import matplotlib.pyplot as plt import matplotlib.cm as cm import matplotlib.animation as animation from mpl_toolkits.mplot3d import Axes3D import os import json import argparse import math import numpy as np import cv2 import math import sys sys.path.insert(1, '../utils') from links import joint_correspondence, joint_correspondence_human36m, links_evaluation, links_evaluation_human36m, \ links_evaluation_human36m_mediapipe, joint_correspondence_human36m_mediapipe, links_mpi_inf_3dhp, \ joints_mpi_inf_3dhp def main(): ap = argparse.ArgumentParser() ap.add_argument("-dataset", "--dataset_name", help="Dataset name. Datasets must be inside hpe/images/. Please use -dataset human36m to optimize Human 3.6M.", type=str, default='mpi') ap.add_argument("-s", "--section", help="Human 3.6M section to optimize. Only works when the dataset is set to human36m", type=str, default='S1') ap.add_argument("-a", "--action", help="Human 3.6M action to optimize. Only works when the dataset is set to human36m", type=str, default='Directions-1') ap.add_argument("-seq", "--sequence", help="MPI sequence optimize. Only works when the dataset is set to human36m", type=str, default='Seq1') ap.add_argument("-2d_detector", "--2d_detector", help="2D detector used for 2D human pose estimation. Current options: openpose (default), mediapipe", type=str, default='groundtruth') ap.add_argument("-fp", "--file_poses", help="Name of file containing 3d poses", type=str, default='poses3d_gt2.json') args = vars(ap.parse_args()) # -------------------------------------------------------- # Loading files, and verifications configurations # -------------------------------------------------------- dataset_folder = '../../images/mpi-inf-3dhp/' + args['section'] + '/' + args['sequence'] + '/' links_evaluation = links_mpi_inf_3dhp # check if dataset folder exists: if not os.path.exists(dataset_folder): raise Exception("The dataset folder does not exist!") ground_truth_path = dataset_folder + "ground_truth.txt" if os.path.exists(ground_truth_path): with open(ground_truth_path, "r") as fp: ground_truth = json.load(fp) else: raise Exception("The ground truth file does not exist!") poses_path = dataset_folder + args['file_poses'] if os.path.exists(poses_path): with open(poses_path, "r") as fp: poses_3d = json.load(fp) else: raise Exception("The 3D poses file does not exist!") ground_truth_path = dataset_folder + "ground_truth.txt" if os.path.exists(ground_truth_path): with open(ground_truth_path, "r") as fp: ground_truth = json.load(fp) else: raise Exception("The ground truth file does not exist!") frames_total = 10000000000 n_frames_camera = len(poses_3d) if n_frames_camera < frames_total: frames_total = n_frames_camera fig = plt.figure() ax1 = fig.add_subplot(1, 1, 1, projection='3d') ax1.set_title("3D pose") # ax1.set_xlim3d(-1, 1) # ax1.set_ylim3d(-3, -1) # ax1.set_zlim3d(0, 2) ax1.set_zlim3d(0, 5000) ax1.set_xlabel('x') ax1.set_ylabel('y') ax1.set_zlabel('z') ax1.view_init(azim=90, elev=-50) Xtotal = [] Ytotal = [] Ztotal = [] Xtotal_gt = [] Ytotal_gt = [] Ztotal_gt = [] colors_total = [] xltotal = [] yltotal = [] zltotal = [] for frame_key, frame in poses_3d.items(): X_vec = [] Y_vec = [] Z_vec = [] joint_colors = [] xlines = [] ylines = [] zlines = [] min_z = 1000 for joint_key, joint in frame.items(): point = poses_3d[frame_key][joint_key] b, g, r = tuple(c / 255 for c in point['color']) joint_colors.append((r, g, b)) X_vec.append(point['X']) Y_vec.append(point['Y']) Z_vec.append(point['Z']) # if args['has_ground_truth']: # X_vec_gt = [] # Y_vec_gt = [] # Z_vec_gt = [] # for joint_key, joint in ground_truth[frame_key].items(): # point = ground_truth[frame_key][joint_key]['pose'] # X_vec_gt.append(float(point['x'])) # Y_vec_gt.append(float(point['y'])) # Z_vec_gt.append(float(point['z'])) # # Xtotal_gt.append(X_vec_gt) # Ytotal_gt.append(Y_vec_gt) # Ztotal_gt.append(Z_vec_gt) Xtotal.append(X_vec) Ytotal.append(Y_vec) Ztotal.append(Z_vec) colors_total.append(joint_colors) for link_name, link in links_mpi_inf_3dhp.items(): joint0 = poses_3d[frame_key][link['parent']] joint1 = poses_3d[frame_key][link['child']] X0 = joint0['X'] Y0 = joint0['Y'] Z0 = joint0['Z'] X1 = joint1['X'] Y1 = joint1['Y'] Z1 = joint1['Z'] xlines.append([X0, X1]) ylines.append([Y0, Y1]) zlines.append([Z0, Z1]) # if args['has_ground_truth']: # xlines_gt = [] # ylines_gt = [] # zlines_gt = [] # # for link_name, link in links_mpi_inf_3dhp.items(): # joint0 = ground_truth[frame_key][link['parent']]['pose'] # joint1 = ground_truth[frame_key][link['child']]['pose'] # X0 = joint0['x'] # Y0 = joint0['y'] # Z0 = joint0['z'] # X1 = joint1['x'] # Y1 = joint1['y'] # Z1 = joint1['z'] # xlines_gt.append([X0, X1]) # ylines_gt.append([Y0, Y1]) # zlines_gt.append([Z0, Z1]) # # xltotal_gt.append(xlines_gt) # yltotal_gt.append(ylines_gt) # zltotal_gt.append(zlines_gt) xltotal.append(xlines) yltotal.append(ylines) zltotal.append(zlines) # print(frames_total) # exit(0) def update_plot(frames): i = frames ax1.clear() # ax1.set_title("3D pose") maxZ=0 maxX=0 maxY=0 ax1.set_xlim3d(-1000, 2000) ax1.set_ylim3d(0, 2000) ax1.set_zlim3d(-1000, 1000) # ax1.set_xlabel('x', fontsize=20) # ax1.set_ylabel('y', fontsize=20) # ax1.set_zlabel('z', fontsize=20) plt.setp(ax1.get_xticklabels(), visible=False) plt.setp(ax1.get_yticklabels(), visible=False) plt.setp(ax1.get_zticklabels(), visible=False) # loc = plticker.MultipleLocator(base=1) # this locator puts ticks at regular intervals # ax1.xaxis.set_major_locator(loc) # ax1.yaxis.set_major_locator(loc) # ax1.zaxis.set_major_locator(loc) # ax1.axis('off') if 0 <= i < len(Ztotal): # continue # z_min = min(Ztotal[i]) # ax1.set_zlim3d(z_min, z_min + 2) # print(z_min) # draw3Dcoordinatesystem(ax1, [], xc=0, yc=0, zc=min_z, size=0.5) ax1.scatter(Xtotal[i], Ytotal[i], Ztotal[i], c=colors_total[i]) for n in range(0, len(xltotal[i]) - 1): ax1.plot(xltotal[i][n], yltotal[i][n], zltotal[i][n], c=(0.5, 0.5, 0.5)) # if args['has_ground_truth']: # ax1.scatter(Xtotal_gt[i], Ytotal_gt[i], Ztotal_gt[i], c='k') # # for n in range(0, len(xltotal_gt[i]) - 1): # ax1.plot(xltotal_gt[i][n], yltotal_gt[i][n], zltotal_gt[i][n], c=(0, 0, 0)) ani = animation.FuncAnimation(fig, update_plot, frames=frames_total, interval=100, repeat=False) # plt.pause(1) # plt.show() ani.save(dataset_folder + '3d_2.mp4', bitrate=1000) if __name__ == "__main__": main()