使用OpenCV部署yolov8检测人脸和关键点以及人脸质量评价，包含C++和Python两个版本的程序，只依赖opencv库就可以运行，彻底摆脱对任何深度学习框架的依赖。
使用OpenCV部署yolov8检测人脸和关键点，包含C++和Python两个版本的程序，只依赖opencv库就可以运行。
训练源码是https://github.com/derronqi/yolov8-face 如果想做车牌检测4个角点，那就把检测5个人脸关键点改成4个
此外，添加了人脸质量评估模型fqa，需要结合人脸检测来使用，对应的程序是main_fqa.py和main_fqa.cpp
我想请教一下如何获得被识别物体的类别，我用cls_id但得到的不是正确的数字，谢谢
Ubuntu 20.04 系统，OpenCV尝试了4.5.5版本和4.7版本，验证了模型文件.onnx无错误，在使用onnxruntime和main.cpp两种部署方式时均返回下述报错
terminate called after throwing an instance of 'cv::Exception'
what(): OpenCV(4.5.5) /home/hou/opencv-4.5.5/modules/dnn/src/onnx/onnx_importer.cpp:709: error: (-215:Assertion failed) model_proto.has_graph() in function 'populateNet'
已放弃 (核心已转储)
大佬知道这是什么原因吗
我用export 导出yolov8n-face到onnx没问题,但是yolov8-lite-s and yolov8-lite-t就报错，大佬你是咋导出的呀
yolo mode=export model=yolov8-lite-s.pt format=onnx simplify=True batch=1
Traceback (most recent call last):
File "/home/pcb/.local/bin/yolo", line 8, in
sys.exit(entrypoint())
File "/home/pcb/.local/lib/python3.8/site-packages/ultralytics/yolo/cfg/init.py", line 378, in entrypoint
model = YOLO(model, task=task)
File "/home/pcb/.local/lib/python3.8/site-packages/ultralytics/yolo/engine/model.py", line 107, in init
self._load(model, task)
File "/home/pcb/.local/lib/python3.8/site-packages/ultralytics/yolo/engine/model.py", line 156, in _load
self.model, self.ckpt = attempt_load_one_weight(weights)
File "/home/pcb/.local/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 578, in attempt_load_one_weight
ckpt, weight = torch_safe_load(weight) # load ckpt
File "/home/pcb/.local/lib/python3.8/site-packages/ultralytics/nn/tasks.py", line 518, in torch_safe_load
return torch.load(file, map_location='cpu'), file # load
File "/home/pcb/.local/lib/python3.8/site-packages/torch/serialization.py", line 607, in load
return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
File "/home/pcb/.local/lib/python3.8/site-packages/torch/serialization.py", line 882, in _load
result = unpickler.load()
File "/home/pcb/.local/lib/python3.8/site-packages/torch/serialization.py", line 875, in find_class
return super().find_class(mod_name, name)
AttributeError: Can't get attribute 'StemBlock' on <module 'ultralytics.nn.modules' from '/home/pcb/.local/lib/python3.8/site-packages/ultralytics/nn/modules/init.py'>
能不能出一期yolov8目标追踪的c++ onnxruntime部署方法呀
大佬，你试过tensorrt加速吗，如果要使用tensorrt，应该怎么处理呀
控制台输出如下：
[ INFO:[email protected]] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load C:\Windows\SYSTEM32\opencv_core_parallel_onetbb470_64d.dll => FAILED
[ INFO:[email protected]] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load opencv_core_parallel_onetbb470_64d.dll => FAILED
[ INFO:[email protected]] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load C:\Windows\SYSTEM32\opencv_core_parallel_tbb470_64d.dll => FAILED
[ INFO:[email protected]] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load opencv_core_parallel_tbb470_64d.dll => FAILED
[ INFO:[email protected]] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load C:\Windows\SYSTEM32\opencv_core_parallel_openmp470_64d.dll => FAILED
[ INFO:[email protected]] global plugin_loader.impl.hpp:67 cv::plugin::impl::DynamicLib::libraryLoad load opencv_core_parallel_openmp470_64d.dll => FAILED
Hi，Could you provide the reference of the fqa model (face-quality-assessment.onnx)?
I find the output of model has 10 dimensions, is there any introduction?
THX~
我用yolov8-face训练出来的 关键点只有4个的模型 在pytorch上跑的坐标都是正确的
但是在dnn调用后的坐标混乱
也可能是关键点相关代码需要特殊修改？
图片无人脸情况下，cv2.dnn.NMSBoxes输出的indices是空的tuple()。
有人脸情况下输出的是array([2])。
所以if len(indices) > 0: 判断这里是无效的，会在上一句直接报错。烦请修改一下
main.py and getting this error.yolov8-face-landmarks-opencv-dnn on main via 🐍 v3.8.10
❯ py main.py
Traceback (most recent call last):
File "main.py", line 171, in <module>
boxes, scores, classids, kpts = YOLOv8_face_detector.detect(srcimg)
File "main.py", line 75, in detect
det_bboxes, det_conf, det_classid, landmarks = self.post_process(outputs, scale_h, scale_w, padh, padw)
File "main.py", line 92, in post_process
bbox = self.distance2bbox(anchors, bbox_pred, max_shape=(self.input_height, self.input_width)) * stride
File "main.py", line 134, in distance2bbox
x1 = points[:, 0] - distance[:, 0]
ValueError: operands could not be broadcast together with shapes (6400,) (1600,)
您好，现有代码是基于CPU的版本，请问如何将其修改为基于GPU的版本？
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