visualizing results

[syssj1002]

Thanks for your great work. After testing the code, how can I print the image results with bounding box? Is there any command or code?

[yang-0201]

I want to know too！！

[lebionick]

i found plot_dual_img function in the code, but struggling with usage of it (no example in code at all). So I am wondering too

[YooWang]

I also didn't find a visualization of outputting a single image, but I referenced DETR's visualization code, which can then be used directly here.

[SaifeiYan]

can you send the your code to me?thanks a lot!

[SaifeiYan]

I also didn't find a visualization of outputting a single image, but I referenced DETR's visualization code, which can then be used directly here. Are you using DAB-Deformable-DETR, can you send me the reasoning visualization file?

[QiqLiang]

I also want to know! Somebody helps!

[SlongLiu]

Hello everyone, I provide a note for a demo of inference and visualization in https://github.com/IDEA-opensource/DAB-DETR/blob/main/inference_and_visualize.ipynb. Hope the file is helpful to you. Thanks for your suggestions.

[SaifeiYan]

Hello everyone, I provide a note for a demo of inference and visualization in https://github.com/IDEA-opensource/DAB-DETR/blob/main/inference_and_visualize.ipynb. Hope the file is helpful to you. Thanks for your suggestions.

Hello ,when I use your inference code, when I get to this line of code:

"output = model(image[None]) output = postprocessors['bbox'](output, torch.Tensor([[1.0, 1.0]]))[0]"

and then, how should I solve this problem, please tell me more , Thanks a lot!

[SlongLiu]

Hello everyone, I provide a note for a demo of inference and visualization in https://github.com/IDEA-opensource/DAB-DETR/blob/main/inference_and_visualize.ipynb. Hope the file is helpful to you. Thanks for your suggestions.

Hello ,when I use your inference code, when I get to this line of code:

"output = model(image[None]) output = postprocessors['bbox'](output, torch.Tensor([[1.0, 1.0]]))[0]"

and then, how should I solve this problem, please tell me more , Thanks a lot!

Our code is running on CPUs, whereas the dab_deformable_detr supports GPU only. You can send images and models to GPU before inference. A simple way to modify it:

model = model.cuda()
image = image.cuda()
output = model(image[None])

[SaifeiYan]

Hello everyone, I provide a note for a demo of inference and visualization in https://github.com/IDEA-opensource/DAB-DETR/blob/main/inference_and_visualize.ipynb. Hope the file is helpful to you. Thanks for your suggestions.

Hello ,when I use your inference code, when I get to this line of code: "output = model(image[None]) output = postprocessors['bbox'](output, torch.Tensor([[1.0, 1.0]]))[0]" and then, how should I solve this problem, please tell me more , Thanks a lot!

Our code is running on CPUs, whereas the dab_deformable_detr supports GPU only. You can send images and models to GPU before inference. A simple way to modify it:

model = model.cuda()
image = image.cuda()
output = model(image[None])

Thank you very much for the answer, I also solved the problem, wish you success in your career, thanks again

[yang-0201]

I find this code will inference validation dataset，but I don‘t konw how to inference local pictures.

[lebionick]

Use PIL Image with path to your image and None as target

[SlongLiu]

I update the notebook to support visualizing custom images. See https://github.com/IDEA-opensource/DAB-DETR/blob/main/inference_and_visualize.ipynb for more details.

I find this code will inference validation dataset，but I don‘t konw how to inference local pictures.