import os
import trimesh
import numpy as np
from PytorchBoot.runners.runner import Runner
from PytorchBoot.config import ConfigManager
import PytorchBoot.stereotype as stereotype
from PytorchBoot.utils.log_util import Log
from PytorchBoot.status import status_manager

from utils.control_util import ControlUtil
from utils.communicate_util import CommunicateUtil
from utils.pts_util import PtsUtil
from utils.view_sample_util import ViewSampleUtil
from utils.reconstruction_util import ReconstructionUtil


@stereotype.runner("CAD_strategy_runner")
class CADStrategyRunner(Runner):

    def __init__(self, config_path: str):
        super().__init__(config_path)
        self.load_experiment("cad_strategy")
        self.status_info = {
            "status_manager": status_manager,
            "app_name": "cad",
            "runner_name": "cad_strategy"
        }
        self.generate_config = ConfigManager.get("runner", "generate")
        self.reconstruct_config = ConfigManager.get("runner", "reconstruct")
        self.model_dir = self.generate_config["model_dir"]
        self.voxel_size = self.generate_config["voxel_size"]
        self.max_view = self.generate_config["max_view"]
        self.min_view = self.generate_config["min_view"]
        self.max_diag = self.generate_config["max_diag"]
        self.min_diag = self.generate_config["min_diag"]
        self.min_cam_table_included_degree = self.generate_config["min_cam_table_included_degree"]
        self.random_view_ratio = self.generate_config["random_view_ratio"]
        
        self.soft_overlap_threshold = self.reconstruct_config["soft_overlap_threshold"]
        self.hard_overlap_threshold = self.reconstruct_config["hard_overlap_threshold"]
        self.scan_points_threshold = self.reconstruct_config["scan_points_threshold"]
        
    def create_experiment(self, backup_name=None):
        super().create_experiment(backup_name)
    
    def load_experiment(self, backup_name=None):
        super().load_experiment(backup_name)
        
    def run_one_model(self, model_name):
        
        ''' init robot '''
        ControlUtil.init()
        ''' load CAD model '''
        model_path = os.path.join(self.model_dir, model_name)
        cad_model = trimesh.load(model_path)
        ''' take first view '''
        view_data = CommunicateUtil.get_view_data()
        first_cam_pts = None
        ''' register '''
        cad_to_cam = PtsUtil.register_icp(first_cam_pts, cad_model)
        cam_to_world = ControlUtil.get_pose()
        cad_to_world = cam_to_world @ cad_to_cam
        cad_model:trimesh.Trimesh = cad_model.apply_transform(cad_to_world)
        ''' sample view '''
        min_corner = cad_model.bounds[0]
        max_corner = cad_model.bounds[1] 
        diag = np.linalg.norm(max_corner - min_corner)
        view_num = int(self.min_view + (diag - self.min_diag)/(self.max_diag - self.min_diag) * (self.max_view - self.min_view))
        sampled_view_data = ViewSampleUtil.sample_view_data_world_space(
            cad_model, cad_to_world,  
            voxel_size = self.voxel_size,
            max_views = view_num,
            min_cam_table_included_degree= self.min_cam_table_included_degree,
            random_view_ratio = self.random_view_ratio
        )
        cam_to_world_poses = sampled_view_data["cam_to_world_poses"]
        world_model_points = sampled_view_data["voxel_down_sampled_points"]

        ''' take sample view '''
        scan_points_idx_list = []
        sample_view_pts_list = []
        for cam_to_world in cam_to_world_poses:
            ControlUtil.move_to(cam_to_world)
            ''' get world pts '''
            view_data = CommunicateUtil.get_view_data()
            cam_pts = None
            scan_points_idx = None
            world_pts = PtsUtil.transform_point_cloud(cam_pts, cam_to_world)
            sample_view_pts_list.append(world_pts)
            scan_points_idx_list.append(scan_points_idx)
            
        ''' generate strategy '''
        limited_useful_view, _, _ = ReconstructionUtil.compute_next_best_view_sequence_with_overlap(
            world_model_points, sample_view_pts_list, 
            scan_points_indices_list = scan_points_idx_list,
            init_view=0,
            threshold=self.voxel_size, 
            soft_overlap_threshold= self.soft_overlap_threshold,
            hard_overlap_threshold= self.hard_overlap_threshold,
            scan_points_threshold = self.scan_points_threshold, 
            status_info=self.status_info
        )
        
        ''' extract cam_to world sequence  '''
        cam_to_world_seq = []
        coveraget_rate_seq = []
        
        for idx, coverage_rate in limited_useful_view:
            cam_to_world_seq.append(cam_to_world_poses[idx])
            coveraget_rate_seq.append(coverage_rate)
            
        ''' take best seq view '''
        for cam_to_world in cam_to_world_seq:
            ControlUtil.move_to(cam_to_world)
            ''' get world pts '''
            view_data = CommunicateUtil.get_view_data()
            cam_pts = None
            scan_points_idx = None
            world_pts = PtsUtil.transform_point_cloud(cam_pts, cam_to_world)
            sample_view_pts_list.append(world_pts)
            scan_points_idx_list.append(scan_points_idx)
        
    
    def run(self):
        total = len(os.listdir(self.model_dir))
        model_start_idx = self.generate_config["model_start_idx"]
        count_object = model_start_idx
        for model_name in os.listdir(self.model_dir[model_start_idx:]):
            Log.info(f"[{count_object}/{total}]Processing {model_name}")
            self.run_one_model(model_name)
            Log.success(f"[{count_object}/{total}]Finished processing {model_name}")
            
    
if __name__ == "__main__":
    model_path = "/home/yan20/nbv_rec/data/test_CAD/test_model/bear_scaled.ply"
    model = trimesh.load(model_path)
    test_pts_L = np.loadtxt("/home/yan20/nbv_rec/data/test_CAD/cam_pts_0_L.txt")
    test_pts_R = np.loadtxt("/home/yan20/nbv_rec/data/test_CAD/cam_pts_0_R.txt")
    cam_to_world_L = PtsUtil.register_icp(test_pts_L, model)
    cam_to_world_R = PtsUtil.register_icp(test_pts_R, model)
    print(cam_to_world_L)
    print("================================")
    print(cam_to_world_R)