Comments (6)
In this example, fortunately, you did int casting right away in visualize, so there was no problem.
but I'd like you to point this out.
from yolort.
Yes, I think it's possible, it depands on the inference results of YOLOv5 models. We didn't filter out the negative coordinates manually.
from yolort.
Yes, I think it's possible, it depands on the inference results of YOLOv5 models.
In the experiment, the box.x value will have a - value, so there will be no problem if I proceed with clip (n, 0, max), right?
from yolort.
Yep, you can filter out the coordinates outside the actual image resolution according to your needs.
from yolort.
@zhiqwang
Thank you for your advice
from yolort.
You're welcome and also thank you for your feedback.
In contrast, like some functions in OpenCV, they will automatically do some filtering of the coordinates outside the actual resolution of the image. We may also support similar features in the future.
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Related Issues (20)
- `numpy` does not support newline delimiter from version 1.23
- zlibwapi.dll (solved)
- No module named 'yolort.utils.update_module_state' while saving the Yolo Model HOT 6
- Dynamic batch dimension not working with ONNX export HOT 1
- module 'yolort' has no attribute 'utils' HOT 4
- Can't load custom trained model HOT 2
- Unexpected side effect on matplotlib's backend HOT 2
- Remove `NestedTensor` from pre-processing
- Loading pre-trained model is not supported for num_classes != 80 HOT 1
- Remove `ComputeLoss` from TorchScript graph
- SpeedUp with microsoft/nni HOT 3
- Can not export to ONNX model. AttributeError: 'NoneType' object has no attribute 'shape' HOT 7
- CLI tool for exporting models.: error: the following arguments are required: --checkpoint_path HOT 16
- Is it correct to subtract x_offset twice when performing bbox scale as post-processing? HOT 1
- If put yolov5 onnx exported from ultralytics into export_engine api, the postprocess speed slows down in cpp deploy. HOT 8
- SetCriterion's forward() incompatible with P6 models. Can't train P6 models.
- [defaultAllocator.cpp::deallocate::42] Error Code 1: Cuda Runtime (invalid argument) Segmentation fault (core dumped)
- Exporting ONNX Model with Fixed Batch Size of 1 Using export_tensorrt_engine
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