341 lines
15 KiB
Python
341 lines
15 KiB
Python
import os
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import time
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import trimesh
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import tempfile
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import subprocess
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import numpy as np
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from PytorchBoot.runners.runner import Runner
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from PytorchBoot.config import ConfigManager
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import PytorchBoot.stereotype as stereotype
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from PytorchBoot.utils.log_util import Log
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from PytorchBoot.status import status_manager
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from utils.control_util import ControlUtil
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from utils.communicate_util import CommunicateUtil
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from utils.pts_util import PtsUtil
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from utils.reconstruction_util import ReconstructionUtil
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from utils.preprocess_util import save_scene_data
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from utils.data_load import DataLoadUtil
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from utils.view_util import ViewUtil
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class PointCloud:
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def __init__(points, camera, name):
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pass
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class PointCloudGroup:
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def __init__(point_clouds, name):
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pass
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@stereotype.runner("temp")
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class CADCloseLoopOnlineRegStrategyRunner(Runner):
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def __init__(self, config_path: str):
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super().__init__(config_path)
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self.load_experiment("cad_strategy")
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self.generate_config = ConfigManager.get("runner", "generate")
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self.reconstruct_config = ConfigManager.get("runner", "reconstruct")
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self.output_dir = self.generate_config["output_dir"]
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self.model_dir = self.generate_config["model_dir"]
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self.object_name = self.generate_config["object_name"]
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self.blender_bin_path = self.generate_config["blender_bin_path"]
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self.generator_script_path = self.generate_config["generator_script_path"]
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self.voxel_size = self.generate_config["voxel_size"]
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self.max_shot_view_num = self.reconstruct_config["max_shot_view_num"]
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self.min_shot_new_pts_num = self.reconstruct_config["min_shot_new_pts_num"]
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self.min_coverage_increase = self.reconstruct_config["min_coverage_increase"]
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self.scan_points_threshold = self.reconstruct_config["scan_points_threshold"]
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def create_experiment(self, backup_name=None):
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super().create_experiment(backup_name)
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def load_experiment(self, backup_name=None):
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super().load_experiment(backup_name)
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def split_scan_pts_and_obj_pts(self, world_pts, z_threshold=0):
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scan_pts = world_pts[world_pts[:, 2] < z_threshold]
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obj_pts = world_pts[world_pts[:, 2] >= z_threshold]
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return scan_pts, obj_pts
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def loop_scan(self, first_cam_to_real_world):
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view_pts_list = []
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first_view_data = CommunicateUtil.get_view_data(init=True)
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ControlUtil.absolute_rotate_display_table(90)
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first_pts = ViewUtil.get_pts(first_view_data)
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first_real_world_pts = PtsUtil.transform_point_cloud(
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first_pts, first_cam_to_real_world
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)
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_, first_splitted_real_world_pts = self.split_scan_pts_and_obj_pts(
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first_real_world_pts
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)
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view_pts_list.append(first_splitted_real_world_pts)
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shot_num = 4
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for i in range(shot_num-1):
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view_data = CommunicateUtil.get_view_data()
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if i != shot_num - 2:
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ControlUtil.absolute_rotate_display_table(90)
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time.sleep(0.5)
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if view_data is None:
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Log.error("No view data received")
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continue
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view_pts = ViewUtil.get_pts(view_data)
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real_world_pts = PtsUtil.transform_point_cloud(
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view_pts, first_cam_to_real_world
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)
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_, splitted_real_world_pts = self.split_scan_pts_and_obj_pts(
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real_world_pts
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)
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view_pts_list.append(splitted_real_world_pts)
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return view_pts_list
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def register(self):
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ControlUtil.connect_robot()
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""" init robot """
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Log.info("start init")
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ControlUtil.init()
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first_cam_to_real_world = ControlUtil.get_pose()
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""" loop shooting """
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Log.info("start loop shooting")
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view_pts_list = self.loop_scan(first_cam_to_real_world)
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""" register """
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Log.info("start register")
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pts = np.vstack(view_pts_list)
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if not os.path.exists(self.output_dir):
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os.makedirs(self.output_dir)
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if not os.path.exists(os.path.join(self.output_dir, self.object_name)):
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os.makedirs(os.path.join(self.output_dir, self.object_name))
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scene_dir = os.path.join(self.output_dir, self.object_name)
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model_path = os.path.join(self.model_dir, self.object_name, "mesh.obj")
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cad_model = trimesh.load(model_path)
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real_world_to_cad = PtsUtil.register(pts, cad_model)
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cad_to_real_world = np.linalg.inv(real_world_to_cad)
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Log.success("finish init and register")
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real_world_to_blender_world = np.eye(4)
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real_world_to_blender_world[:3, 3] = np.asarray([0, 0, 0.9215])
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cad_model_real_world: trimesh.Trimesh = cad_model.apply_transform(
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cad_to_real_world
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)
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cad_model_real_world.export(os.path.join(scene_dir, "mesh.obj"))
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#downsampled_pts = PtsUtil.voxel_downsample_point_cloud(pts, self.voxel_size)
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np.savetxt(os.path.join(scene_dir, "pts_for_init_reg.txt"), pts)
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return cad_to_real_world
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def render_data(self):
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scene_dir = os.path.join(self.output_dir, self.object_name)
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result = subprocess.run(
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[
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self.blender_bin_path,
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"-b",
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"-P",
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self.generator_script_path,
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"--",
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scene_dir,
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],
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capture_output=True,
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text=True,
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)
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print(result)
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def preprocess_data(self):
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save_scene_data(self.output_dir, self.object_name, file_type="npy")
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def get_scan_points_indices(self, scan_points, mask, object_mask_label= (0, 255, 0, 255), cam_intrinsic = None, cam_extrinsic = None):
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scan_points_homogeneous = np.hstack((scan_points, np.ones((scan_points.shape[0], 1))))
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points_camera = np.dot(np.linalg.inv(cam_extrinsic), scan_points_homogeneous.T).T[:, :3]
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points_image_homogeneous = np.dot(cam_intrinsic, points_camera.T).T
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points_image_homogeneous /= points_image_homogeneous[:, 2:]
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pixel_x = points_image_homogeneous[:, 0].astype(int)
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pixel_y = points_image_homogeneous[:, 1].astype(int)
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h, w = mask.shape[:2]
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valid_indices = (pixel_x >= 0) & (pixel_x < w) & (pixel_y >= 0) & (pixel_y < h)
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mask_colors = mask[pixel_y[valid_indices], pixel_x[valid_indices]]
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selected_points_indices = np.where((mask_colors != object_mask_label).any(axis=-1))[0]
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selected_points_indices = np.where(valid_indices)[0][selected_points_indices]
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return selected_points_indices
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def run_one_model(self, model_name):
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scene_dir = os.path.join(self.output_dir, model_name)
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ControlUtil.connect_robot()
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""" init robot """
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Log.info("start init")
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ControlUtil.init()
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first_cam_to_real_world = ControlUtil.get_pose()
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""" loop shooting """
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Log.info("start loop shooting")
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view_pts_list = self.loop_scan(first_cam_to_real_world)
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""" register """
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cad_path = os.path.join(scene_dir, "mesh.obj")
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cad_model = trimesh.load(cad_path)
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Log.info("start register")
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init_pts = np.vstack(view_pts_list)
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real_world_to_cad = PtsUtil.register(init_pts, cad_model)
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curr_cad_to_real_world = np.linalg.inv(real_world_to_cad)
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# np.savetxt(os.path.join("/home/yan20/nbv_rec/project/franka_control/debug", "pts_for_init_reg.txt"), init_pts)
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# debug_cad = cad_model.apply_transform(curr_cad_to_real_world)
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# debug_cad.export(os.path.join("/home/yan20/nbv_rec/project/franka_control/debug", "cad_for_init_reg.obj"))
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pts_dir = os.path.join(scene_dir, "pts")
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sample_view_pts_list = []
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frame_num = len(os.listdir(pts_dir))
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for frame_idx in range(frame_num):
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pts_path = os.path.join(scene_dir, "pts", f"{frame_idx}.npy")
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point_cloud = np.load(pts_path)
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if point_cloud.shape[0] != 0:
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sampled_point_cloud = PtsUtil.voxel_downsample_point_cloud(
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point_cloud, self.voxel_size
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)
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sample_view_pts_list.append(sampled_point_cloud)
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else:
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sample_view_pts_list.append(np.zeros((0, 3)))
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""" close-loop online registery strategy """
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scanned_pts = PtsUtil.voxel_downsample_point_cloud(init_pts, voxel_size=self.voxel_size)
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shot_pts_list = []
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last_coverage = 0
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Log.info("start close-loop control")
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cnt = 0
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mask_list = []
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cam_to_cad_list = []
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cam_R_to_cad_list = []
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shot_view_idx_list = []
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scan_points_path = os.path.join(self.output_dir, self.object_name, "scan_points.txt")
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display_table_scan_points = np.loadtxt(scan_points_path)
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for i in range(frame_num):
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path = DataLoadUtil.get_path(self.output_dir, self.object_name, i)
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mask_L, mask_R = DataLoadUtil.load_seg(path, binocular=True)
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mask_list.append((mask_L, mask_R))
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cam_info = DataLoadUtil.load_cam_info(path, binocular=True)
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cam_to_cad = cam_info["cam_to_world"]
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cam_to_cad_list.append(cam_to_cad)
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cam_R_to_cad = cam_info["cam_to_world_R"]
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cam_R_to_cad_list.append(cam_R_to_cad)
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selected_view = []
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while True:
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import ipdb; ipdb.set_trace()
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history_indices = []
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scan_points_idx_list = []
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for i in range(frame_num):
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cam_to_cad = cam_to_cad_list[i]
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cam_R_to_cad = cam_R_to_cad_list[i]
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curr_cam_L_to_world = curr_cad_to_real_world @ cam_to_cad
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curr_cam_R_to_world = curr_cad_to_real_world @ cam_R_to_cad
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scan_points_indices_L = self.get_scan_points_indices(display_table_scan_points, mask_list[i][0], cam_intrinsic=cam_info["cam_intrinsic"], cam_extrinsic=curr_cam_L_to_world)
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scan_points_indices_R = self.get_scan_points_indices(display_table_scan_points, mask_list[i][1], cam_intrinsic=cam_info["cam_intrinsic"], cam_extrinsic=curr_cam_R_to_world)
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scan_points_indices = np.intersect1d(scan_points_indices_L, scan_points_indices_R)
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scan_points_idx_list.append(scan_points_indices)
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for shot_view_idx in shot_view_idx_list:
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history_indices.append(scan_points_idx_list[shot_view_idx])
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cad_scanned_pts = PtsUtil.transform_point_cloud(scanned_pts, np.linalg.inv(curr_cad_to_real_world))
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next_best_view, next_best_coverage, next_best_covered_num = (
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ReconstructionUtil.compute_next_best_view_with_overlap(
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cad_scanned_pts,
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sample_view_pts_list,
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selected_view,
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history_indices,
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scan_points_idx_list,
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threshold=self.voxel_size,
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overlap_area_threshold=25,
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scan_points_threshold=self.scan_points_threshold,
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)
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)
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if next_best_view is None:
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Log.warning("No next best view found")
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selected_view.append(next_best_view)
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nbv_path = DataLoadUtil.get_path(self.output_dir, self.object_name, next_best_view)
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nbv_cam_info = DataLoadUtil.load_cam_info(nbv_path, binocular=True)
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nbv_cam_to_cad = nbv_cam_info["cam_to_world_O"]
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nbv_cam_to_world = curr_cad_to_real_world @ nbv_cam_to_cad
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target_camera_pose = nbv_cam_to_world @ ControlUtil.CAMERA_CORRECTION
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ControlUtil.move_to(target_camera_pose)
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''' get world pts '''
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time.sleep(0.5)
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view_data = CommunicateUtil.get_view_data()
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if view_data is None:
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Log.error("No view data received")
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continue
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shot_view_idx_list.append(next_best_view)
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cam_shot_pts = ViewUtil.get_pts(view_data)
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world_shot_pts = PtsUtil.transform_point_cloud(
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cam_shot_pts, first_cam_to_real_world
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)
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_, world_splitted_shot_pts = self.split_scan_pts_and_obj_pts(
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world_shot_pts
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)
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shot_pts_list.append(world_splitted_shot_pts)
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debug_dir = os.path.join(scene_dir, "debug")
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if not os.path.exists(debug_dir):
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os.makedirs(debug_dir)
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last_scanned_pts_num = scanned_pts.shape[0]
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import ipdb;ipdb.set_trace()
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new_scanned_pts = PtsUtil.voxel_downsample_point_cloud(
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np.vstack([scanned_pts, world_splitted_shot_pts]), self.voxel_size
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)
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# last_real_world_to_cad = real_world_to_cad
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# real_world_to_cad = PtsUtil.register_fine(new_scanned_pts, cad_model)
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# # rot distance of two rotation matrix
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# rot_dist = np.arccos(
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# (np.trace(real_world_to_cad[:3, :3].T @ last_real_world_to_cad[:3, :3]) - 1) / 2
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# )
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# print(f"-----rot dist: {rot_dist}")
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curr_cad_to_real_world = np.linalg.inv(real_world_to_cad)
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cad_splitted_shot_pts = PtsUtil.transform_point_cloud(world_splitted_shot_pts, real_world_to_cad)
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np.savetxt(os.path.join(debug_dir, f"shot_pts_{cnt}.txt"), world_splitted_shot_pts)
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np.savetxt(os.path.join(debug_dir, f"render_pts_{cnt}.txt"), sample_view_pts_list[next_best_view])
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np.savetxt(os.path.join(debug_dir, f"reg_scanned_pts_{cnt}.txt"), new_scanned_pts)
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cad_pts = cad_model.vertices
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world_cad_pts = PtsUtil.transform_point_cloud(cad_pts, curr_cad_to_real_world)
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np.savetxt(os.path.join(debug_dir, f"world_cad_pts_{cnt}.txt"), world_cad_pts)
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#import ipdb; ipdb.set_trace()
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new_scanned_pts_num = new_scanned_pts.shape[0]
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scanned_pts = new_scanned_pts
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Log.info(
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f"Next Best cover pts: {next_best_covered_num}, Best coverage: {next_best_coverage}"
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)
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coverage_rate_increase = next_best_coverage - last_coverage
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if coverage_rate_increase < self.min_coverage_increase:
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Log.info(f"Coverage rate = {coverage_rate_increase} < {self.min_coverage_increase}, stop scanning")
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# break
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last_coverage = next_best_coverage
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new_added_pts_num = new_scanned_pts_num - last_scanned_pts_num
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if new_added_pts_num < self.min_shot_new_pts_num:
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Log.info(f"New added pts num = {new_added_pts_num} < {self.min_shot_new_pts_num}")
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#ipdb.set_trace()
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if len(shot_pts_list) >= self.max_shot_view_num:
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Log.info(f"Scanned view num = {len(shot_pts_list)} >= {self.max_shot_view_num}, stop scanning")
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#break
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cnt += 1
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Log.success("[Part 4/4] finish close-loop control")
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def run(self):
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self.run_one_model(self.object_name)
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# ---------------------------- test ---------------------------- #
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if __name__ == "__main__":
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model_path = r"/home/yan20/nbv_rec/data/models/workpiece_1/mesh.obj"
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model = trimesh.load(model_path)
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