Add sv.CropAnnotator which annotates a cropped part of detections
#888
Conversation
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I struggled with the method that calculates the final x,y coordinates to placement and applies a trim to exceeding part of the image, that has to apply for all positions. Maybe you can refine a bit if you can to make it shorter. Nevertheless, execution time is pretty good. It would be nice if you could add a feature to use different anchor coordinates from another detections. For example, if we have two YOLO models to detect cars, and the second to detect plates, to have the ability to place the cropped plates in anchor positions of cars. Also we could use the filtering of These two methods will have a significant problem two cluster two objects from different class together, i.e. a person and a handbag, and not assign it to different once. Also the difference in number of prediction from both classes because sometimes a person may not carry a bag or may not be predicted. Maybe we could try that as an independent scenario in another issue. |
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Hi @xaristeidou 👋🏻 Thanks for opening the PR 🙏🏻 Yeah I saw |
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@SkalskiP The problem is that in each position a lot of checks have to be done to avoid numpy broadcasting errors, and these are not the same for all cases of position. I tried first to make it work for all cases and then would try to optimize. If I can achieve any optimization I will let you know. |
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Hello @xaristeidou 👋 First of all before reading code first thing caught my eyes is your commit messages needs clean up I personally don't like to see that "as" or "asdf" as commit message, it has no value and no meaning please rebase/squash those or I can do in the end or I can just simply squash merge because we also want to see meaningful commit messages |
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@onuralpszr Holy!! I wanted to test first the whole annotator and had a thought to re-write the commits as single separate for each method, but totally forgot that because that was days ago when I started it! I was in a hurry yesterday to finish and submit due to new version release! I am very very sorry for that, I don't like that also. I would be grateful if you could squash them for me because I haven't done it before and I don't want to mesh it up until I search a bit an test how to!! Thanks, and sorry again. |
It is okay just do what you need to, I can handle when it is done (squash or fix commits) |
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Awesome! I'll try to help out with refactoring. I probably won't be able to do it until Friday. I now have some Roboflow duties with a higher priority than Supervision. :/ |
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Hi @xaristeidou 👋🏻, I've made all the appropriate changes. I'm merging your PR. |
Description
This is an implementation of
sv.CropAnnotator. Crops a part for each detection insv.Detectionsbased on the selectedsv.Position.The following methods have been developed:
annotate: annotates the image scene using the methods below.apply_zoom: utilizedcv2.resize()to apply zoom of the cropped part.calculate_place_coordinates_and_crop: if/else statements for eachsv.Position. Returns x,y pixels that are the top left pixel for all cases of position, and trims any exceeding part of the cropped images from detections.place_cropped_scene: places the cropped part to the calculated position x,y up to cropped part shape dimensions.List any dependencies that are required for this change.
None
Please delete options that are not relevant.
How has this change been tested, please provide a testcase or example of how you tested the change?
Tested using YOLOv8 detection and applied on video sample of walking people.
Any specific deployment considerations
Although the
calculate_place_coordinates_and_cropmethod is wide enough, execution time is pretty fast.Noticed some delay (3ms) when using very high value of zoom_factor, which I think due to
cv2.resize()delay.Docs