From 7aadb872dcb27efbfe6c4c6ab32f7d94f7359e7c Mon Sep 17 00:00:00 2001
From: Alex AUTERNAUD <alex.auternaud@inria.fr>
Date: Tue, 4 Apr 2023 12:04:52 +0200
Subject: [PATCH] remove gcff from this git
---
README.md | 33 +------
requirements.txt | 1 -
social_mpc/controller.py | 6 --
social_mpc/goal.py | 7 --
.../ssn_model/group_detection/__init__.py | 13 ---
.../group_detection/gcff/__init__.py | 12 ---
.../ssn_model/group_detection/gcff/gcff.py | 94 -------------------
social_mpc/ssn_model/group_detection/utils.py | 19 ----
8 files changed, 1 insertion(+), 184 deletions(-)
delete mode 100644 social_mpc/ssn_model/group_detection/__init__.py
delete mode 100644 social_mpc/ssn_model/group_detection/gcff/__init__.py
delete mode 100644 social_mpc/ssn_model/group_detection/gcff/gcff.py
delete mode 100644 social_mpc/ssn_model/group_detection/utils.py
diff --git a/README.md b/README.md
index 6bb3c40..30404ce 100644
--- a/README.md
+++ b/README.md
@@ -1,32 +1 @@
-# MPC-based Robot controller in social environments
-
-This library implements a model predictive controller for a robot in a crowded environment.
-It is used in the Spring project that has received funding from the
-European Union’s Horizon 2020 research and innovation programme
-under grant agreement No 871245.
-
-## Installation
-
-Get and install [pygco](https://gitlab.inria.fr/spring/wp4_behavior/pygco.git) in your python environment.
-
-Install python requirements using
-
-```
-pip install -r requirements.txt
-```
-
-Install:
-
-```
-pip install .
-```
-
-## Demo
-
-To run the demo, you need to install the [2D simulator](https://gitlab.inria.fr/spring/wp6_robot_behavior/2D_Simulator)
-
-Run
-
-```
-./run_demo.sh
-```
\ No newline at end of file
+TODO
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index d13a2cc..9bf8118 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -37,7 +37,6 @@ Pygments>=2.10.0
pylint>=2.10.2
pyqtgraph==0.12.2
pyqt5==5.12
-pygco==0.1
python-dateutil>=2.8.2
PyWavelets>=1.1.1
PyYAML>=5.4.1
diff --git a/social_mpc/controller.py b/social_mpc/controller.py
index d0f4417..07714e7 100644
--- a/social_mpc/controller.py
+++ b/social_mpc/controller.py
@@ -10,7 +10,6 @@
from multiprocessing import Process, Lock
from multiprocessing.managers import SharedMemoryManager
-import social_mpc.ssn_model.group_detection as gd
import atexit
import rospy
import time
@@ -514,10 +513,6 @@ class RobotController():
humans[j, :] = * \
local_position, local_angle, state.humans_velocity[i, 0], 0
if n_human > 1:
- groups = gd.gcff.identify_groups(humans, stride=self.controller_config.group_detection_stride)
- for group in groups:
- rospy.loginfo('get_social_cost_map: groups from gcff: center :{} person_ids : {}'.format(group.center, group.person_ids))
-
groups = []
for idx, group_id in enumerate(state.groups_id):
if group_id != -1:
@@ -525,7 +520,6 @@ class RobotController():
groups.append(Group(center=center, person_ids=np.where(state.humans_group_id == group_id)[0]))
else:
break
- rospy.loginfo('get_social_cost_map: groups read from hri listener : center :{} person_ids : {}'.format(groups[-1].center, groups[-1].person_ids))
f_dsz = ssn.calc_dsz(humans, groups=groups)
f_dsz = np.flip(f_dsz, axis=0)
diff --git a/social_mpc/goal.py b/social_mpc/goal.py
index ea94c39..8c46600 100644
--- a/social_mpc/goal.py
+++ b/social_mpc/goal.py
@@ -9,7 +9,6 @@
# timothee.wintz@inria.fr
from social_mpc.ssn_model.social_spaces import SocialSpaces, Group
-import social_mpc.ssn_model.group_detection as gd
from social_mpc import utils
import numpy as np
@@ -95,15 +94,9 @@ class GoalFinder():
print("Target group not in sight")
continue
- groups = gd.gcff.identify_groups(humans, stride=stride)
- for group in groups:
- print('groups from gcff GOAL: center :{} person_ids : {}'.format(group.center, group.person_ids))
-
groups = []
for idx, group_id in enumerate(group_ids):
groups.append(Group(center=sh_groups[idx, :2], person_ids=np.where(humans[:, -2] == group_id)[0]))
- for group in groups:
- print('groups from hri listener GOAL: center :{} person_ids : {}'.format(group.center, group.person_ids))
humans_fdz = np.zeros((n_human, 5))
humans_fdz[:, :3] = humans[:, :3]
diff --git a/social_mpc/ssn_model/group_detection/__init__.py b/social_mpc/ssn_model/group_detection/__init__.py
deleted file mode 100644
index a28f7ea..0000000
--- a/social_mpc/ssn_model/group_detection/__init__.py
+++ /dev/null
@@ -1,13 +0,0 @@
-# This file, part of Social MPC in the WP6 of the Spring project,
-# is part of a project that has received funding from the
-# European Union’s Horizon 2020 research and innovation programme
-# under grant agreement No 871245.
-#
-# Copyright (C) 2020-2022 by Inria
-# Authors : Chris Reinke, Alex Auternaud, Timothée Wintz
-# chris.reinke@inria.fr
-# alex.auternaud@inria.fr
-# timothee.wintz@inria.fr
-
-from social_mpc.ssn_model.group_detection.gcff import *
-from social_mpc.ssn_model.group_detection.utils import group_labels_to_lists
diff --git a/social_mpc/ssn_model/group_detection/gcff/__init__.py b/social_mpc/ssn_model/group_detection/gcff/__init__.py
deleted file mode 100644
index e81b7c4..0000000
--- a/social_mpc/ssn_model/group_detection/gcff/__init__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-# This file, part of Social MPC in the WP6 of the Spring project,
-# is part of a project that has received funding from the
-# European Union’s Horizon 2020 research and innovation programme
-# under grant agreement No 871245.
-#
-# Copyright (C) 2020-2022 by Inria
-# Authors : Chris Reinke, Alex Auternaud, Timothée Wintz
-# chris.reinke@inria.fr
-# alex.auternaud@inria.fr
-# timothee.wintz@inria.fr
-
-from social_mpc.ssn_model.group_detection.gcff.gcff import identify_groups, Group
diff --git a/social_mpc/ssn_model/group_detection/gcff/gcff.py b/social_mpc/ssn_model/group_detection/gcff/gcff.py
deleted file mode 100644
index 53f38f7..0000000
--- a/social_mpc/ssn_model/group_detection/gcff/gcff.py
+++ /dev/null
@@ -1,94 +0,0 @@
-# This file, part of Social MPC in the WP6 of the Spring project,
-# is part of a project that has received funding from the
-# European Union’s Horizon 2020 research and innovation programme
-# under grant agreement No 871245.
-#
-# Copyright (C) 2020-2022 by Inria
-# Authors : Chris Reinke, Alex Auternaud, Timothée Wintz
-# chris.reinke@inria.fr
-# alex.auternaud@inria.fr
-# timothee.wintz@inria.fr
-
-import numpy as np
-import pygco
-
-
-class Group:
- def __init__(self, center, person_ids):
- self.center = center
- self.person_ids = person_ids
-
-
-def identify_groups(persons, **parameters):
- stride = parameters.get('stride',
- 1.0) # distance from to person to the center of its transactional space (aslo called D)
- # minimum discription length parameter (also called sigma)
- mdl = parameters.get('mdl', 1.0)
- max_iter = parameters.get('max_iter', 100)
-
- n_persons = persons.shape[0]
-
- # calculate the center of the transactional space for each person and the initinal group centers
- transaction_segments = np.full((n_persons, 2), np.nan)
- group_centers = np.full((n_persons, 2), np.nan)
- for p_idx in range(n_persons):
- ts_x = persons[p_idx][0] + np.cos(persons[p_idx][2]) * stride
- ts_y = persons[p_idx][1] + np.sin(persons[p_idx][2]) * stride
-
- transaction_segments[p_idx, :] = [ts_x, ts_y]
- group_centers[p_idx, :] = [ts_x, ts_y]
-
- labels = np.arange(n_persons)
- distances = np.zeros((n_persons, n_persons))
-
- pairwise_cost = np.zeros_like(distances)
- cost_v = np.zeros((0, n_persons))
- cost_h = np.zeros((1, n_persons - 1))
- label_cost = np.ones(n_persons) * mdl
-
- if n_persons == 1:
- result = [Group(center=group_centers[0, :], person_ids=[0])]
- return result
-
- iter_count = 0
- while iter_count < max_iter:
-
- # calculate distance of each person to each group center
- for p_idx in range(n_persons):
- distances[p_idx, :] = np.sqrt(
- np.sum((transaction_segments[p_idx] - group_centers) ** 2, 1))
-
- # perform graph cut for 1 iteration
- old_labels = labels
- labels = pygco.cut_grid_graph(np.array([distances]),
- pairwise_cost=pairwise_cost,
- cost_v=cost_v,
- cost_h=cost_h,
- label_cost=label_cost,
- n_iter=-1)
-
- # stop if there is no change of labels
- if np.all(old_labels == labels):
- break
-
- # recalculate the group centers
- for g_idx in range(group_centers.shape[0]):
- # people in that group
- people_in_group_inds = (labels == g_idx)
-
- if np.any(people_in_group_inds):
- group_centers[g_idx, :] = np.mean(
- transaction_segments[people_in_group_inds, :], 0)
-
- iter_count += 1
-
- result = []
-
- for g_idx in range(group_centers.shape[0]):
- # people in that group
- people_in_group = np.where(labels == g_idx)[0].tolist()
- if len(people_in_group):
- result.append(
- Group(center=group_centers[g_idx, :], person_ids=people_in_group))
-
- return result
diff --git a/social_mpc/ssn_model/group_detection/utils.py b/social_mpc/ssn_model/group_detection/utils.py
deleted file mode 100644
index 23d4418..0000000
--- a/social_mpc/ssn_model/group_detection/utils.py
+++ /dev/null
@@ -1,19 +0,0 @@
-import numpy as np
-
-def group_labels_to_lists(group_labels):
- '''Converts a group labels (list with id of the group for each person) to a group list.'''
-
- group_labels = np.array(group_labels)
-
- group_list = []
-
- group_ids = set(group_labels)
-
- for group_id in group_ids:
- cur_group_inds = (group_labels == group_id)
-
- if np.sum(cur_group_inds) > 1:
- group_list.append(np.where(cur_group_inds)[0])
-
- return group_list
-
--
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