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change DataLoadUtil and Dataset to blender version

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hofee
2024-08-29 13:54:13 -05:00
parent eceedd5c15
commit 80cd4aba9d
6 changed files with 135 additions and 129 deletions
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66
core/evaluation.py
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@@ -1,23 +1,37 @@
import torch
from utils.pose import PoseUtil
import PytorchBoot.stereotype as stereotype
import PytorchBoot.namespace as namespace
@stereotype.evaluation_method("delta_pose_diff")
class DeltaPoseDiff:
def get_view_data(cam_pose, scene_name):
pass
@stereotype.evaluation_method("pose_diff", comment="not tested")
class PoseDiff:
def __init__(self, _):
pass
def evaluate(self, output_list, data_list):
results = {namespace.TensorBoard.SCALAR: {}}
rot_angle_list = []
trans_dist_list = []
for output, data in zip(output_list, data_list):
gt_delta_rot_6d = data['delta_rot_6d']
est_delta_rot_6d = output['estimated_delta_rot_6d']
gt_delta_rot_mat = PoseUtil.rotation_6d_to_matrix_tensor_batch(gt_delta_rot_6d)
est_delta_rot_mat = PoseUtil.rotation_6d_to_matrix_tensor_batch(est_delta_rot_6d)
rotation_angles = PoseUtil.rotation_angle_distance(gt_delta_rot_mat, est_delta_rot_mat)
gt_pose_9d = data['nbv_cam_pose']
pred_pose_9d = output['pred_pose_9d']
gt_rot_6d = gt_pose_9d[:, :6]
gt_trans = gt_pose_9d[:, 6:]
pred_rot_6d = pred_pose_9d[:, :6]
pred_trans = pred_pose_9d[:, 6:]
gt_rot_mat = PoseUtil.rotation_6d_to_matrix_tensor_batch(gt_rot_6d)
pred_rot_mat = PoseUtil.rotation_6d_to_matrix_tensor_batch(pred_rot_6d)
rotation_angles = PoseUtil.rotation_angle_distance(gt_rot_mat, pred_rot_mat)
rot_angle_list.extend(list(rotation_angles))
trans_dist = torch.norm(gt_trans-pred_trans)
trans_dist_list.append(trans_dist)
results[namespace.TensorBoard.SCALAR]["delta_rotation"] = float(sum(rot_angle_list) / len(rot_angle_list))
results[namespace.TensorBoard.SCALAR]["rot_diff"] = float(sum(rot_angle_list) / len(rot_angle_list))
results[namespace.TensorBoard.SCALAR]["trans_diff"] = float(sum(trans_dist_list) / len(trans_dist_list))
return results
@@ -25,8 +39,40 @@ class DeltaPoseDiff:
@stereotype.evaluation_method("coverage_rate_increase",comment="unfinished")
class ConverageRateIncrease:
def __init__(self, config):
pass
self.config = config
def evaluate(self, output_list, data_list):
return
results = {namespace.TensorBoard.SCALAR: {}}
gt_coverate_increase_list = []
pred_coverate_increase_list = []
cr_diff_list = []
for output, data in zip(output_list, data_list):
scanned_cr = data['scanned_coverages_rate']
gt_cr = data["nbv_coverage_rate"]
scene_name_list = data['scene_name']
scanned_view_pts_list = data['scanned_views_pts']
pred_pose_9ds = output['pred_pose_9d']
pred_rot_mats = PoseUtil.rotation_6d_to_matrix_tensor_batch(pred_pose_9ds[:, :6])
pred_pose_mats = torch.cat([pred_rot_mats, pred_pose_9ds[:, 6:]], dim=-1)
for idx in range(len(scanned_cr)):
gt_coverate_increase_list.append(gt_cr-scanned_cr[idx])
scene_name = scene_name_list[idx]
pred_pose = pred_pose_mats[idx]
scanned_view_pts = scanned_view_pts_list[idx]
view_data = get_view_data(pred_pose, scene_name)
pred_cr = self.compute_coverage_rate(pred_pose, scanned_view_pts, view_data)
pred_coverate_increase_list.append(pred_cr-scanned_cr[idx])
cr_diff_list.append(gt_cr-pred_cr)
results[namespace.TensorBoard.SCALAR]["gt_cr_increase"] = float(sum(gt_coverate_increase_list) / len(gt_coverate_increase_list))
results[namespace.TensorBoard.SCALAR]["pred_cr_increase"] = float(sum(pred_coverate_increase_list) / len(pred_coverate_increase_list))
results[namespace.TensorBoard.SCALAR]["cr_diff"] = float(sum(cr_diff_list) / len(cr_diff_list))
return results
def compute_coverage_rate(self, pred_pose, scanned_view_pts, view_data):
pass