framework/PoseEstimation/objs2BOPdataset.py

261 lines
10 KiB
Python

import blenderproc as bproc
"""
objs2BOPdataset
Общая задача: распознавание 6D позы объекта (6D pose estimation)
Реализуемая функция: создание датасета в формате BOP для серии заданных объектов (*.obj) в заданной сцене (*.blend)
Используется модуль blenderproc
29.08.2023 @shalenikol release 0.1
12.10.2023 @shalenikol release 0.2
"""
import sys
import numpy as np
import argparse
import random
import os
import shutil
import json
Not_Categories_Name = True # наименование категории в аннотации отсутствует
def convert2relative(height, width, bbox):
"""
YOLO format use relative coordinates for annotation
"""
x, y, w, h = bbox
x += w/2
y += h/2
return x/width, y/height, w/width, h/height
parser = argparse.ArgumentParser()
parser.add_argument('scene', nargs='?', default="resources/sklad.blend", help="Path to the scene object.")
parser.add_argument('obj_path', nargs='?', default="resources/in_obj", help="Path to the object files.")
parser.add_argument('output_dir', nargs='?', default="output", help="Path to where the final files, will be saved")
parser.add_argument('vhacd_path', nargs='?', default="blenderproc_resources/vhacd", help="The directory in which vhacd should be installed or is already installed.")
parser.add_argument('-single_object', nargs='?', type= bool, default=True, help="One object per frame.")
parser.add_argument('--imgs', default=2, type=int, help="The number of times the objects should be rendered.")
args = parser.parse_args()
if not os.path.isdir(args.obj_path):
print(f"{args.obj_path} : no object directory")
sys.exit()
if not os.path.isdir(args.output_dir):
os.mkdir(args.output_dir)
single_object = args.single_object
bproc.init()
# ? загрузим свет из сцены
#cam = bproc.loader.load_blend(args.scene, data_blocks=["cameras"])
#lights = bproc.loader.load_blend(args.scene, data_blocks=["lights"])
# загрузим объекты
list_files = os.listdir(args.obj_path)
obj_names = []
obj_filenames = []
all_meshs = []
nObj = 0
for f in list_files:
if (os.path.splitext(f))[1] == ".obj":
f = os.path.join(args.obj_path, f) # путь к файлу объекта
if os.path.isfile(f):
obj = bproc.loader.load_obj(f)
all_meshs += obj
obj_names += [obj[0].get_name()]
obj_filenames += [f]
nObj += 1
if nObj == 0:
print("Objects not found")
sys.exit()
for i,obj in enumerate(all_meshs):
#print(f"{i} *** {obj}")
obj.set_cp("category_id", i+1)
# загрузим сцену
scene = bproc.loader.load_blend(args.scene, data_blocks=["objects"])
# найдём объекты коллизии (пол и т.д.)
obj_type = ["floor", "obj"]
collision_objects = []
#floor = None
for o in scene:
o.set_cp("category_id", 999)
s = o.get_name()
for type in obj_type:
if s.find(type) >= 0:
collision_objects += [o]
o.enable_rigidbody(False, collision_shape='BOX')
if not collision_objects:
print("Collision objects not found in the scene")
sys.exit()
#floor.enable_rigidbody(False, collision_shape='BOX')
for obj in all_meshs:
# Make the object actively participate in the physics simulation
obj.enable_rigidbody(active=True, collision_shape="COMPOUND")
# Also use convex decomposition as collision shapes
obj.build_convex_decomposition_collision_shape(args.vhacd_path)
objs = all_meshs + scene
with open(os.path.join(args.output_dir,"res.txt"), "w") as fh:
# fh.write(str(type(scene[0]))+"\n")
i = 0
for o in objs:
i += 1
loc = o.get_location()
euler = o.get_rotation_euler()
fh.write(f"{i} : {o.get_name()} {loc} {euler} category_id = {o.get_cp('category_id')}\n")
# define a light and set its location and energy level
light = bproc.types.Light()
light.set_type("POINT")
light.set_location([5, -5, 5])
#light.set_energy(900)
#light.set_color([0.7, 0.7, 0.7])
light1 = bproc.types.Light(name="light1")
light1.set_type("SUN")
light1.set_location([0, 0, 0])
light1.set_rotation_euler([-0.063, 0.6177, -0.1985])
#light1.set_energy(7)
light1.set_color([1, 1, 1])
# define the camera intrinsics
bproc.camera.set_intrinsics_from_blender_params(1, 640, 480, lens_unit="FOV")
# add segmentation masks (per class and per instance)
bproc.renderer.enable_segmentation_output(map_by=["category_id", "instance", "name"])
#bproc.renderer.enable_segmentation_output(map_by=["category_id", "instance", "name", "bop_dataset_name"],
# default_values={"category_id": 0, "bop_dataset_name": None})
# activate depth rendering
bproc.renderer.enable_depth_output(activate_antialiasing=False)
res_dir = os.path.join(args.output_dir, "bop_data")
if os.path.isdir(res_dir):
shutil.rmtree(res_dir)
# Цикл рендеринга
n_cam_location = 3 #5 # количество случайных локаций камеры
n_cam_poses = 3 #3 # количество сэмплов для каждой локации камеры
# Do multiple times: Position the shapenet objects using the physics simulator and render X images with random camera poses
for r in range(args.imgs):
# один случайный объект в кадре / все заданные объекты
meshs = [random.choice(all_meshs)] if single_object else all_meshs[:]
# Randomly set the color and energy
light.set_color(np.random.uniform([0.5, 0.5, 0.5], [1, 1, 1]))
light.set_energy(random.uniform(500, 1000))
light1.set_energy(random.uniform(3, 11))
for i,o in enumerate(meshs): #objs
mat = o.get_materials()[0]
mat.set_principled_shader_value("Specular", random.uniform(0, 1))
mat.set_principled_shader_value("Roughness", random.uniform(0, 1))
mat.set_principled_shader_value("Base Color", np.random.uniform([0, 0, 0, 1], [1, 1, 1, 1]))
mat.set_principled_shader_value("Metallic", random.uniform(0, 1))
# Clear all key frames from the previous run
bproc.utility.reset_keyframes()
# Define a function that samples 6-DoF poses
def sample_pose(obj: bproc.types.MeshObject):
obj.set_location(np.random.uniform([-1, -1.5, 0.2], [1, 2, 1.2])) #[-1, -1, 0], [1, 1, 2]))
obj.set_rotation_euler(bproc.sampler.uniformSO3())
# Sample the poses of all shapenet objects above the ground without any collisions in-between
#bproc.object.sample_poses(meshs, objects_to_check_collisions = meshs + [floor], sample_pose_func = sample_pose)
bproc.object.sample_poses(meshs, objects_to_check_collisions = meshs + collision_objects, sample_pose_func = sample_pose)
# Run the simulation and fix the poses of the shapenet objects at the end
bproc.object.simulate_physics_and_fix_final_poses(min_simulation_time=4, max_simulation_time=20, check_object_interval=1)
# Find point of interest, all cam poses should look towards it
poi = bproc.object.compute_poi(meshs)
coord_max = [0.1, 0.1, 0.1]
coord_min = [0., 0., 0.]
with open(os.path.join(args.output_dir,"res.txt"), "a") as fh:
fh.write("*****************\n")
fh.write(f"{r}) poi = {poi}\n")
i = 0
for o in meshs:
i += 1
loc = o.get_location()
euler = o.get_rotation_euler()
fh.write(f" {i} : {o.get_name()} {loc} {euler}\n")
for j in range(3):
if loc[j] < coord_min[j]:
coord_min[j] = loc[j]
if loc[j] > coord_max[j]:
coord_max[j] = loc[j]
# Sample up to X camera poses
#an = np.random.uniform(0.78, 1.2) #1. #0.35
for i in range(n_cam_location):
# Sample location
location = bproc.sampler.shell(center=[0, 0, 0],
radius_min=1.1,
radius_max=2.2,
elevation_min=5,
elevation_max=89)
# координата, по которой будем сэмплировать положение камеры
j = random.randint(0, 2)
# разовый сдвиг по случайной координате
d = (coord_max[j] - coord_min[j]) / n_cam_poses
if location[j] < 0:
d = -d
for k in range(n_cam_poses):
# Compute rotation based on vector going from location towards poi
rotation_matrix = bproc.camera.rotation_from_forward_vec(poi - location, inplane_rot=np.random.uniform(-0.7854, 0.7854))
# Add homog cam pose based on location an rotation
cam2world_matrix = bproc.math.build_transformation_mat(location, rotation_matrix)
bproc.camera.add_camera_pose(cam2world_matrix)
location[j] -= d
#world_matrix = bproc.math.build_transformation_mat([2.3, -0.4, 0.66], [1.396, 0., an])
#bproc.camera.add_camera_pose(world_matrix)
#an += 0.2
# render the whole pipeline
data = bproc.renderer.render()
# Write data to bop format
bproc.writer.write_bop(res_dir,
target_objects = all_meshs, # Optional[List[MeshObject]] = None
depths = data["depth"],
depth_scale = 1.0,
colors = data["colors"],
color_file_format='JPEG',
append_to_existing_output = (r>0),
save_world2cam = False) # world coords are arbitrary in most real BOP datasets
# dataset="robo_ds",
"""
!!! categories -> name берётся из category_id !!!
см.ниже
blenderproc.python.writer : BopWriterUtility.py
class _BopWriterUtility
def calc_gt_coco
...
CATEGORIES = [{'id': obj.get_cp('category_id'), 'name': str(obj.get_cp('category_id')), 'supercategory':
dataset_name} for obj in dataset_objects]
поэтому заменим наименование категории в аннотации
"""
if Not_Categories_Name:
coco_file = os.path.join(res_dir,"train_pbr/000000/scene_gt_coco.json")
with open(coco_file, "r") as fh:
data = json.load(fh)
cats = data["categories"]
#print(f"type(cat) = {type(cat)} cat : {cat}")
i = 0
for cat in cats:
cat["name"] = obj_names[i]
i += 1
#print(cat)
with open(coco_file, "w") as fh:
json.dump(data, fh, indent=0)