At Readme of YOLOv3, Value types of original image size need to be float
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Description
Bug Report
Which model does this pertain to?
Describe the bug
Each of hosted models(YOLOv3, YOLOv3-12, YOLOv3-12-int8) need the original image size as the second input.
These Onnx Models expect float values for the second input, but the preprocessing steps sets it as dtype=np.int32, this causes asserting by type error.
It need to be np.float32 or 'float32' for the parameter dtype on this last line, same as Tiny Yolov3.
I will make a pull request for this issue soon.
Reproduction instructions
System Information
OS Platform and Distribution:
Windows 11 22H2
ONNX version:
not needed for reproducing this issue
Backend/Runtime version:
onnxruntime 1.18.0
numpy 1.26.0
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Open validated/vision/object_detection_segmentation/yolov3/README.md and read the preprocessing steps, especially the final dtype setting for the original image size. Compare it with the linked Tiny YOLOv3 README. Done means the YOLOv3 README uses the float dtype expected by the hosted models instead of int32.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 35/100