ONNX-YOLOv7-Object-Detection
AS-One
ONNX-YOLOv7-Object-Detection | AS-One | |
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2 | 6 | |
182 | 577 | |
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0.0 | 6.6 | |
about 1 year ago | 5 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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ONNX-YOLOv7-Object-Detection
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
Finally, I tried to look if someone has done similar work for the ONNX model and I found this repo which links the same repo I am trying to use, and I believe this function is doing exactly what I want to do, but I could not understand what it is doing (I don't understand how it knows exactly where the number of detections is, and where the bounding boxes are and the class labels, etc.) furthermore, I am not sure if removing end2end and the changing the version from 12 to 9 has any effect on the output shape or it has to do with the internal layers.
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YOLOv7 object detection in Ruby in 10 minutes
git clone https://github.com/ibaiGorordo/ONNX-YOLOv7-Object-Detection.git cd ONNX-YOLOv7-Object-Detection pip install -r requirements.txt
AS-One
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What are some alternatives?
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easy-yolov7 - This a clean and easy-to-use implementation of YOLOv7 in PyTorch, made with ❤️ by Theos AI.
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mmyolo - OpenMMLab YOLO series toolbox and benchmark. Implemented RTMDet, RTMDet-Rotated,YOLOv5, YOLOv6, YOLOv7, YOLOv8,YOLOX, PPYOLOE, etc.