 通过连接 grounding dino 实现 grouding,请问怎么控制模型输出的 bounding box 数量呢,目前模型只输出 top1 的 bounding box
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I am working to retrain mm_grounding_dino with my custom dataset.
The training process works fine
```
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.784
Average Precisi…
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Hi everyone,
I was testing Grounding Dino with SwinB backbone and I found that, unexpectedly, it detects less objects than Grounding Dino SwinT. For example, when asking for "light bulb", G-DINO Sw…
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Hi does this work with cuda? I'm using:
https://github.com/HumanSignal/label-studio-ml-backend/tree/master/label_studio_ml/examples/grounding_dino
and getting the following:
`label-studio-ml-…
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我使用grounded_sam_simple_demo.py进行测试,配置如下
GROUNDING_DINO_CONFIG_PATH = "GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py"
GROUNDING_DINO_CHECKPOINT_PATH = "./groundingdino_swint_ogc.pth"
…
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As described in the title, if setting the device to "cuda:2" there are no results by dino.
Still not sure where the bug occurs.
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我使用实例代码:
python demo/image_demo.py demo/demo.jpg configs/grounding_dino/grounding_dino_swin-t_pretrain_obj365_goldg_cap4m.py --weights /mnt/sh_flex_storage/home/wushuche/mnist-fastapi-aio-tr…
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首先感谢你们的工作,按照你们提供的方式,在自有数据集上进行微调,获得了超预期的效果。
我有一个疑问关于:mm_grounding_dino获得伪标签后的训练。
在“模型自训练伪标签迭代生成和优化 pipeline”中的第3条:“在得到伪标签后,你可以混合一些预训练数据联合进行继续预训练,提升模型在当前数据集上的性能,然后重新运行 2 步骤,得到更准确的伪标签,如此循环迭代即可”。
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Hello,
I am trying to replicate the performance of Grounding DINO on COCO dataset. Is there any code or any way to replicate the performance of the Grounding DINO on COCO dataset?
Thanks for t…