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大气企业网站,北京seo优化费用,合肥最好的网站建设公司排名,天津网站定制公司FreiHAND （handposeX-json 格式）数据集-release 注意： 1)为了方便使用，按照 handposeX json 自定义格式存储 2)使用常见依赖库进行调用,降低数据集使用难度。 3)部分数据集获取请加入：DataBall-X数据球(free) 4)完…

FreiHAND （handposeX-json 格式）数据集-release

注意：

1)为了方便使用，按照 handposeX json 自定义格式存储

2)使用常见依赖库进行调用,降低数据集使用难度。

3)部分数据集获取请加入：DataBall-X数据球(free)

4)完整数据集获取请加入：DataBall-X数据球(vip)

FreiHAND 数据集官方项目地址：https://github.com/lmb-freiburg/freihand

handposeX-json 格式项目地址：GitHub - XIAN-HHappy/handpose_x_plus

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一、handposeX json 格式示例

cx,cy,fx,fy为相机内参。

label:左右手标签

joint3d:三维手部21关键点

vertex3d:三维手mesh网格点

{"author": "XIAN","img_name:": "","cx": 112.0,"cy": 112.0,"fx": 388.9018310596544,"fy": 388.71231836584275,"hands": [{"label": "right","joint3d": [[29.402047395706177,-27.920207008719444,587.0807766914368],······],"vertex3d": [[10.056010007858276,29.915300235152245,-626.9440693855286],······]}]}

---------------

二、脚本运行

cd script/FreiHANDpython read_handposex_json.py

read_handposex_json.py具体实现如下，简洁明了：

#-*-coding:utf-8-*-
# date:2024-02-23
# Author: XIAN
# function: handposeX json 格式读取数据标签
import sys
sys.path.append("./")
import os
import cv2
import json
import numpy as np
import random
'''
function: 绘制二维关键点连线
'''
def draw_joints(img_,hand_,x,y):thick = 2colors = [(0,215,255),(255,115,55),(5,255,55),(25,15,255),(225,15,55)]#cv2.line(img_, (int(hand_['0']['x']+x), int(hand_['0']['y']+y)),(int(hand_['1']['x']+x), int(hand_['1']['y']+y)), colors[0], thick)cv2.line(img_, (int(hand_['1']['x']+x), int(hand_['1']['y']+y)),(int(hand_['2']['x']+x), int(hand_['2']['y']+y)), colors[0], thick)cv2.line(img_, (int(hand_['2']['x']+x), int(hand_['2']['y']+y)),(int(hand_['3']['x']+x), int(hand_['3']['y']+y)), colors[0], thick)cv2.line(img_, (int(hand_['3']['x']+x), int(hand_['3']['y']+y)),(int(hand_['4']['x']+x), int(hand_['4']['y']+y)), colors[0], thick)cv2.line(img_, (int(hand_['0']['x']+x), int(hand_['0']['y']+y)),(int(hand_['5']['x']+x), int(hand_['5']['y']+y)), colors[1], thick)cv2.line(img_, (int(hand_['5']['x']+x), int(hand_['5']['y']+y)),(int(hand_['6']['x']+x), int(hand_['6']['y']+y)), colors[1], thick)cv2.line(img_, (int(hand_['6']['x']+x), int(hand_['6']['y']+y)),(int(hand_['7']['x']+x), int(hand_['7']['y']+y)), colors[1], thick)cv2.line(img_, (int(hand_['7']['x']+x), int(hand_['7']['y']+y)),(int(hand_['8']['x']+x), int(hand_['8']['y']+y)), colors[1], thick)cv2.line(img_, (int(hand_['0']['x']+x), int(hand_['0']['y']+y)),(int(hand_['9']['x']+x), int(hand_['9']['y']+y)), colors[2], thick)cv2.line(img_, (int(hand_['9']['x']+x), int(hand_['9']['y']+y)),(int(hand_['10']['x']+x), int(hand_['10']['y']+y)), colors[2], thick)cv2.line(img_, (int(hand_['10']['x']+x), int(hand_['10']['y']+y)),(int(hand_['11']['x']+x), int(hand_['11']['y']+y)), colors[2], thick)cv2.line(img_, (int(hand_['11']['x']+x), int(hand_['11']['y']+y)),(int(hand_['12']['x']+x), int(hand_['12']['y']+y)), colors[2], thick)cv2.line(img_, (int(hand_['0']['x']+x), int(hand_['0']['y']+y)),(int(hand_['13']['x']+x), int(hand_['13']['y']+y)), colors[3], thick)cv2.line(img_, (int(hand_['13']['x']+x), int(hand_['13']['y']+y)),(int(hand_['14']['x']+x), int(hand_['14']['y']+y)), colors[3], thick)cv2.line(img_, (int(hand_['14']['x']+x), int(hand_['14']['y']+y)),(int(hand_['15']['x']+x), int(hand_['15']['y']+y)), colors[3], thick)cv2.line(img_, (int(hand_['15']['x']+x), int(hand_['15']['y']+y)),(int(hand_['16']['x']+x), int(hand_['16']['y']+y)), colors[3], thick)cv2.line(img_, (int(hand_['0']['x']+x), int(hand_['0']['y']+y)),(int(hand_['17']['x']+x), int(hand_['17']['y']+y)), colors[4], thick)cv2.line(img_, (int(hand_['17']['x']+x), int(hand_['17']['y']+y)),(int(hand_['18']['x']+x), int(hand_['18']['y']+y)), colors[4], thick)cv2.line(img_, (int(hand_['18']['x']+x), int(hand_['18']['y']+y)),(int(hand_['19']['x']+x), int(hand_['19']['y']+y)), colors[4], thick)cv2.line(img_, (int(hand_['19']['x']+x), int(hand_['19']['y']+y)),(int(hand_['20']['x']+x), int(hand_['20']['y']+y)), colors[4], thick)
'''
function: 21个三维关键点转为二维点，并进行绘制
'''
def Draw_KeyPoints3D(img,Joints_,fx,fy,cx,cy):#----------------------------------- 计算 3D到 2D相机的投影X = Joints_[:,0]Y = Joints_[:,1]Z = Joints_[:,2]x_p = X / Zy_p = Y / Z#三维点转为二维点x_2d = fx* x_p + cxy_2d = fy* y_p + cypts2d_list = {}pts2d_ss = []for ii in range(x_2d.shape[0]):x_,y_ = x_2d[ii],y_2d[ii]pts2d_list[str(ii)]={"x":x_,"y":y_}cv2.circle(img, (int(x_),int(y_)), 4, (25,155,255), -1)cv2.circle(img, (int(x_),int(y_)), 2, (255,0,55), -1)pts2d_ss.append((x_,y_))draw_joints(img,pts2d_list,0,0)pts2d_ss = np.array(pts2d_ss)return pts2d_ssdef Draw_Vertex_KeyPoints(img,img_mesh,Vertex,fx_d,fy_d,cx_d,cy_d,triangles_index,RGB_ = (245, 125, 35)):#----------------------------------- 计算 Mano 到 相机的投影Xdc = -Vertex[:,0].reshape(-1)Ydc = -Vertex[:,1].reshape(-1)Zdc = -Vertex[:,2].reshape(-1)x_mano_p = Xdc / Zdcy_mano_p = Ydc / Zdc#点云转为二维图x_mano = fx_d* x_mano_p + cx_dy_mano = fy_d* y_mano_p + cy_dmanopts_list = []mesh_list = []color_rr = (random.randint(100,230),random.randint(120,250),random.randint(100,240))for ii in range(triangles_index.shape[0]):a,b,c = triangles_index[ii]x1_,y1_ = x_mano[a].astype(np.int32),y_mano[a].astype(np.int32)x2_,y2_ = x_mano[b].astype(np.int32),y_mano[b].astype(np.int32)x3_,y3_ = x_mano[c].astype(np.int32),y_mano[c].astype(np.int32)area_ = np.array([[int(x1_), int(y1_)], [int(x2_), int(y2_)], [int(x3_),int(y3_)]])color_ = (255, 0, 0)# cv2.fillPoly(mask_v, [area_], (255))cv2.fillPoly(img_mesh, [area_], color_rr)mesh_list.append(area_)cv2.fillPoly(img, mesh_list, RGB_)
if __name__ == '__main__':path_root = "datasets/"path_s_image = "{}/image/".format(path_root)path_s_label = "{}/label/".format(path_root)triangles_index = np.load("../../config/triangles_index.npy").reshape(-1,3)out_cnt = 0hand_cnt = 0for f_ in os.listdir(path_s_image):path_img = path_s_image + f_path_json = path_s_label + f_.replace(".jpg",".json")with open(path_json, 'r', encoding='utf-8') as file:data_json = json.load(file)hands_json = data_json["hands"]cx,cy,fx,fy = data_json["cx"],data_json["cy"],data_json["fx"],data_json["fy"]img_ = cv2.imread(path_img)img_joint = img_.copy()img_mesh = img_.copy()img_mask = np.zeros(img_.shape).astype(np.uint8)img_mask[:,:,:]=255for msg_ in hands_json:RGB_ = (245, 55, 133)if msg_["label"] == "left":RGB_ = (25, 255, 133)Joints3D = np.array(msg_["joint3d"])Vertex3D = np.array(msg_["vertex3d"])pts2d_ss = Draw_KeyPoints3D(img_joint,Joints3D,fx,fy,cx,cy)Draw_Vertex_KeyPoints(img_mesh,img_mask,Vertex3D,fx,fy,cx,cy,triangles_index,RGB_ = RGB_)hand_cnt += 1stk_1 = np.hstack((img_,img_joint))stk_2 = np.hstack((img_mesh,img_mask))stk_ = np.vstack((stk_1,stk_2))cv2.namedWindow("img_stk",0)cv2.imshow("img_stk",stk_)out_cnt += 1print("--------->>>imgs_num : [{}] , hands_num: [{}]".format(out_cnt,hand_cnt))key_id = cv2.waitKey(0)cv2.imwrite("f1.jpg",stk_)if key_id == 27:break