from models.rotation2xyz import Rotation2xyz import numpy as np from trimesh import Trimesh import os os.environ['PYOPENGL_PLATFORM'] = "osmesa" import torch from visualize.simplify_loc2rot import joints2smpl import pyrender import matplotlib.pyplot as plt import io import imageio from shapely import geometry import trimesh from pyrender.constants import RenderFlags import math # import ffmpeg from PIL import Image class WeakPerspectiveCamera(pyrender.Camera): def __init__(self, scale, translation, znear=pyrender.camera.DEFAULT_Z_NEAR, zfar=None, name=None): super(WeakPerspectiveCamera, self).__init__( znear=znear, zfar=zfar, name=name, ) self.scale = scale self.translation = translation def get_projection_matrix(self, width=None, height=None): P = np.eye(4) P[0, 0] = self.scale[0] P[1, 1] = self.scale[1] P[0, 3] = self.translation[0] * self.scale[0] P[1, 3] = -self.translation[1] * self.scale[1] P[2, 2] = -1 return P def render(motions, outdir='test_vis', device_id=0, name=None, pred=True): frames, njoints, nfeats = motions.shape MINS = motions.min(axis=0).min(axis=0) MAXS = motions.max(axis=0).max(axis=0) height_offset = MINS[1] motions[:, :, 1] -= height_offset trajec = motions[:, 0, [0, 2]] j2s = joints2smpl(num_frames=frames, device_id=0, cuda=True) rot2xyz = Rotation2xyz(device=torch.device("cuda:0")) faces = rot2xyz.smpl_model.faces if (not os.path.exists(outdir + name+'_pred.pt') and pred) or (not os.path.exists(outdir + name+'_gt.pt') and not pred): print(f'Running SMPLify, it may take a few minutes.') motion_tensor, opt_dict = j2s.joint2smpl(motions) # [nframes, njoints, 3] vertices = rot2xyz(torch.tensor(motion_tensor).clone(), mask=None, pose_rep='rot6d', translation=True, glob=True, jointstype='vertices', vertstrans=True) if pred: torch.save(vertices, outdir + name+'_pred.pt') else: torch.save(vertices, outdir + name+'_gt.pt') else: if pred: vertices = torch.load(outdir + name+'_pred.pt') else: vertices = torch.load(outdir + name+'_gt.pt') frames = vertices.shape[3] # shape: 1, nb_frames, 3, nb_joints print (vertices.shape) MINS = torch.min(torch.min(vertices[0], axis=0)[0], axis=1)[0] MAXS = torch.max(torch.max(vertices[0], axis=0)[0], axis=1)[0] # vertices[:,:,1,:] -= MINS[1] + 1e-5 out_list = [] minx = MINS[0] - 0.5 maxx = MAXS[0] + 0.5 minz = MINS[2] - 0.5 maxz = MAXS[2] + 0.5 polygon = geometry.Polygon([[minx, minz], [minx, maxz], [maxx, maxz], [maxx, minz]]) polygon_mesh = trimesh.creation.extrude_polygon(polygon, 1e-5) vid = [] for i in range(frames): if i % 10 == 0: print(i) mesh = Trimesh(vertices=vertices[0, :, :, i].squeeze().tolist(), faces=faces) base_color = (0.11, 0.53, 0.8, 0.5) ## OPAQUE rendering without alpha ## BLEND rendering consider alpha material = pyrender.MetallicRoughnessMaterial( metallicFactor=0.7, alphaMode='OPAQUE', baseColorFactor=base_color ) mesh = pyrender.Mesh.from_trimesh(mesh, material=material) polygon_mesh.visual.face_colors = [0, 0, 0, 0.21] polygon_render = pyrender.Mesh.from_trimesh(polygon_mesh, smooth=False) bg_color = [1, 1, 1, 0.8] scene = pyrender.Scene(bg_color=bg_color, ambient_light=(0.4, 0.4, 0.4)) sx, sy, tx, ty = [0.75, 0.75, 0, 0.10] camera = pyrender.PerspectiveCamera(yfov=(np.pi / 3.0)) light = pyrender.DirectionalLight(color=[1,1,1], intensity=300) scene.add(mesh) c = np.pi / 2 scene.add(polygon_render, pose=np.array([[ 1, 0, 0, 0], [ 0, np.cos(c), -np.sin(c), MINS[1].cpu().numpy()], [ 0, np.sin(c), np.cos(c), 0], [ 0, 0, 0, 1]])) light_pose = np.eye(4) light_pose[:3, 3] = [0, -1, 1] scene.add(light, pose=light_pose.copy()) light_pose[:3, 3] = [0, 1, 1] scene.add(light, pose=light_pose.copy()) light_pose[:3, 3] = [1, 1, 2] scene.add(light, pose=light_pose.copy()) c = -np.pi / 6 scene.add(camera, pose=[[ 1, 0, 0, (minx+maxx).cpu().numpy()/2], [ 0, np.cos(c), -np.sin(c), 1.5], [ 0, np.sin(c), np.cos(c), max(4, minz.cpu().numpy()+(1.5-MINS[1].cpu().numpy())*2, (maxx-minx).cpu().numpy())], [ 0, 0, 0, 1] ]) # render scene r = pyrender.OffscreenRenderer(960, 960) color, _ = r.render(scene, flags=RenderFlags.RGBA) # Image.fromarray(color).save(outdir+name+'_'+str(i)+'.png') vid.append(color) r.delete() out = np.stack(vid, axis=0) if pred: imageio.mimsave(outdir + name+'_pred.gif', out, fps=20) else: imageio.mimsave(outdir + name+'_gt.gif', out, fps=20) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser() parser.add_argument("--filedir", type=str, default='/CV/xhr/xhr_project/Paper/text2Pose/t2m/T2M-GPT-main/visualization/pose_np', help='motion npy file dir') parser.add_argument('--motion-list', default=None, nargs="1", type=str, help="motion name list") args = parser.parse_args() filename_list = args.motion_list filedir = args.filedir for filename in filename_list: motions = np.load(filedir + filename+'.npy') print('pred', motions.shape, filename) render(motions[0], outdir=filedir, device_id=0, name=filename, pred=True) # motions = np.load(filedir + filename+'_pred.npy') # print('pred', motions.shape, filename) # render(motions[0], outdir=filedir, device_id=0, name=filename, pred=True) # motions = np.load(filedir + filename+'_gt.npy') # print('gt', motions.shape, filename) # render(motions[0], outdir=filedir, device_id=0, name=filename, pred=False)