389 lines
16 KiB
Python
389 lines
16 KiB
Python
from tqdm import tqdm
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import cv2
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import os
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from easymocap.visualize.pyrender_wrapper import plot_meshes
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from os.path import join
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import numpy as np
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from easymocap.datasets.base import add_logo
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from easymocap.mytools.vis_base import merge, plot_bbox
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from .vis import VisBase
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class Render(VisBase):
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def __init__(self, name='render', scale=0.5, backend='pyrender', **kwargs) -> None:
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super().__init__(name=name, scale=1., **kwargs)
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self.scale3d = scale
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def __call__(self, body_model, params, cameras, imgnames):
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vertices = body_model.vertices(params, return_tensor=False)
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faces = body_model.faces
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for nf, img in enumerate(tqdm(imgnames, desc=self.name)):
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basename = os.path.basename(img)
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# 重新读入图片
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assert os.path.exists(img), img
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vis = cv2.imread(img)
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vis = cv2.resize(vis, None, fx=self.scale3d, fy=self.scale3d)
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vert = vertices[nf]
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meshes = {}
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meshes[0] = {
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'vertices': vert,
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'faces': faces,
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'id': 0,
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'name': 'human_{}'.format(0)
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}
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K = cameras['K'][nf].copy()
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K[:2, :] *= self.scale3d
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R = cameras['R'][nf]
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T = cameras['T'][nf]
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ret = plot_meshes(vis, meshes, K, R, T, mode='image')
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self.merge_and_write([ret])
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class Render_multiview(VisBase):
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def __init__(self, view_list=[], name='render', model_name='body_model', render_mode='image', backend='pyrender', shape=[-1,-1], scale=1., **kwargs):
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self.scale3d = scale
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super().__init__(name=name, scale=1., **kwargs)
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self.view_list = view_list
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self.render_mode = render_mode
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self.model_name = model_name
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self.shape = shape
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def render_(self, vertices, faces, cameras, imgnames):
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for nf, img in enumerate(tqdm(imgnames, desc=self.name)):
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mv_ret = []
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if not isinstance(img, list):
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img = [img]
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for nv in self.view_list:
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basename = os.path.basename(img[nv])
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assert os.path.exists(img[nv]), img[nv]
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vis = cv2.imread(img[nv])
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vis = cv2.resize(vis, None, fx=self.scale3d, fy=self.scale3d)
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vert = vertices[nf]
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meshes = {}
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if vert.ndim == 2:
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meshes[0] = {
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'vertices': vert,
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'faces': faces,
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'id': 0,
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'name': 'human_{}'.format(0)
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}
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elif vert.ndim == 3:
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for pid in range(vert.shape[0]):
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meshes[pid] = {
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'vertices': vert[pid],
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'faces': faces,
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'id': pid,
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'name': 'human_{}'.format(pid)
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}
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if cameras['K'].ndim == 4:
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K = cameras['K'][nf][nv].copy()
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K[:2, :] *= self.scale
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R = cameras['R'][nf][nv]
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T = cameras['T'][nf][nv]
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else:
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K = cameras['K'][nv].copy()
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K[:2, :] *= self.scale3d
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R = cameras['R'][nv]
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T = cameras['T'][nv]
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# add ground
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if self.render_mode == 'ground':
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from easymocap.visualize.geometry import create_ground
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ground = create_ground(
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center=[0, 0, -0.05], xdir=[1, 0, 0], ydir=[0, 1, 0], # 位置
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step=1, xrange=10, yrange=10, # 尺寸
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white=[1., 1., 1.], black=[0.5,0.5,0.5], # 颜色
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two_sides=True
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)
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meshes[1001] = ground
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vis = np.zeros((self.shape[0], self.shape[1], 3), dtype=np.uint8) + 255
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focal = min(self.shape) * 1.2
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K = np.array([
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[focal,0,vis.shape[0]/2],
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[0,focal,vis.shape[1]/2],
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[0,0,1]])
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ret = plot_meshes(vis, meshes, K, R, T, mode='rgb')
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else:
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ret = plot_meshes(vis, meshes, K, R, T, mode=self.render_mode)
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ret = add_logo(ret)
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mv_ret.append(ret)
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self.merge_and_write(mv_ret)
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def __call__(self, params, cameras, imgnames, **kwargs):
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body_model = kwargs[self.model_name]
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vertices = body_model.vertices(params, return_tensor=False)
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faces = body_model.faces
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self.render_(vertices, faces, cameras, imgnames)
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class Render_nocam:
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def __init__(self, scale=0.5, backend='pyrender',view_list=[0]) -> None:
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self.name = 'render'
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self.scale = scale
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self.view_list = view_list
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def __call__(self, hand_model, params, images):
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vertices = hand_model(**params, return_verts=True, return_tensor=False)
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faces = hand_model.faces
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for nf, img in enumerate(tqdm(images, desc=self.name)):
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for nv in self.view_list:
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if isinstance(img, np.ndarray):
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vis = img.copy()
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basename = '{:06}.jpg'.format(nf)
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else:
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basename = os.path.basename(img[nv])
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# 重新读入图片
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assert os.path.exists(img[nv]), img[nv]
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vis = cv2.imread(img[nv])
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vis = cv2.resize(vis, None, fx=self.scale, fy=self.scale)
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vert = vertices[nf]
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meshes = {}
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meshes[0] = {
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'vertices': vert,
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'faces': faces,
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'id': 0,
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'name': 'human_{}'.format(0)
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}
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K = np.array([[vis.shape[0],0,vis.shape[0]/2],[0,vis.shape[1],vis.shape[1]/2],[0,0,1]])
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K[:2, :] *= self.scale
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R = np.eye(3)
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T = np.array([0,0,0.3])
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ret = plot_meshes(vis, meshes, K, R, T, mode='image')
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outname = join(self.output, self.name, basename)
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os.makedirs(os.path.dirname(outname), exist_ok=True)
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cv2.imwrite(outname, ret)
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class Render_multiview_hand(Render_multiview):
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def __call__(self, hand_model_l, params_l, cameras, imgnames):
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vertices = hand_model_l(**params_l, return_verts=True, return_tensor=False)
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faces = hand_model_l.faces
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self.render_(vertices, faces, cameras, imgnames)
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class Render_smplh(Render_multiview):
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def __init__(self, path, at_step, scale=0.5, mode='image', backend='pyrender', view_list=[0]) -> None:
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super().__init__(scale, mode, backend, view_list)
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from easymocap.config import Config, load_object
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cfg_data = Config.load(path)
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self.model = load_object(cfg_data.module, cfg_data.args)
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self.at_step = at_step
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def __call__(self, params_smplh, cameras, imgnames):
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vertices = self.model(return_verts=True, return_tensor=False, **params_smplh)
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faces = self.model.faces
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if self.at_step:
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self.render_([vertices], faces, cameras, [imgnames])
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else:
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self.render_(vertices, faces, cameras, imgnames)
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class Render_smplh2(Render_smplh):
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def __call__(self, params, cameras, imgnames):
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super().__call__(params, cameras, imgnames)
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def projectPoints(X, K, R, t, Kd):
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x = R @ X + t
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x[0:2,:] = x[0:2,:]/x[2,:]#到归一化平面
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r = x[0,:]*x[0,:] + x[1,:]*x[1,:]
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x[0,:] = x[0,:]*(1 + Kd[0]*r + Kd[1]*r*r + Kd[4]*r*r*r) + 2*Kd[2]*x[0,:]*x[1,:] + Kd[3]*(r + 2*x[0,:]*x[0,:])
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x[1,:] = x[1,:]*(1 + Kd[0]*r + Kd[1]*r*r + Kd[4]*r*r*r) + 2*Kd[3]*x[0,:]*x[1,:] + Kd[2]*(r + 2*x[1,:]*x[1,:])
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x[0,:] = K[0,0]*x[0,:] + K[0,1]*x[1,:] + K[0,2]
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x[1,:] = K[1,0]*x[0,:] + K[1,1]*x[1,:] + K[1,2]
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return x
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class Render_multiview_handbyk3d(Render_multiview):
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def __call__(self, hand_model_l, params_l, hand_model_r, params_r, cameras, imgnames, keypoints3d):
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# breakpoint()
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joint_regressor_r = np.load('models/handmesh/data/joint_regressor_r.npy') #右手
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joint_regressor_l = np.load('models/handmesh/data/joint_regressor_l.npy') #右手
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facesl = hand_model_l.faces
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facesr = hand_model_r.faces
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# for nf, img in enumerate(tqdm(imgnames, desc=self.name)):
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#不显示0号人物的结果
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keypoints3d[0]=0
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img = imgnames
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k3d = keypoints3d
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vertices_l = hand_model_l(**params_l, return_verts=True, return_tensor=False) #[nf]
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vertices_r = hand_model_r(**params_r, return_verts=True, return_tensor=False) #[nf]
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# breakpoint()
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joint_l = np.repeat(joint_regressor_l[None, :, :],vertices_l.shape[0],0) @ vertices_l
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joint_r = np.repeat(joint_regressor_r[None, :, :],vertices_r.shape[0],0) @ vertices_r
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params_l['Th']+=k3d[:,7,:3] - joint_l[:,0,:] #左手7右手4 #[nf]
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params_r['Th']+=k3d[:,4,:3] - joint_r[:,0,:] #左手7右手4 #[nf]
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vertices_l = hand_model_l(**params_l, return_verts=True, return_tensor=False) #[nf]
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vertices_r = hand_model_r(**params_r, return_verts=True, return_tensor=False) #[nf]
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faces = []
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vert = []
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pids = []
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for i in range(k3d.shape[0]):
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if k3d[i,7,-1]==0:
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continue
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vv = vertices_l[i].copy()
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vert.append(vv)
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faces.append(facesl)
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pids.append(i)
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for i in range(k3d.shape[0]):
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if k3d[i,4,-1]==0:
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continue
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vv = vertices_r[i].copy()
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vert.append(vv)
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faces.append(facesr)
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pids.append(i)
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faces = np.stack(faces)
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vert = np.stack(vert)
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for nv in self.view_list:
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basename = os.path.basename(img[nv])
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# 重新读入图片
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assert os.path.exists(img[nv]), img[nv]
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vis = cv2.imread(img[nv])
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vis = cv2.resize(vis, None, fx=self.scale, fy=self.scale)
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# vert = vertices
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meshes = {}
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if vert.ndim == 2:
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meshes[0] = {
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'vertices': vert,
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'faces': faces,
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'id': 0,
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'name': 'human_{}'.format(0)
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}
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elif vert.ndim == 3:
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for pid in range(vert.shape[0]):
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meshes[pid] = {
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'vertices': vert[pid],
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'faces': faces[pid],
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'vid': pids[pid],
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'name': 'human_{}'.format(pid)
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}
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K = cameras['K'][nv].copy()
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K[:2, :] *= self.scale
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R = cameras['R'][nv]
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T = cameras['T'][nv]
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# breakpoint()
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from easymocap.mytools.vis_base import plot_keypoints_auto
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for pid in range(keypoints3d.shape[0]):
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keypoints_repro = projectPoints(keypoints3d[pid].T[:3,:], K, R, T, cameras['dist'][nv].reshape(5)).T
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keypoints_repro[:,-1] = keypoints3d[pid,:,-1]
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plot_keypoints_auto(vis, keypoints_repro, pid=pid, use_limb_color=False)
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ret = plot_meshes(vis, meshes, K, R, T, mode=self.mode)
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outname = join(self.output, self.name, basename)
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os.makedirs(os.path.dirname(outname), exist_ok=True)
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cv2.imwrite(outname, ret)
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class Render_selectview:
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def __init__(self, scale=0.5, backend='pyrender', output='output',mode = 'image') -> None:
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self.name = 'render_debug'
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self.scale = scale
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self.view_list = [5]
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self.output = output
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self.mode = mode
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def __call__(self, hand_model_l, posel, match3d_l, cameras, imgnames, keypoints3d,bbox_handl, joint_regressor, wristid):
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img = imgnames
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k3d = keypoints3d
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# joint_regressor_r = np.load('models/handmesh/data/joint_regressor_r.npy') #右手
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# joint_regressor_l = np.load('models/handmesh/data/joint_regressor_l.npy')
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joint_regressor_l = joint_regressor
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facesl = hand_model_l.faces
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# facesr = hand_model_r.faces
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# breakpoint()
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hand_list=[]
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for pid in range(len(match3d_l)):
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dt = match3d_l[pid]
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if(isinstance(dt,int)):
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# TODO:处理-1的情况，也就是没有找到合适的匹配到的手
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hand_list.append(np.zeros((1,48)))
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break
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# Merge_list=[]
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out_img = []
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for cid in range(len(dt['views'])):
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nv = dt['views'][cid]
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poseid = dt['indices'][cid]
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pose = posel[nv][poseid].copy()
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Rh = pose[:,:3].copy()
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invR = np.linalg.inv(cameras['R'][nv])
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Rh_m_old = np.matrix(cv2.Rodrigues(Rh)[0])
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Rh_m_new = invR @ Rh_m_old
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Rh = cv2.Rodrigues(Rh_m_new)[0]
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pose_ = np.hstack((Rh.reshape(3),pose[:,3:].reshape(-1))).reshape(1,-1)
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Rh = pose_[:,:3].copy()
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pose_[:,:3] = 0
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params_l={
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'Rh':Rh,
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'Th':np.zeros_like(Rh),
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'poses':pose_,
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'shapes':np.zeros((Rh.shape[0],10)),
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}
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vertices_l = hand_model_l(**params_l, return_verts=True, return_tensor=False)
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joint_l = np.repeat(joint_regressor_l[None, :, :],vertices_l.shape[0],0) @ vertices_l
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params_l['Th']+=k3d[pid,wristid,:3] - joint_l[0,0,:]
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vertices_l = hand_model_l(**params_l, return_verts=True, return_tensor=False)
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vert = vertices_l[0]
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faces = facesl
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basename = os.path.basename(img[nv])
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# 重新读入图片
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assert os.path.exists(img[nv]), img[nv]
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vis = cv2.imread(img[nv])
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plot_bbox(vis,bbox_handl[nv][poseid],0)
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vis = cv2.resize(vis, None, fx=self.scale, fy=self.scale)
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meshes = {}
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if vert.ndim == 2:
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meshes[0] = {
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'vertices': vert,
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'faces': faces,
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'id': 0,
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'name': 'human_{}'.format(0)
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}
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elif vert.ndim == 3:
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for pid in range(vert.shape[0]):
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meshes[pid] = {
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'vertices': vert[pid],
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'faces': faces[pid],
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'id': pid,
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'name': 'human_{}'.format(pid)
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}
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K = cameras['K'][nv].copy()
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K[:2, :] *= self.scale
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R = cameras['R'][nv]
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T = cameras['T'][nv]
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# breakpoint()
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ret = plot_meshes(vis, meshes, K, R, T, mode=self.mode)
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out_img.append(ret)
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out_img = merge(out_img)
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outname = join(self.output, self.name, '{}-{:02d}.jpg'.format(basename.split('.jpg')[0],pid))
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os.makedirs(os.path.dirname(outname), exist_ok=True)
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cv2.imwrite(outname, out_img)
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class Render_selectview_lr:
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def __init__(self, scale=0.5, backend='pyrender', output='output',mode = 'image') -> None:
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self.output = output
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self.model_l = Render_selectview(scale=0.5, backend='pyrender', output = self.output,mode = mode)
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self.model_r = Render_selectview(scale=0.5, backend='pyrender', output = self.output,mode = mode)
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self.model_l.name+='_l'
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self.model_r.name+='_r'
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def __call__(self, hand_model_l, posel, poser, match3d_l, match3d_r, hand_model_r, cameras, imgnames, keypoints3d,bbox_handl,bbox_handr):
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joint_regressor_r = np.load('models/handmesh/data/joint_regressor_r.npy') #右手
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joint_regressor_l = np.load('models/handmesh/data/joint_regressor_l.npy')
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self.model_l(hand_model_l, posel, match3d_l, cameras, imgnames, keypoints3d,bbox_handl, joint_regressor_l, 7)
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self.model_r(hand_model_r, poser, match3d_r, cameras, imgnames, keypoints3d,bbox_handr, joint_regressor_r, 4)
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class Render_mv(Render):
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def __call__(self, body_model, params, cameras, imgnames):
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# breakpoint()
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super().__call__(body_model, params, cameras, [imgnames[0],imgnames[1]]) |