def collect_real_set_info(self):
database=[]
projector=Projector()
modeldb=LineModModelDB()
transformer=PoseTransformer(class_type=self.cls_name)
img_num=len(os.listdir(os.path.join(self.linemod_dir,self.rgb_dir)))
print(img_num)
for k in range(img_num):
data={}
data['rgb_pth']=os.path.join(self.rgb_dir,'color_{:05}.png'.format(k))
data['dpt_pth']=os.path.join(self.mask_dir,'{}.png'.format(k))
pose=self.read_pose(os.path.join(self.rt_dir,'info_{:05}.txt'.format(k)))
if len(pose)==0:
# os.system('cp {} ./{:05}.png'.format(os.path.join(cfg.OCCLUSION_LINEMOD,data['rgb_pth']),k))
continue
data['RT']=transformer.occlusion_pose_to_blender_pose(pose)
data['cls_typ']=self.cls_name
data['rnd_typ']='real'
data['corners']=projector.project(modeldb.get_corners_3d(self.cls_name),data['RT'],'linemod')
data['farthest']=projector.project(modeldb.get_farthest_3d(self.cls_name),data['RT'],'linemod')
for num in [4,12,16,20]:
data['farthest{}'.format(num)]=projector.project(modeldb.get_farthest_3d(self.cls_name,num),data['RT'],'linemod')
data['center']=projector.project(modeldb.get_centers_3d(self.cls_name)[None,:],data['RT'],'linemod')
data['small_bbox'] = projector.project(modeldb.get_small_bbox(self.cls_name), data['RT'], 'linemod')
axis_direct=np.concatenate([np.identity(3), np.zeros([3, 1])], 1).astype(np.float32)
data['van_pts']=projector.project_h(axis_direct, data['RT'], 'blender')
database.append(data)
save_pickle(database,self.real_pkl)
return database
def collect_ms_info(self):
database=[]
projector=Projector()
model_db=LineModModelDB()
for k in range(self.ms_num):
data=dict()
data['rgb_pth']=os.path.join(self.ms_dir, '{}.jpg'.format(k))
data['dpt_pth']=os.path.join(self.ms_dir, '{}_{}_mask.png'.format(k,self.cls_name))
# if too few foreground pts then continue
mask=imread(os.path.join(self.linemod_dir,data['dpt_pth']))
if np.sum(mask)<5: continue
data['RT'] = read_pickle(os.path.join(self.linemod_dir, self.ms_dir, '{}_{}_RT.pkl'.format(self.cls_name,k)))['RT']
data['cls_typ']=self.cls_name
data['rnd_typ']='render_multi'
data['corners']=projector.project(model_db.get_corners_3d(self.cls_name),data['RT'],'blender')
data['farthest']=projector.project(model_db.get_farthest_3d(self.cls_name),data['RT'],'blender')
for num in [4,12,16,20]:
data['farthest{}'.format(num)]=projector.project(modeldb.get_farthest_3d(self.cls_name,num),data['RT'],'blender')
data['center']=projector.project(model_db.get_centers_3d(self.cls_name)[None,:],data['RT'],'blender')
data['small_bbox'] = projector.project(modeldb.get_small_bbox(self.cls_name), data['RT'], 'blender')
axis_direct=np.concatenate([np.identity(3), np.zeros([3, 1])], 1).astype(np.float32)
data['van_pts']=projector.project_h(axis_direct, data['RT'], 'blender')
database.append(data)
save_pickle(database,self.ms_pkl)
return database
def collect_real_set_info(self): # linemod standard
database=[]
projector=Projector()
modeldb=LineModModelDB()
img_num=len(os.listdir(os.path.join(self.linemod_dir,self.rgb_dir)))
for k in range(img_num):
data={}
data['rgb_pth']=os.path.join(self.rgb_dir, '{:06}.jpg'.format(k))
data['dpt_pth']=os.path.join(self.mask_dir, '{:04}.png'.format(k))
pose=read_pose(os.path.join(self.rt_dir, 'rot{}.rot'.format(k)),
os.path.join(self.rt_dir, 'tra{}.tra'.format(k)))
pose_transformer = PoseTransformer(class_type=self.cls_name)
data['RT'] = pose_transformer.orig_pose_to_blender_pose(pose).astype(np.float32)
data['cls_typ']=self.cls_name
data['rnd_typ']='real'
data['corners']=projector.project(modeldb.get_corners_3d(self.cls_name),data['RT'],'linemod')
data['farthest']=projector.project(modeldb.get_farthest_3d(self.cls_name),data['RT'],'linemod')
for num in [4,12,16,20]:
data['farthest{}'.format(num)]=projector.project(modeldb.get_farthest_3d(self.cls_name,num),data['RT'],'linemod')
data['center']=projector.project(modeldb.get_centers_3d(self.cls_name)[None, :],data['RT'],'linemod')
data['small_bbox'] = projector.project(modeldb.get_small_bbox(self.cls_name), data['RT'], 'linemod')
axis_direct=np.concatenate([np.identity(3), np.zeros([3, 1])], 1).astype(np.float32)
data['van_pts']=projector.project_h(axis_direct, data['RT'], 'linemod')
database.append(data)
save_pickle(database,self.set_pkl)
return database
def collect_real_set_info(self):
'''
pvnet 的数据集linemod有做更改， cat.ply 与原始的linemod中的cat.ply,有模型偏移和旋转，
所以 原始数据集中的pose真值，需要 简单变换，就是这边数据集的 pose
会这样问了，既然图片数据集 这是没有改变的，怎么RT改变呢
因为 这边提的3d特征是 新的model上取的，所以计算RT的时候， RT要变的
pose_real.pkl
'''
database = []
projector = Projector()
modeldb = LineModModelDB()
img_num = len(os.listdir(os.path.join(self.linemod_dir, self.rgb_dir)))
for k in range(img_num):
data = {}
data['rgb_pth'] = os.path.join(self.rgb_dir, '{:06}.jpg'.format(k))
data['dpt_pth'] = os.path.join(self.mask_dir,
'{:04}.png'.format(k))
pose = read_pose(os.path.join(self.rt_dir, 'rot{}.rot'.format(k)),
os.path.join(self.rt_dir, 'tra{}.tra'.format(k)))
pose_transformer = PoseTransformer(class_type=self.cls_name)
data['RT'] = pose_transformer.orig_pose_to_blender_pose(
pose).astype(np.float32)
data['cls_typ'] = self.cls_name
data['rnd_typ'] = 'real'
data['corners'] = projector.project(
modeldb.get_corners_3d(self.cls_name), data['RT'], 'linemod')
data['farthest'] = projector.project(
modeldb.get_farthest_3d(self.cls_name), data['RT'], 'linemod')
for num in [4, 12, 16, 20]:
data['farthest{}'.format(num)] = projector.project(
modeldb.get_farthest_3d(self.cls_name, num), data['RT'],
'linemod')
data['center'] = projector.project(
modeldb.get_centers_3d(self.cls_name)[None, :], data['RT'],
'linemod')
data['small_bbox'] = projector.project(
modeldb.get_small_bbox(self.cls_name), data['RT'], 'linemod')
axis_direct = np.concatenate(
[np.identity(3), np.zeros([3, 1])], 1).astype(np.float32)
data['van_pts'] = projector.project_h(axis_direct, data['RT'],
'linemod')
database.append(data)
save_pickle(database, self.real_pkl)
return database
def collect_render_set_info(self,pkl_file,render_dir,format='jpg'):
database=[] # blender standard
projector=Projector()
modeldb=LineModModelDB()
for k in range(self.render_num):
data={}
data['rgb_pth']=os.path.join(render_dir,'{}.{}'.format(k,format))
data['RT']=read_pickle(os.path.join(self.linemod_dir,render_dir,'{}_RT.pkl'.format(k)))['RT']
data['cls_typ']=self.cls_name
data['rnd_typ']='render'
data['corners']=projector.project(modeldb.get_corners_3d(self.cls_name),data['RT'],'blender')
data['farthest']=projector.project(modeldb.get_farthest_3d(self.cls_name),data['RT'],'blender')
data['center']=projector.project(modeldb.get_centers_3d(self.cls_name)[None,:],data['RT'],'blender')
for num in [4,12,16,20]:
data['farthest{}'.format(num)]=projector.project(modeldb.get_farthest_3d(self.cls_name,num),data['RT'],'blender')
data['small_bbox'] = projector.project(modeldb.get_small_bbox(self.cls_name), data['RT'], 'blender')
axis_direct=np.concatenate([np.identity(3), np.zeros([3, 1])], 1).astype(np.float32)
data['van_pts']=projector.project_h(axis_direct, data['RT'], 'blender')
database.append(data)
save_pickle(database,pkl_file)
return database
def collect_val_render(self, pkl_file, render_dir, format='jpg'):
database = []
projector = Projector()
modeldb = HomemadeModelDB()
for k in range(3482, 3499):
data = {}
print(os.path.join(self.render_val_dir, '{}.{}'.format(k, format)))
data['rgb_pth'] = os.path.join(self.render_val_dir,
'{}.{}'.format(k, format))
data['dpt_pth'] = os.path.join(self.render_val_dir,
'{}_depth.png'.format(k))
data['RT'] = read_pickle(
os.path.join(self.homemade_dir, self.render_val_dir,
'{}_RT.pkl'.format(k)))['RT']
data['cls_typ'] = self.cls_name
data['rnd_typ'] = 'render'
data['corners'] = projector.project(
modeldb.get_corners_3d(self.cls_name), data['RT'], 'blender')
data['farthest'] = projector.project(
modeldb.get_farthest_3d(self.cls_name), data['RT'], 'blender')
data['center'] = projector.project(
modeldb.get_centers_3d(self.cls_name)[None, :], data['RT'],
'blender')
for num in [4, 12, 16, 20]:
data['farthest{}'.format(num)] = projector.project(
modeldb.get_farthest_3d(self.cls_name, num), data['RT'],
'blender')
data['small_bbox'] = projector.project(
modeldb.get_small_bbox(self.cls_name), data['RT'], 'blender')
axis_direct = np.concatenate(
[np.identity(3), np.zeros([3, 1])], 1).astype(np.float32)
data['van_pts'] = projector.project_h(axis_direct, data['RT'],
'blender')
database.append(data)
print("collectval successful?: length = ", len(database))
save_pickle(database, pkl_file)
return database
