6.3 深度学习替代SVM 如果你发现SVM的效果不够好,可以尝试使用深度学习方法(如卷积神经网络CNN或长短期记忆网络LSTM)来替代SVM,以更好地捕捉时间序列中的动态特征。 7. 总结 本教程展示了如何结合YOLO Pose进行人体姿态估计,并使用支持向量机(SVM)进行动作分类。YOLO Pose提供了人体的关键点信息,而SVM则根据这些关键...
yolov7-pose_lstm +---+ | LSTM | | (64) | | return_sequences=True | +---+---+ | +---+---+ | LayerNormalization | | (axis=1) | +---+---+ | +---+---+ | LSTM | | (128) | | return_sequences=True | +---+---+ | +---+---+ | LSTM | | (128) | ...
二、Yolopose核心原理 网络结构 Yolopose采用了独特的网络结构,融合了卷积神经网络(CNN)与长短期记忆网络(LSTM)的优点。CNN负责提取图像中的特征,而LSTM则能够捕捉时间序列信息,二者相结合,使得Yolopose在处理动态视频时具有更高的准确性。 关键点检测 Yolopose通过训练大量的数据,学习到了人体关键点的特征。在推理...
模型训练权重和指标可视化展示 我们将使用 YOLOv8Pose 进行人脸关键点检测(模拟水表指针位置),并使用 CRNN 进行数字识别。 训练YOLOv8Pose []fromultralyticsimportYOLOimportos# Define pathsdataset_path='path/to/dataset'weights_path='runs/train/exp/weights/best.pt'# Create dataset.yamlyaml_content=f"""t...
deep-learningcnnpytorchsortlstmyoloface-recognitionface-detectionarcfaceretinafacest-gcnyolov5yolo5faceyolov7yolo-posestrongsort UpdatedMar 9, 2025 Python FatemeZamanian/YOLOv8-pose-onnxruntime-web Star16 A simple React application to detect persons and their pose landmarks ...
In this study, four types of fall detection systems – designed with YOLOPose, principal component analysis (PCA), convolutional neural network (CNN), and long short-term memory (LSTM) architectures – were developed and compared in the detection of everyday falls. T...
['pose'] = obj.find('pose').text #obj_struct['truncated'] = int(obj.find('truncated').text) obj_struct['difficult'] = int(obj.find('difficult').text) bbox = obj.find('bndbox') obj_struct['bbox'] = [int(bbox.find('xmin').text), int(bbox.find('ymin').text), int(b...
Pose Estimation using YOLOv7 Badminton Shots Identification using LSTM and YOLOv7 Pose Estimation Model Crunch Counter using YOLOv7 Pose Estimation Real Time Sign Language Alphabets Detection using YOLO-NAS Personal Protective Equipment Detection using YOLO-NAS Real-Time Custom Object Detection with YOLO...
#图片的宽和高 <size> <width>486</width> <height>500</height> <depth>3</depth> </size> <segmented>0</segmented> #类别名 <name>person</name> #物体的姿势 <pose>Unspecified</pose> #物体是否被部分遮挡 <truncated>0</truncated> ##是否为难以辨识的物体, 主要指要结合背景才能判断出类别的...
lstm_layer.o l2norm_layer.o yolo_layer.o iseg_layer.o image_opencv.o EXECOBJA=captcha.o lsd.o super.o art.o tag.o cifar.o go.o rnn.o segmenter.o regressor.o classifier.o coco.o yolo.o detector.o nightmare.o instance-segmenter.o darknet.o ifeq ($(GPU), 1) LDFLAGS+= -lstdc...