tasks/obb/ #7974
Replies: 18 comments 66 replies
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Hi, when I am using yolov8_obb model in results I always have even when the model makes prediction. Did someone faced with this problem and if yes, what was the solution? Thank you.🙂 |
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Hi, how can I access the results from this new model so I can extract bounding box information |
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Hi, I am trying to obtain the angle of an object using angle = float(box.xywhr[0][4]), but it does not seem to be what I expected. I usually get an angle value between 0 and 3, even when I rotate the image by 90 or 180 degrees, the model still predicts and returns the correct object coordinates. It seems like I made a mistake somewhere while attempting to obtain the angle of an object. |
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Hi,Could the heatmap functionality be used on YOLOv8-obb? |
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Hi,I have some questions when I use the DOTAv1.0 for OBB task. |
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how to do Model Ensembling on yolov8-obb models? |
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Hi, the YOLOv8n-obb test map-50 result on DOTAv1.0 is 78.0%. I split the train set and val set images to 1024*1024 and I wonder the 78% is the val set result given by the model.val()? or the test set result given by the DOTA server? And how to merge the result submitted to the server if the figure 78% is the test result given by the DOTA server? |
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how can i test DOTA1.0 datasets using YOLOV8-obb ? online submit for results? somebody help me? emergency |
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Hi, I saw yolov8 obb with tracking from yolov8-v2 |
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Subject: Cropping Images from YOLOv8 Detections (Python) Hi everyone, I'm working on a Python project that utilizes a YOLOv8 model for object detection. I'd like to achieve the following functionality: Perform object detection on input images using my trained YOLOv8 model. could you share an example code snippet demonstrating how to achieve this cropping functionality using the bounding box data? |
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Hello, I'm currently working with YOLOOBB (You Only Look Once Oriented Bounding Boxes), and I've annotated my data using the YOLOOBB format. My concern now is how to apply augmentations for oriented bounding boxes, particularly for transformations like rotation, horizontal flipping, and vertical flipping. Each augmented image will need its annotation file adjusted accordingly. I'm using the albumentations library in Python for data augmentation. Here's the transformation pipeline I've defined: import albumentations as A
transform_pipeline= A.Compose([
A.Rotate(limit=(-90, 90)),
A.VerticalFlip(p=1),
A.HorizontalFlip(p=0.5),
A.ToTensor()
], bbox_params=A.BboxParams(
format="yolo",
label_fields=["class_labels"],
)) However, the YOLOOBB format is different from the default YOLO format. How should I process the annotations in this case to ensure they match the augmented images? Any insights or suggestions on how to handle this scenario would be greatly appreciated! Thank you. |
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HI, when I am training yolov8_obb models on muti-GPUs I meet an error File "/tmp/pycharm_project_538/ultralytics-main/ultralytics/utils/loss.py", line 626, in call It seems that the error is related to the calculation of the OBB loss. It expects two elements but got three. This error occurs when training on multiple GPUs, but it works fine on single GPU. How can I solve this problem?Thank you. |
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i am curious, doest it uses the same approach as yolov5-obb which use CSL for its OBB function? |
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for yolov8n-obb , results[0].boxes are returning none. previously, it was working. i think ultralytics recent update got it removed? |
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Hey, 0: 704x1024 191.9ms AttributeError: 'NoneType' object has no attribute '_jit_internal' This is my code: cap = cv2.VideoCapture("video.mp4") while True: |
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I tried to follow the above instructions to use OBB in a webcam environment, but I'm encountering the following error. |
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Hi, I would like to train a yolov8l-obb model, but I couldn't find the corresponding yolov8l-obb.yaml configuration file. Also, I want to set my image size to 512x1024, but it seems it's not taking effect. Lastly, how can I set up random vertical flipping during training? Looking forward to your response, thank you. |
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tasks/obb/
Learn how to use oriented object detection models with Ultralytics YOLO. Instructions on training, validation, image prediction, and model export.
https://docs.ultralytics.com/tasks/obb/
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