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bugs for "release/6.0" on "Add new GridAnchorRect_TRT plugin to support rectangular feature maps." #247
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@rajeevsrao for bug with this plugin. Also FWIW, this commit wasn't included in release/7.0 or master branch. |
@fshi98 can you please attach sample code to repro the issue you are seeing for 2 (assuming the plugin must be registered under GridAnchorRect_TRT)? Also, did you check if sampleUffSSD (which uses GridAchorRect_TRT) works? |
Closing since no response. Will re-open if necessary. |
I used a squared size (300x300) and the plugin worked fine, but now I am using a different input size (240 height x 360 width) with "GridAnchorRect_TRT" and the output predictions are wrong. I use the following configuration to create the trt plugin:
And I get these weird/mirrored predictions: Obviously the bounding box coordinates are wrongly encoded/decoded from the anchors. I think that GridAnchorRect_TRT is a fundamental plugin for real world applications, and it needs a fix asap. |
@rmccorm4 do you mind re-opening it? |
Well @rajeevsrao , now the uff parser does not find the plugin:
I am creating the plugin node using this code:
I started from the container nvcr.io/nvidia/deepstream-l4t:5.0-20.07-base. I also tried to rebuild the TensorRT OSS components on Jetson from the master branch, with no success, the error was the same. I am using TensorRT version: 7.1.3, library version: 7. Am I doing something wrong? Do you have any clues? EDIT: I have opened a new issue for this 807 |
If using different input size (such as 600x300), with "GridAnchorRect_TRT", the outputs are wrong.
we use a featuremaps of "featureMapShapes=[19, 38, 10, 19, 5, 10, 3, 5, 2, 3, 1, 2])#600x300". There are couple of bugs:
Even if we resolve such issues, the output bounding boxes are still not correct, and not sure how the problems come from.
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