I didn't try it. I expect errors if we load the weights directly because the naming conventions of the modules differ. We might need to map the names to the original model in order to load its weights.
Hi. I would like to improve the accuracy of yolo recognition. The task is to recognize the contours of empty circles superimposed on each other in the image, as I understand it, you need to change the Bounding box to circles. How long will it take? Is it difficult? I want to get the radius of the circle instead of the width and height, the exact coordinates along the xy axis
Hi. That would be a nice project. However, I think it might not be a simple task. In terms of dataset, I'm not sure if there is any available dataset. For the model, we need to change the head to output radius + center, which might not be trivial.
@@taido4883 Hi! I already have a dataset of 2,000 labeled images in JSON format, including COCO, YOLO v1.1, YOLO v8, and others. All data was annotated using CVAT. Regarding the idea of recognizing circles, I consulted with other specialists, and we came to the conclusion that the center of the circle should match the center of the predicted bounding box. The radius can be calculated as the average of half the width and height of the bounding box, i.e., (height + width) / 4. This approach might simplify the model modification. What do you think?
I hope you are well. It happens that I want to use Dataset file on my photos, I have the photos and annotations in different folders. What is the proper structure I should have for dataset to work correctly? Because I'm trying to adapt it and it doesn't take the annotations only the photos. Thanks for your attention
Hi. It is cool that you want to adapt it on your own data. Here is the data structure ├── COCO ├── images ├── train2017 ├── 1111.jpg ├── 2222.jpg ├── val2017 ├── 1111.jpg ├── 2222.jpg ├── labels ├── train2017 ├── 1111.txt ├── 2222.txt ├── val2017 ├── 1111.txt ├── 2222.txt
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Can you do for detr(detection transformer) also, it will be really good sir
Sound good, definitely will dive into it in the future!
I was just about to do the same , even create a mini API for full pipeline...
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That would be cool!
Hi Tai, that was really grate and Im persuaded to engage with your channel, that was amazing, too
Hi (not sure how to call you!). I am very happy you like it 👍
did you try loading in the original yolov8 weights into the model
I didn't try it. I expect errors if we load the weights directly because the naming conventions of the modules differ. We might need to map the names to the original model in order to load its weights.
Hi. I would like to improve the accuracy of yolo recognition. The task is to recognize the contours of empty circles superimposed on each other in the image, as I understand it, you need to change the Bounding box to circles. How long will it take? Is it difficult? I want to get the radius of the circle instead of the width and height, the exact coordinates along the xy axis
Hi. That would be a nice project.
However, I think it might not be a simple task. In terms of dataset, I'm not sure if there is any available dataset. For the model, we need to change the head to output radius + center, which might not be trivial.
@@taido4883 Hi! I already have a dataset of 2,000 labeled images in JSON format, including COCO, YOLO v1.1, YOLO v8, and others. All data was annotated using CVAT. Regarding the idea of recognizing circles, I consulted with other specialists, and we came to the conclusion that the center of the circle should match the center of the predicted bounding box. The radius can be calculated as the average of half the width and height of the bounding box, i.e., (height + width) / 4. This approach might simplify the model modification. What do you think?
can you share the link of the dataset you used
Sure. You can get it from Kaggle
www.kaggle.com/datasets/awsaf49/coco-2017-dataset
@@taido4883 thanks
I hope you are well. It happens that I want to use Dataset file on my photos, I have the photos and annotations in different folders. What is the proper structure I should have for dataset to work correctly? Because I'm trying to adapt it and it doesn't take the annotations only the photos. Thanks for your attention
Hi. It is cool that you want to adapt it on your own data. Here is the data structure
├── COCO
├── images
├── train2017
├── 1111.jpg
├── 2222.jpg
├── val2017
├── 1111.jpg
├── 2222.jpg
├── labels
├── train2017
├── 1111.txt
├── 2222.txt
├── val2017
├── 1111.txt
├── 2222.txt
@@taido4883 can i See how txt files Looks?
@@taido4883 perfect! My files are . XML ,What do your txt files look like? Do i need to modify my py Dataset file?
@@taido4883 thanks a lot! How Is the structure of txt files? Is the Same as XML?