Object Detection through YOLOv3 using Darknet Importer in MATLAB

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Hi
I am loading the cfg and weight files using darknet importer but finding difficulties to add the detection layer at the end.
In the official Documentation here (https://www.mathworks.com/matlabcentral/fileexchange/71277-deep-learning-darknet-importer?focused=098f9ec1-f049-4aef-a910-93b617a7a299&tab=function), there is no explanation about adding a detection layer. It is only for image classification.
Can anyone please help me in this regard?
Or you can tell me any other way to detect objects in matlab (pre-trained on coco)

Risposte (2)

Farah Sarwar
Farah Sarwar il 5 Nov 2019
You can use YOLOv2 in MATLAB for object detection as well as R-CNN, Fast R-CNN and Faster R-CNN. Here is the link of help file for object detecion in MATLAB using YOLOv2: https://au.mathworks.com/help/deeplearning/examples/object-detection-using-yolo-v2.html
YOLOv3 definitely performs better than v2 but you will develop some understanding of the topic.
  2 Commenti
Muhammad Talha
Muhammad Talha il 25 Nov 2019
Modificato: Muhammad Talha il 25 Nov 2019
Hi Farah Sarwar,
Thanks for your help.
The sent link has the dataset only for vehicles.
Can you please guide me how I can get or make the .mat file for my own dataset or for the famous datasets like COCO or VOC, so that I can train the dataset for YOLO v2 or Faster RCNN or Mask RCNN?
Hayat  Bouchkouk
Hayat Bouchkouk il 22 Mar 2020
Hi,Muhammad Talha
I want to know if you are able to load coco dataset in matlab or not because i face the same probleme,plizz if any body can help me ,i'me really stuck

Accedi per commentare.


cui,xingxing
cui,xingxing il 19 Ago 2020
This is the yolov3 you want, but there is a problem with saving the model during training, especially the parameter saving of the bn layer should be consistent with darknet, and the labeled [x, y, w, h], instead of Normalized [center_x, center_y, w, h ]

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