Open PGDneedoffer opened 3 years ago
I did demo.py to run the inference on a single image and visualize the results on it. you can get it at https://github.com/ahmed-nady/Deformable-DETR
hello @ahmed-nady could you tell me what inference speed do you have and with what gpu?
thanks in advance
Inference speed on image size provided in the code (800) is 110 ms roughly and the GPU used is Tesla V100-SXM2
代码(800)中提供的图像大小推断速度大约为110毫秒,所使用的GPU为Tesla V100-SXM2
please to ask How could I add class tags and prediction probability to the prediction box, thanks
In demo.py line 182, you can set the wanted threshold as keep = scores[0] > 0.35. For class tags, line 184 provides you with tags of detected objects labels = labels[0, keep]. Also, you can filter the unwanted class. For the size of the input image, you can change it as required as in line 134, for example, this instruction makes your input be in size 800T.Resize(800)
@ahmed-nady When I run demo.py I get the following message:
error in ms_deformable_im2col_cuda: out of memory
.
This error never appears during training or when I evaluate on epoch end, have you encountered this?
Is it convenient to provide reasoning files?