from ultralytics import YOLO
import cv2
import torch

# 加载模型
model = YOLO('best.pt')

# 读取一张真实图像
img_path = '/media/hx/04e879fa-d697-4b02-ac7e-a4148876ebb0/dataset/point2/train/1.jpg'  # 替换成您的图像路径
image = cv2.imread(img_path)

# 将图像转换成RGB格式，并调整大小
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
image_resized = cv2.resize(image_rgb, (640, 640))

# 进行推理
results = model(image_resized)

# 打印关键点数据形状和样本
if len(results) > 0 and hasattr(results[0], 'keypoints') and results[0].keypoints is not None:
    print("Keypoints data shape:", results[0].keypoints.data.shape)
    if results[0].keypoints.data.shape[0] > 0:
        print("Keypoints data sample:", results[0].keypoints.data[0, :12])
else:
    print("No keypoints detected or invalid keypoints data.")