🚀 update 3d visualization code

This commit is contained in:
shuaiqing 2021-01-25 19:37:23 +08:00
parent ba6e58d56e
commit ceba363dcb
10 changed files with 2596 additions and 18 deletions

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@ -2,7 +2,7 @@
* @Date: 2021-01-13 20:32:12
* @Author: Qing Shuai
* @LastEditors: Qing Shuai
* @LastEditTime: 2021-01-24 22:11:37
* @LastEditTime: 2021-01-25 19:35:14
* @FilePath: /EasyMocapRelease/Readme.md
-->
# EasyMocap
@ -74,10 +74,14 @@ out=path/to/output
python3 scripts/preprocess/extract_video.py ${data}
# 1. example for skeleton reconstruction
python3 code/demo_mv1pmf_skel.py ${data} --out ${out} --vis_det --vis_repro --undis --sub_vis 1 7 13 19
# 2. example for SMPL reconstruction
# 2.1 example for SMPL reconstruction
python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --end 300 --vis_smpl --undis --sub_vis 1 7 13 19 --gender male
# 2. example for SMPL-X reconstruction
# 2.2 example for SMPL-X reconstruction
python3 code/demo_mv1pmf_smpl.py ${data} --out ${out} --undis --body bodyhandface --sub_vis 1 7 13 19 --start 400 --model smplx --vis_smpl --gender male
# 3.1 example for rendering SMPLX to ${out}/smpl
python3 code/vis_render.py ${data} --out ${out} --skel ${out}/smpl --model smplx --gender male --undis --start 400 --sub_vis 1
# 3.2 example for rendering skeleton of SMPL to ${out}/smplskel
python3 code/vis_render.py ${data} --out ${out} --skel ${out}/smpl --model smplx --gender male --undis --start 400 --sub_vis 1 --type smplskel --body bodyhandface
```
## Not Quick Start

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@ -2,8 +2,8 @@
@ Date: 2021-01-13 16:53:55
@ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-24 22:27:01
@ FilePath: /EasyMocapRelease/code/dataset/base.py
@ LastEditTime: 2021-01-25 19:12:34
@ FilePath: /EasyMocap/code/dataset/base.py
'''
import os
import json
@ -351,6 +351,8 @@ class MVBase(Dataset):
self.mode = mode
self.undis = undis
self.no_img = no_img
# use when debug
self.ret_crop = False
self.config = config
# results path
# the results store keypoints3d
@ -425,6 +427,18 @@ class MVBase(Dataset):
images.append(img)
# TODO:这里直接取了0
annot = read_annot(annname, self.mode)
if self.ret_crop:
for det in annot:
bbox = det['bbox']
l, t, r, b = det['bbox'][:4]
l = max(0, int(l+0.5))
t = max(0, int(t+0.5))
r = min(img.shape[1], int(r+0.5))
b = min(img.shape[0], int(b+0.5))
det['bbox'][:4] = [l, t, r, b]
crop_img = img[t:b, l:r, :]
crop_img = cv2.resize(crop_img, (128, 256))
det['crop'] = crop_img
annots.append(annot)
if self.undis:
images = self.undistort(images)
@ -465,6 +479,29 @@ class MVBase(Dataset):
results.append(result)
self.writer.write_smpl(results, nf)
def vis_smpl(self, peopleDict, faces, images, nf, sub_vis=[],
mode='smpl', extra_data=[], add_back=True):
# render the smpl to each view
render_data = {}
for pid, data in peopleDict.items():
render_data[pid] = {
'vertices': data.vertices, 'faces': faces,
'vid': pid, 'name': 'human_{}_{}'.format(nf, pid)}
for iid, extra in enumerate(extra_data):
render_data[10000+iid] = {
'vertices': extra['vertices'],
'faces': extra['faces'],
'colors': extra['colors'],
'name': extra['name']
}
cameras = {'K': [], 'R':[], 'T':[]}
if len(sub_vis) == 0:
sub_vis = self.cams
for key in cameras.keys():
cameras[key] = [self.cameras[cam][key] for cam in sub_vis]
images = [images[self.cams.index(cam)] for cam in sub_vis]
self.writer.vis_smpl(render_data, nf, images, cameras, mode, add_back=add_back)
def read_skel(self, nf, mode='none'):
if mode == 'a4d':
outname = join(self.skel_path, '{}.txt'.format(nf))

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@ -2,7 +2,7 @@
@ Date: 2021-01-12 17:08:25
@ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-24 22:26:09
@ LastEditTime: 2021-01-25 19:32:44
@ FilePath: /EasyMocapRelease/code/demo_mv1pmf_smpl.py
'''
# show skeleton and reprojection
@ -23,10 +23,7 @@ def load_weight_shape():
def load_weight_pose(model):
if model == 'smpl':
weight = {
'k3d': 1., 'reg_poses_zero': 1e-2,
'reg_expression': 1e-1,
'smooth_joints': 1e-5
# 'smooth_Rh': 1e-1, 'smooth_Th': 1e-1, 'smooth_poses': 1e-1, 'smooth_hands': 1e-2
'k3d': 1., 'reg_poses_zero': 1e-2, 'smooth_body': 1e-2
}
elif model == 'smplh':
weight = {
@ -38,7 +35,6 @@ def load_weight_pose(model):
'k3d': 1., 'reg_poses_zero': 1e-3,
'reg_expression': 1e-2,
'smooth_body': 1e-2, 'smooth_hand': 1e-2
# 'smooth_Rh': 1e-1, 'smooth_Th': 1e-1, 'smooth_poses': 1e-1, 'smooth_hands': 1e-2
}
else:
raise NotImplementedError

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@ -2,8 +2,8 @@
* @ Date: 2020-09-14 11:01:52
* @ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-24 22:28:09
@ FilePath: /EasyMocapRelease/code/mytools/reconstruction.py
@ LastEditTime: 2021-01-25 16:06:41
@ FilePath: /EasyMocap/code/mytools/reconstruction.py
'''
import numpy as np
@ -72,14 +72,14 @@ def simple_recon_person(keypoints_use, Puse, config=None, ret_repro=False):
# 计算重投影误差
kpts_repro = projectN3(out, Puse)
square_diff = (keypoints_use[:, :, :2] - kpts_repro[:, :, :2])**2
# conf = (out[None, :, -1] > 0.01) * (keypoints_use[:, :, 2] > 0.01)
conf = np.repeat(out[None, :, -1:], len(Puse), 0)
kpts_repro = np.concatenate((kpts_repro, conf), axis=2)
if conf.sum() < 3: # 至少得有3个有效的关节
repro_error = 1e3
else:
conf2d = conf *(keypoints_use[:, :, -1:] > 0.01)
# (nViews, nJoints): reprojection error for each joint in each view
repro_error_joint = np.sqrt(square_diff.sum(axis=2, keepdims=True))*conf
repro_error_joint = np.sqrt(square_diff.sum(axis=2, keepdims=True))*conf2d
# remove the not valid joints
# remove the bad views
repro_error = repro_error_joint.sum()/conf.sum()

97
code/vis_render.py Normal file
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@ -0,0 +1,97 @@
'''
@ Date: 2021-01-17 21:14:50
@ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-25 19:34:46
@ FilePath: /EasyMocapRelease/code/vis_render.py
'''
# visualize the results by pyrender
import pyrender # first import the pyrender
from collections import namedtuple
from dataset.base import MVBase
from dataset.config import CONFIG
import numpy as np
from tqdm import tqdm
from visualize.geometry import create_ground
Person = namedtuple('Person', ['vertices', 'keypoints3d'])
def inBound(keypoints3d, bound):
if bound is None:
return True
valid = np.where(keypoints3d[:, -1] > 0.01)[0]
kpts = keypoints3d[valid]
crit = (kpts[:, 0] > bound[0][0]) & (kpts[:, 0] < bound[1][0]) &\
(kpts[:, 1] > bound[0][1]) & (kpts[:, 1] < bound[1][1]) &\
(kpts[:, 2] > bound[0][2]) & (kpts[:, 2] < bound[1][2])
if crit.sum()/crit.shape[0] < 0.8:
return False
else:
return True
def visualize(path, sub, out, mode, rend_type, args):
config = CONFIG[mode]
no_img = False
dataset = MVBase(path, cams=sub, config=config,
undis=args.undis, no_img=no_img, out=out)
dataset.skel_path = args.skel
if rend_type in ['skel']:
from visualize.skelmodel import SkelModel
body_model = SkelModel(config['nJoints'], config['kintree'])
elif rend_type in ['mesh']:
from smplmodel import load_model
body_model = load_model(args.gender, model_type=args.model)
smpl_model = body_model
elif rend_type == 'smplskel':
from smplmodel import load_model
smpl_model = load_model(args.gender, model_type=args.model)
from visualize.skelmodel import SkelModel
body_model = SkelModel(config['nJoints'], config['kintree'])
dataset.writer.save_origin = args.save_origin
start, end = args.start, min(args.end, len(dataset))
bound = None
if args.scene == 'none':
ground = create_ground(step=0.5)
elif args.scene == 'hw':
ground = create_ground(step=1, xrange=14, yrange=10, two_sides=False)
bound = [[0, 0, 0], [14, 10, 2.5]]
else:
ground = create_ground(step=1, xrange=28, yrange=15, two_sides=False)
for nf in tqdm(range(start, end), desc='rendering'):
images, annots = dataset[nf]
if rend_type == 'skel':
infos = dataset.read_skel(nf)
else:
infos = dataset.read_smpl(nf)
# body_model: input: keypoints3d/smpl params, output: vertices, (colors)
# The element of peopleDict must have `id`, `vertices`
peopleDict = {}
for info in infos:
if rend_type == 'skel':
joints = info['keypoints3d']
else:
joints = smpl_model(return_verts=False, return_tensor=False, **info)[0]
if not inBound(joints, bound):
continue
if rend_type == 'smplskel':
joints = smpl_model(return_verts=False, return_tensor=False, **info)[0]
joints = np.hstack([joints, np.ones((joints.shape[0], 1))])
info_new = {'id': info['id'], 'keypoints3d': joints}
vertices = body_model(return_verts=True, return_tensor=False, **info_new)[0]
else:
vertices = body_model(return_verts=True, return_tensor=False, **info)[0]
peopleDict[info['id']] = Person(vertices=vertices, keypoints3d=None)
dataset.vis_smpl(peopleDict, faces=body_model.faces, images=images, nf=nf,
sub_vis=args.sub_vis, mode=rend_type, extra_data=[ground], add_back=args.add_back)
if __name__ == "__main__":
from mytools.cmd_loader import load_parser
parser = load_parser()
parser.add_argument('--type', type=str, default='mesh', choices=['skel', 'mesh', 'smplskel'])
parser.add_argument('--scene', type=str, default='none', choices=['none', 'zjub', 'hw'])
parser.add_argument('--skel', type=str, default=None)
parser.add_argument('--add_back', action='store_true')
parser.add_argument('--save_origin', action='store_true')
args = parser.parse_args()
visualize(args.path, args.sub, args.out, args.body, args.type, args)

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@ -0,0 +1,82 @@
'''
@ Date: 2021-01-17 22:44:34
@ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-25 19:14:20
@ FilePath: /EasyMocapRelease/code/visualize/geometry.py
'''
import numpy as np
import cv2
import numpy as np
def create_ground(
center=[0, 0, 0], xdir=[1, 0, 0], ydir=[0, 1, 0], # 位置
step=1, xrange=10, yrange=10, # 尺寸
white=[1., 1., 1.], black=[0.,0.,0.], # 颜色
two_sides=True
):
if isinstance(center, list):
center = np.array(center)
xdir = np.array(xdir)
ydir = np.array(ydir)
xdir = xdir * step
ydir = ydir * step
vertls, trils, colls = [],[],[]
cnt = 0
min_x = -xrange if two_sides else 0
min_y = -yrange if two_sides else 0
for i in range(min_x, xrange+1):
for j in range(min_y, yrange+1):
point0 = center + i*xdir + j*ydir
point1 = center + (i+1)*xdir + j*ydir
point2 = center + (i+1)*xdir + (j+1)*ydir
point3 = center + (i)*xdir + (j+1)*ydir
if (i%2==0 and j%2==0) or (i%2==1 and j%2==1):
col = white
else:
col = black
vert = np.stack([point0, point1, point2, point3])
col = np.stack([col for _ in range(vert.shape[0])])
tri = np.array([[2, 3, 0], [0, 1, 2]]) + vert.shape[0] * cnt
cnt += 1
vertls.append(vert)
trils.append(tri)
colls.append(col)
vertls = np.vstack(vertls)
trils = np.vstack(trils)
colls = np.vstack(colls)
return {'vertices': vertls, 'faces': trils, 'colors': colls, 'name': 'ground'}
def get_rotation_from_two_directions(direc0, direc1):
direc0 = direc0/np.linalg.norm(direc0)
direc1 = direc1/np.linalg.norm(direc1)
rotdir = np.cross(direc0, direc1)
if np.linalg.norm(rotdir) < 1e-2:
return np.eye(3)
rotdir = rotdir/np.linalg.norm(rotdir)
rotdir = rotdir * np.arccos(np.dot(direc0, direc1))
rotmat, _ = cv2.Rodrigues(rotdir)
return rotmat
def create_plane(normal, point, width=1, height=1, depth=0.005):
mesh_box = TriangleMesh.create_box(width=2*width, height=2*height, depth=2*depth)
mesh_box.paint_uniform_color([0.8, 0.8, 0.8])
# 根据normal计算旋转
rotmat = get_rotation_from_two_directions(np.array([0, 0, 1]), normal[0])
transform0 = np.eye(4)
transform0[0, 3] = -width
transform0[1, 3] = -height
transform0[2, 3] = -depth
transform = np.eye(4)
transform[:3, :3] = rotmat
transform[0, 3] = point[0, 0]
transform[1, 3] = point[0, 1]
transform[2, 3] = point[0, 2]
mesh_box.transform(transform @ transform0)
return {'vertices': np.asarray(mesh_box.vertices), 'faces': np.asarray(mesh_box.triangles), 'colors': np.asarray(mesh_box.vertex_colors), 'name': 'ground'}
faces = np.loadtxt('./code/visualize/sphere_faces_20.txt', dtype=np.int)
vertices = np.loadtxt('./code/visualize/sphere_vertices_20.txt')
colors = np.ones((vertices.shape[0], 3))
return {'vertices': vertices, 'faces': faces, 'colors': colors, 'name': 'ground'}

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'''
@ Date: 2021-01-17 21:38:19
@ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-22 23:08:18
@ FilePath: /EasyMocap/code/visualize/skelmodel.py
'''
import numpy as np
import cv2
def calTransformation(v_i, v_j, r, adaptr=False, ratio=10):
""" from to vertices to T
Arguments:
v_i {} -- [description]
v_j {[type]} -- [description]
"""
xaxis = np.array([1, 0, 0])
v = (v_i + v_j)/2
direc = (v_i - v_j)
length = np.linalg.norm(direc)
direc = direc/length
rotdir = np.cross(xaxis, direc)
rotdir = rotdir/np.linalg.norm(rotdir)
rotdir = rotdir * np.arccos(np.dot(direc, xaxis))
rotmat, _ = cv2.Rodrigues(rotdir)
# set the minimal radius for the finger and face
shrink = max(length/ratio, 0.005)
eigval = np.array([[length/2/r, 0, 0], [0, shrink, 0], [0, 0, shrink]])
T = np.eye(4)
T[:3,:3] = rotmat @ eigval @ rotmat.T
T[:3, 3] = v
return T, r, length
class SkelModel:
def __init__(self, nJoints, kintree) -> None:
self.nJoints = nJoints
self.kintree = kintree
faces = np.loadtxt('./code/visualize/sphere_faces_20.txt', dtype=np.int)
self.vertices = np.loadtxt('./code/visualize/sphere_vertices_20.txt')
# compose faces
faces_all = []
for nj in range(nJoints):
faces_all.append(faces + nj*self.vertices.shape[0])
for nk in range(len(kintree)):
faces_all.append(faces + nJoints*self.vertices.shape[0] + nk*self.vertices.shape[0])
self.faces = np.vstack(faces_all)
def __call__(self, keypoints3d, id=0, return_verts=True, return_tensor=False):
vertices_all = []
r = 0.02
# joints
for nj in range(self.nJoints):
if nj > 25:
r_ = r * 0.4
else:
r_ = r
if keypoints3d[nj, -1] < 0.01:
vertices_all.append(self.vertices*0.001)
continue
vertices_all.append(self.vertices*r_ + keypoints3d[nj:nj+1, :3])
# limb
for nk, (i, j) in enumerate(self.kintree):
if keypoints3d[i][-1] < 0.1 or keypoints3d[j][-1] < 0.1:
vertices_all.append(self.vertices*0.001)
continue
T, _, length = calTransformation(keypoints3d[i, :3], keypoints3d[j, :3], r=1)
if length > 2: # 超过两米的
vertices_all.append(self.vertices*0.001)
continue
vertices = self.vertices @ T[:3, :3].T + T[:3, 3:].T
vertices_all.append(vertices)
vertices = np.vstack(vertices_all)
return vertices[None, :, :]

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View File

@ -2,7 +2,7 @@
@ Date: 2021-01-13 20:38:33
@ Author: Qing Shuai
@ LastEditors: Qing Shuai
@ LastEditTime: 2021-01-22 20:45:37
@ LastEditTime: 2021-01-25 14:41:56
@ FilePath: /EasyMocap/scripts/preprocess/extract_video.py
'''
import os, sys
@ -16,7 +16,7 @@ sys.path.append(code_path)
mkdir = lambda x: os.makedirs(x, exist_ok=True)
def extract_video(videoname, path, start=0, end=10000, step=1):
def extract_video(videoname, path, start, end, step):
base = os.path.basename(videoname).replace('.mp4', '')
if not os.path.exists(videoname):
return base
@ -193,6 +193,12 @@ if __name__ == "__main__":
default='/media/qing/Project/openpose')
parser.add_argument('--render', action='store_true', help='use to render the openpose 2d')
parser.add_argument('--no2d', action='store_true')
parser.add_argument('--start', type=int, default=0,
help='frame start')
parser.add_argument('--end', type=int, default=10000,
help='frame end')
parser.add_argument('--step', type=int, default=1,
help='frame step')
parser.add_argument('--debug', action='store_true')
args = parser.parse_args()
mode = args.mode
@ -201,7 +207,7 @@ if __name__ == "__main__":
videos = sorted(glob(join(args.path, 'videos', '*.mp4')))
subs = []
for video in videos:
basename = extract_video(video, args.path)
basename = extract_video(video, args.path, start=args.start, end=args.end, step=args.step)
subs.append(basename)
print('cameras: ', ' '.join(subs))
if not args.no2d: