Comments (4)
Between 500ms and 700ms sounds about right. Did that finding answer your question then? I am not sure if I can do anything to speed up the visualization function. I guess the bottleneck there is matplotlib but never profiled it.
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@michaelisc Iam trying to use opencv instead to see whether it can boost the visualization time or not. I will report the results later.
Update: I think the problem comes from my PC, after trying several times again with matplotlib and opencv, the total time results ( prediction + visualization ) are the same.
Thank you for your prompt support.
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Which model did you download and which function did you use for testing? model.evaluate_dataset
or model.detect
? The latter one can take a long time for the first image, as it has to initialize some components when the model is called for the first time. I found this behavior to be the same for the original Matterport Mask R-CNN implementation we build upon.
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@michaelisc I downloaded large_siamese_mrcnn_coco_full model and used model.detect for detection. I was testing detection for multiple images.
For the first image, it took about 24sec, and approximately 5 to 7sec for each image after that.
Ah, I just figured out that for prediction part, the model takes only 0.5 to 0.7 sec for 1 image. But display_results part takes so much time (at least 3sec for 1 image in my PC).
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Related Issues (20)
- How to use the pretrained weights? HOT 5
- plz help HOT 5
- shape error HOT 1
- Problem with mask predictions HOT 17
- How to design the loss function? HOT 4
- Multiple runs on training not evaluation HOT 2
- typo HOT 1
- Small typo HOT 1
- Dimension dismatch error when evaluate the retrained model for COCO, from epoch 2 HOT 2
- Problem with custom dataset HOT 8
- Under segmentation for close items HOT 4
- Performance is not as good as Mask RCNN when training on a small custom dataset HOT 1
- Modifications for training on custom dataset
- Test.ipynb
- One-Shot Detection - input_target shape Error HOT 3
- TypeError: unhashable type: 'ListWrapper' when try to train model HOT 1
- issue re-running
- Support for Tensorflow 2.4+ HOT 1
- Loading weights
- Why are model loading and inference times so slow?
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