From 0b3232a160413dd6b5fdf3a8e9092cfc159ff6bc Mon Sep 17 00:00:00 2001 From: "Alessandro de Oliveira Faria (A.K.A.CABELO)" Date: Tue, 27 Feb 2024 09:34:15 -0300 Subject: [PATCH] Merge pull request #25095 from cabelo:yolov8x Added and tested yolov8x model #25095 ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [X] I agree to contribute to the project under Apache 2 License. - [X] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [X] The PR is proposed to the proper branch - [X] There is a reference to the original bug report and related work - [X] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [X] The feature is well documented and sample code can be built with the project CMake Below is evidence of the test: ![opencv](https://github.com/opencv/opencv/assets/675645/40e81951-a8fd-410b-9dfc-c08254f99bdc) --- samples/dnn/models.yml | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/samples/dnn/models.yml b/samples/dnn/models.yml index 4d2774c71e..f72a385942 100644 --- a/samples/dnn/models.yml +++ b/samples/dnn/models.yml @@ -18,6 +18,22 @@ opencv_fd: rgb: false sample: "object_detection" +# YOLOv8 object detection family from ultralytics (https://github.com/ultralytics/ultralytics) +# Might be used for all YOLOv8n YOLOv8s YOLOv8m YOLOv8l and YOLOv8x +yolov8x: + load_info: + url: "https://huggingface.co/cabelo/yolov8/resolve/main/yolov8x.onnx?download=true" + sha1: "462f15d668c046d38e27d3df01fe8142dd004cb4" + model: "yolov8x.onnx" + mean: 0.0 + scale: 0.00392 + width: 640 + height: 640 + rgb: true + classes: "object_detection_classes_yolo.txt" + background_label_id: 0 + sample: "yolo_detector" + # YOLO4 object detection family from Darknet (https://github.com/AlexeyAB/darknet) # YOLO object detection family from Darknet (https://pjreddie.com/darknet/yolo/) # Might be used for all YOLOv2, TinyYolov2, YOLOv3, YOLOv4 and TinyYolov4