Hi, we’d like to annotate spherical objects like walnuts, eggs to classify them by sizes/ diameter. I understand that images can be labelled with circular boundings, but not sure what is the best way to achieve it within the roboflow labelling interface. While labelling images, within smart polygo…

Based on the information provided in the extracts, Roboflow supports various annotation tools including bounding boxes, polygons, and smart polygons. However, there is no specific mention of a tool for annotating spherical objects or using a convex hull shape option within the smart polygons. The S…

@kedar Whether using object detection or instance segmentation depends on the project. If the circular object detection you’re looking for is something you want rendered fast, maybe many times per second I would recommend using an object-detection model built on a large and well annotated dataset w…

Thanks @Alejandro_Bermudez . Speed of prediction is not important in this use case, accuracy is. [Screen Shot 2023-10-02 at 16.26.07] Based on this, per your reasoning, using this type of bounding circle to classify sizes should be better than the bounding box. Is that incorrect?

Yes, if speed is not an important factor and you’re looking for accuracy of shape, this should be an instance segmentation project! Also, I am curious as to why you have two classes for the same type of object, did you mean to do that?

Thanks for asking. The two classes represent walnuts of 2 different sizes (32mm and 30mm). Our goal is to train a model to identify different sizes of the walnuts. These walnuts have been calibrated manually using a measuring device in order for labelling the dataset. Does this approach not make s…

I think it does, and making the model shouldn’t be too hard… however I will say, since you’re working with measurements you bring in a new factor, scale. Which means you are likely gonna want to standardize the process! Making a model that can tell the difference between objects is easy enough, but …

That’s right @Alejandro_Bermudez . The vertical distance between the image capture device and tray is kept constant with this setup and flash on. [IMG_20231003_074748130] The tray is placed in 3 positions: Center (cross hairs at the center of tray) Up (cross hairs 2 rows up) Down (cross hairs …

@kedar thats great! it looks like this is already well thought out. Also, im curious as to why you went with 3 different slightly different angles, is there a strategy to that?

Oh well, it is still in test so let’s see if it helps. The image captured at 3072X4096, 12.58MP resolution, tall, 4:3 The tray is moved up and down from center to view the units in outer rows without overlap for larger sizes of walnuts. center view + 2 positions displaced vertically from center ar…

The only challenges I see with this approach is deviation from the normalization of data. If you can fit all the walnuts into one picture without distortion, why not just do that? without moving the board you dont introduce any more variables than necessary. Unless im understanding wrong, you wrote …

Bounding circles for 3d objects like eggs, walnuts, etc?

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kedar October 2, 2023, 9:31pm 4

Thanks @Alejandro_Bermudez.

Speed of prediction is not important in this use case, accuracy is.

Based on this, per your reasoning, using this type of bounding circle to classify sizes should be better than the bounding box. Is that incorrect?

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Bounding circles for 3d objects like eggs, walnuts, etc?

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