Comments (3)
zhreshold
commented on September 15, 2024
Measure single image is not accurate especially on GPU, because cuda/mxnet engine need to be cold initialized.
You can try batching a series of images, or even dummy duplicate images to test the forward avg time consumption.
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liumusicforever
commented on September 15, 2024
@zhreshold Can you share your detection benchmark in this repo ? thanks!!
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zhreshold
commented on September 15, 2024
#13 Is a nice example
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Related Issues (20)
- import HOT 1
- Error in building HOT 4
- What the number of column 9 mean in file *.lst? HOT 1
- Can not run using GPU HOT 2
- how to write a .json config file? HOT 1
- why error when using pretrained model?
- MXNet built from source problem HOT 3
- AttributeError: module 'mxnet.contrib.symbol' has no attribute 'YoloOutput' HOT 10
- The different effects of different resnet pretrained models HOT 3
- 'module' object has no attribute 'Yolo2Output' HOT 8
- Errors when running demo.py and video_demo.py HOT 1
- mxnet.base.MXNetError: Failed loading Op yolo_output of type _contrib_Yolo2Output: [13:11:48] src/core/op.cc:55: Check failed: op != nullptr Operator _contrib_Yolo2Output is not registered HOT 6
- Any plans for yolov3？ HOT 8
- method get_symbol() cannot be invoked correctly HOT 2
- Acc don't change
- training on my own dataset
- symbol_darknet19.py batchnorm layers use_global_stats problems
- Why not use the mxnet.image.ImageDetIter?
- Not reliable
- What is the execution environment
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