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utils.py
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utils.py
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import random
import json
import re
import os
import copy
import numpy as np
from .environment import EnvironmentGraph, Property, Room
from .execution import SitExecutor, LieExecutor
random.seed(123)
def get_visible_nodes(graph, agent_id):
# Obtains partial observation from the perspective of agent_id
# That is, objects inside the same room as agent_id and not inside closed containers
# NOTE: Assumption is that the graph has an inside transition that is not transitive
state = graph
id2node = {node['id']: node for node in state['nodes']}
rooms_ids = [node['id'] for node in graph['nodes'] if node['category'] == 'Rooms']
character = id2node[agent_id]
# find character
character_id = character["id"]
inside_of, is_inside, edge_from = {}, {}, {}
grabbed_ids = []
for edge in state['edges']:
if edge['relation_type'] == 'INSIDE':
if edge['to_id'] not in is_inside.keys():
is_inside[edge['to_id']] = []
is_inside[edge['to_id']].append(edge['from_id'])
inside_of[edge['from_id']] = edge['to_id']
elif 'HOLDS' in edge['relation_type']:
if edge['from_id'] == character['id']:
grabbed_ids.append(edge['to_id'])
character_inside_ids = inside_of[character_id]
room_id = character_inside_ids
object_in_room_ids = is_inside[room_id]
# Some object are not directly in room, but we want to add them
curr_objects = list(object_in_room_ids)
while len(curr_objects) > 0:
objects_inside = []
for curr_obj_id in curr_objects:
new_inside = is_inside[curr_obj_id] if curr_obj_id in is_inside.keys() else []
objects_inside += new_inside
object_in_room_ids += list(objects_inside)
curr_objects = list(objects_inside)
# Only objects that are inside the room and not inside something closed
# TODO: this can be probably speed up if we can ensure that all objects are either closed or open
object_hidden = lambda ido: inside_of[ido] not in rooms_ids and 'OPEN' not in id2node[inside_of[ido]]['states']
observable_object_ids = [object_id for object_id in object_in_room_ids if not object_hidden(object_id)] + rooms_ids
observable_object_ids += grabbed_ids
partilly_observable_state = {
"edges": [edge for edge in state['edges'] if edge['from_id'] in observable_object_ids and edge['to_id'] in observable_object_ids],
"nodes": [id2node[id_node] for id_node in observable_object_ids]
}
return partilly_observable_state
def load_graph(file_name):
with open(file_name) as f:
data = json.load(f)
return EnvironmentGraph(data)
def load_graph_dict(file_name):
with open(file_name) as f:
data = json.load(f)
return data
def load_name_equivalence(file_name='../../resources/class_name_equivalence.json'):
abs_dir_path = os.path.dirname(os.path.abspath(__file__))
file_name_all = os.path.join(abs_dir_path, file_name)
with open(file_name_all, 'r') as f:
return json.load(f)
def load_object_states(file_name='../../resources/object_states.json'):
abs_dir_path = os.path.dirname(os.path.abspath(__file__))
file_name_all = os.path.join(abs_dir_path, file_name)
with open(file_name_all, 'r') as f:
file_content = json.load(f)
obj_keys = list(file_content.keys())
for name in obj_keys:
file_content[name.replace('_', '')] = file_content[name]
return file_content
def load_object_placing(file_name='../../resources/object_script_placing.json'):
abs_dir_path = os.path.dirname(os.path.abspath(__file__))
file_name_all = os.path.join(abs_dir_path, file_name)
with open(file_name_all, 'r') as f:
return json.load(f)
def load_properties_data(file_name='../../resources/properties_data.json'):
abs_dir_path = os.path.dirname(os.path.abspath(__file__))
file_name_all = os.path.join(abs_dir_path, file_name)
with open(file_name_all, 'r') as f:
pd_dict = json.load(f)
return {key: [Property[p] for p in props] for (key, props) in pd_dict.items()}
def build_unity2object_script(script_object2unity_object):
"""Builds mapping from Unity 2 Script objects. It works by creating connected
components between objects: A: [c, d], B: [f, e]. Since they share
one object, A, B, c, d, f, e should be merged
"""
unity_object2script_object = {}
object_script_merge = {}
for k, vs in script_object2unity_object.items():
vs = [x.lower().replace('_', '') for x in vs]
kmod = k.lower().replace('_', '')
object_script_merge[k] = [kmod] + vs
if kmod in unity_object2script_object:
prev_parent = unity_object2script_object[kmod]
dest_parent = prev_parent
source_parent = k
if len(k) < len(prev_parent) and prev_parent != 'computer':
dest_parent = k
source_parent = prev_parent
children_source = object_script_merge[source_parent]
object_script_merge[dest_parent] += children_source
for child in children_source: unity_object2script_object[child] = dest_parent
else:
unity_object2script_object[kmod] = k
for v in vs:
if v in unity_object2script_object:
prev_parent = unity_object2script_object[v]
dest_parent = prev_parent
source_parent = k
if len(k) < len(prev_parent) and prev_parent != 'computer':
dest_parent = k
source_parent = prev_parent
children_source = object_script_merge[source_parent]
object_script_merge[dest_parent] += children_source
for child in children_source: unity_object2script_object[child] = dest_parent
else:
unity_object2script_object[v] = k
return unity_object2script_object
class BinaryVariable(object):
def __init__(self, v_list, default):
assert default in v_list
v1, v2 = v_list
self.default = default
if default == v1:
self.negative = v2
self.positive = v1
else:
self.positive = v2
self.negative = v1
def invert(self):
if self.default == self.positive:
self.default = self.negative
else:
self.default = self.positive
def set_to_default_state(self, node):
while self.negative in node["states"]:
node["states"].remove(self.negative)
if self.positive not in node["states"]:
node["states"].append(self.positive)
def sample_state(self, node):
sampled_state = random.choice([self.positive, self.negative])
self.set_node_state(node, sampled_state)
def set_node_state(self, node, node_state):
assert node_state in [self.positive, self.negative]
if node_state == self.positive:
remove_state = self.negative
else:
remove_state = self.positive
while remove_state in node["states"]:
node["states"].remove(remove_state)
if node_state not in node["states"]:
node["states"].append(node_state)
def check(self, node, verbose):
if self.positive not in node["states"] and self.negative not in node["states"]:
if verbose:
print("Neither {} nor {} in states".format(self.positive, self.negative), node)
return False
if not ((self.positive in node["states"] and self.negative not in node["states"]) or (self.positive not in node["states"] and self.negative in node["states"])):
if verbose:
print("Should exist at least on {}, {}".format(self.positive, self.negative), node)
return False
if self.positive in node["states"] and len([s for s in node["states"] if s == self.positive]) != 1:
if verbose:
print("Too many {} in states".format(self.positive))
self.set_node_state(node, self.positive)
if self.negative in node["states"] and len([s for s in node["states"] if s == self.negative]) != 1:
if verbose:
print("Too many {} in states".format(self.negative))
self.set_node_state(node, self.negative)
return True
class graph_dict_helper(object):
def __init__(self, properties_data=None, object_placing=None, object_states=None, max_nodes=300):
if properties_data is None:
properties_data = load_properties_data()
if object_placing is None:
object_placing = load_object_placing()
if object_states is None:
object_states = load_object_states()
self.properties_data = properties_data
self.object_placing = object_placing
self.object_states = object_states
self.max_nodes = max_nodes
self.open_closed = BinaryVariable(["OPEN", "CLOSED"], default="CLOSED")
self.on_off = BinaryVariable(["ON", "OFF"], default="OFF")
self.clean_dirty = BinaryVariable(["CLEAN", "DIRTY"], default="CLEAN")
self.plugged_in_out = BinaryVariable(["PLUGGED_IN", "PLUGGED_OUT"], default="PLUGGED_IN")
self.binary_variables = [self.open_closed, self.on_off, self.clean_dirty, self.plugged_in_out]
self.body_part = ['face', 'leg', 'arm', 'eye', 'hand', 'feet']
self.possible_rooms = ['home_office', 'kitchen', 'living_room', 'bathroom', 'dining_room', 'bedroom', 'kids_bedroom', 'entrance_hall']
self.script_object2unity_object = load_name_equivalence()
self.unity_object2script_object = build_unity2object_script(self.script_object2unity_object)
self.equivalent_rooms = {
"kitchen": "dining_room",
"dining_room": "kitchen",
"entrance_hall": "living_room",
"home_office": "living_room",
"living_room": "home_office",
"kids_bedroom": "bedroom"
}
# precondition to simulator
self.relation_script_precond_simulator = {
"inside": "INSIDE",
"location": "INSIDE",
"atreach": "CLOSE",
"in": "ON"
}
self.states_script_precond_simulator = {
"dirty": "DIRTY",
"clean": "CLEAN",
"open": "OPEN",
"closed": "CLOSED",
"plugged": "PLUGGED_IN",
"unplugged": "PLUGGED_OUT",
"is_on": "ON",
"is_off": "OFF",
"sitting": "SITTING",
"lying": "LYING"
}
# object_placing.json
self.relation_placing_simulator = {
"in": "INSIDE",
"on": "ON",
"nearby": "CLOSE"
}
# object_states.json
self.states_mapping = {
"dirty": "dirty",
"clean": "clean",
"open": "open",
"closed": "closed",
"plugged": "plugged_in",
"unplugged": "plugged_out",
"on": "on",
"off": "off"
}
def initialize(self, graph_dict):
script_object_ids = [node["id"] for node in filter(lambda v: v["id"] >= 1000 and v["id"] < 2000, graph_dict["nodes"])]
random_object_ids = [node["id"] for node in filter(lambda v: v["id"] >= 2000, graph_dict["nodes"])]
self.script_objects_id = max(script_object_ids) if len(script_object_ids) != 0 else 1000
self.random_objects_id = max(random_object_ids) if len(random_object_ids) != 0 else 2000
def check_binary(self, graph_dict, id_checker, verbose):
open_closed = self.open_closed
on_off = self.on_off
plugged_in_out = self.plugged_in_out
for node in graph_dict["nodes"]:
if id_checker(node["id"]):
# always set to off, closed, open, clean
if "CAN_OPEN" in node["properties"]:
if not open_closed.check(node, verbose):
open_closed.set_to_default_state(node)
if "HAS_PLUG" in node["properties"]:
if not plugged_in_out.check(node, verbose):
plugged_in_out.set_to_default_state(node)
if "HAS_SWTICH" in node["properties"]:
if not on_off.check(node, verbose):
on_off.set_to_default_state(node)
if "light" in node["class_name"] or "lamp" in node["class_name"]:
if not on_off.check(node, verbose):
on_off.set_node_state(node, "ON")
if node["category"] == "Doors":
if not open_closed.check(node, verbose):
open_closed.set_node_state(node, "OPEN")
def open_all_doors(self, graph_dict):
open_closed = self.open_closed
for node in graph_dict["nodes"]:
if node["category"] == "Doors":
open_closed.set_node_state(node, "OPEN")
def get_object_binary_variables(self, object_name):
'''
For a given object name, obtains the binary variables
'''
if object_name in self.object_states:
states = self.object_states[object_name]
else:
states = []
bin_vars = self.get_binary_variables(states)
return bin_vars
def get_binary_variables(self, possible_states):
'''
Given a set of possible_states, returns the binary_variables associated
'''
added_variables = []
state_to_bin_var = {}
added_variables_default = []
for bin_var in self.binary_variables:
state_to_bin_var[bin_var.positive] = (bin_var, bin_var.default)
state_to_bin_var[bin_var.negative] = (bin_var, bin_var.default)
for state in possible_states:
if state.upper() in state_to_bin_var:
bin_var, default_var = state_to_bin_var[state.upper()]
if default_var not in added_variables_default:
added_variables.append(bin_var)
added_variables_default.append(default_var)
return added_variables
def set_to_default_state(self, graph_dict, first_room, id_checker):
open_closed = self.open_closed
on_off = self.on_off
clean_dirty = self.clean_dirty
plugged_in_out = self.plugged_in_out
body_part = self.body_part
character_id = [i["id"] for i in filter(lambda v: v["class_name"] == 'character', graph_dict["nodes"])][0]
for node in graph_dict["nodes"]:
if id_checker(node["id"]):
# always set to off, closed, open, clean
if "CAN_OPEN" in node["properties"]:
open_closed.set_to_default_state(node)
if node["class_name"] == "door":
open_closed.set_node_state(node, "OPEN")
if "HAS_PLUG" in node["properties"]:
plugged_in_out.set_to_default_state(node)
if "HAS_SWTICH" in node["properties"]:
on_off.set_to_default_state(node)
clean_dirty.set_to_default_state(node)
if node["class_name"] == 'character' and first_room is not None:
# character is not sitting, lying, holding, not close to anything
graph_dict["edges"] = [e for e in filter(lambda e: e["from_id"] != character_id and e["to_id"] != character_id, graph_dict["edges"])]
# set the character inside the pre-specified room
first_room_id = [i["id"] for i in filter(lambda v: v['class_name'] == first_room, graph_dict["nodes"])][0]
graph_dict["edges"].append({"relation_type": "INSIDE", "from_id": character_id, "to_id": first_room_id})
node["states"] = []
if "light" in node["class_name"] or "lamp" in node["class_name"]:
on_off.set_node_state(node, "ON")
if node["category"] == "Doors":
open_closed.set_node_state(node, "OPEN")
if any([Property.BODY_PART in node["properties"] for v in body_part]):
graph_dict["edges"].append({"relation_type": "CLOSE", "from_id": character_id, "to_id": node["id"]})
graph_dict["edges"].append({"relation_type": "CLOSE", "from_id": node["id"], "to_id": character_id})
def _add_missing_node(self, graph_dict, id, obj, category):
graph_dict['nodes'].append({
"properties": [i.name for i in self.properties_data[obj]],
"id": id,
"states": [],
"category": category,
"class_name": obj
})
def _random_pick_a_room_with_objects_name_in_graph(self, available_rooms_in_graph, available_rooms_in_graph_id, objects_in_script, available_nodes, graph_dict):
# Room is not specified in this program, assign one to it
hist = np.zeros(len(available_rooms_in_graph_id))
for obj in objects_in_script:
obj_name = obj[0]
if obj_name == 'character':
continue
for node in available_nodes:
if node['class_name'] == obj_name:
edges = [i for i in filter(lambda v: v['relation_type'] == 'INSIDE' and v['from_id'] == node['id'] and v['to_id'] in available_rooms_in_graph_id, graph_dict["edges"])]
if len(edges) > 0:
for edge in edges:
dest_id = edge['to_id']
idx = available_rooms_in_graph_id.index(dest_id)
hist[idx] += 1
if hist.std() < 1e-5:
room_name = random.choice(available_rooms_in_graph)
else:
idx = np.argmax(hist)
room_name = available_rooms_in_graph[idx]
return room_name
def _any_room_except(self, first_room, available_rooms_in_graph):
available_rooms = copy.deepcopy(available_rooms_in_graph)
available_rooms.remove(first_room)
return random.choice(available_rooms)
def modify_script_with_specified_id(self, script, id_mapping, room_mapping):
# change the id in script
for script_line in script:
for parameter in script_line.parameters:
if parameter.name in self.possible_rooms:
parameter.name = room_mapping[parameter.name]
try:
assert (parameter.name, parameter.instance) in id_mapping
except:
print(parameter.name, parameter.instance)
print(id_mapping)
assert (parameter.name, parameter.instance) in id_mapping
parameter.instance = id_mapping[(parameter.name, parameter.instance)]
def ensure_light_on(self, graph_dict, id_checker):
on_off = self.on_off
for node in graph_dict["nodes"]:
if 'light' in node["class_name"] or 'lamp' in node["class_name"]:
if id_checker(node["id"]):
if "ON" not in node["states"]:
while "OFF" in node["states"]:
node["states"].remove("OFF")
on_off.set_node_state(node, "ON")
def add_missing_object_from_script(self, script, precond, graph_dict, id_mapping):
equivalent_rooms = self.equivalent_rooms
possible_rooms = self.possible_rooms
available_rooms_in_graph = [i['class_name'] for i in filter(lambda v: v["category"] == 'Rooms', graph_dict['nodes'])]
available_rooms_in_graph_id = [i['id'] for i in filter(lambda v: v["category"] == 'Rooms', graph_dict['nodes'])]
available_nodes = copy.deepcopy(graph_dict['nodes'])
available_name = list(set([node['class_name'] for node in available_nodes]))
# create room mapping
room_mapping = {}
for room in possible_rooms:
nroom = room
rooms_tried = []
while nroom not in available_rooms_in_graph and nroom not in rooms_tried:
rooms_tried.append(nroom)
assert nroom in equivalent_rooms, "Not pre-specified mapping for room: {}".format(nroom)
nroom = equivalent_rooms[nroom]
# nroom = nroom.replace('_', '')
try:
assert nroom in available_rooms_in_graph, "No equivalent room in graph for room: {}".format(nroom)
except:
print(nroom, rooms_tried, available_rooms_in_graph)
room_mapping[room] = nroom
# use room mapping to change the precond (in-place opetation)
for precond_i in precond:
if 'location' in precond_i:
room = precond_i['location'][1][0]
precond_i['location'][1][0] = room_mapping[room]
# apply room mapping to the script
for script_line in script:
for parameter in script_line.parameters:
if parameter.name in possible_rooms:
parameter.name = room_mapping[parameter.name]
# find the first room
first_room = None
for script_line in script:
for parameter in script_line.parameters:
if parameter.name in possible_rooms and first_room is None:
first_room = parameter.name
# initialize the `objects_in_script`
objects_in_script = {}
character_id = [i for i in filter(lambda v: v['class_name'] == 'character', graph_dict["nodes"])][0]["id"]
key = ('character', 1)
objects_in_script[key] = id_mapping[key] if key in id_mapping else character_id
for key in script.obtain_objects():
if key not in objects_in_script:
objects_in_script[key] = id_mapping[key] if key in id_mapping else None
# set up the first room
#location_precond = {tuple(i['location'][0]): i['location'][1][0] for i in filter(lambda v: 'location' in v, precond)}
location_precond = {(i['location'][0][0], int(i['location'][0][1])): i['location'][1][0] for i in filter(lambda v: 'location' in v, precond)}
rooms_in_precond = list(set([i for i in location_precond.values()]))
if first_room == None:
assert len(rooms_in_precond) == 0
first_room = self._random_pick_a_room_with_objects_name_in_graph(available_rooms_in_graph, available_rooms_in_graph_id, objects_in_script, available_nodes, graph_dict)
else:
first_room = self._any_room_except(first_room, available_rooms_in_graph)
assert first_room is not None and first_room in available_rooms_in_graph
# mapping objects
for obj in objects_in_script.keys():
# objects that are specified already
if objects_in_script[obj] is not None:
continue
room_obj = location_precond[obj] if obj in location_precond else first_room
room_id = [i["id"] for i in filter(lambda v: v['class_name'] == room_obj, graph_dict["nodes"])][0]
if obj[0] in possible_rooms:
id_to_be_assigned = [i["id"] for i in filter(lambda v: v["class_name"] == obj[0], graph_dict["nodes"])]
objects_in_script[obj] = id_to_be_assigned[0]
elif obj[0] in available_name:
added = False
possible_matched_nodes = [i for i in filter(lambda v: v['class_name'] == obj[0], available_nodes)]
# existing nodes
for node in possible_matched_nodes:
obj_in_room = [i for i in filter(lambda v: v['relation_type'] == 'INSIDE' and v['from_id'] == node['id'] and v["to_id"] == room_id, graph_dict["edges"])]
if len(obj_in_room) == 0:
continue
else:
objects_in_script[obj] = node['id']
available_nodes.remove(node)
added = True
break
if not added:
# add node
node_with_same_class_name = [node for node in filter(lambda v: v["class_name"] == obj[0], graph_dict["nodes"])]
category = node_with_same_class_name[0]['category']
self._add_missing_node(graph_dict, self.script_objects_id, obj[0], category)
objects_in_script[obj] = self.script_objects_id
# add edges
graph_dict["edges"].append({"relation_type": "INSIDE", "from_id": self.script_objects_id, "to_id": room_id})
self.script_objects_id += 1
else:
# add missing nodes
self._add_missing_node(graph_dict, self.script_objects_id, obj[0], 'placable_objects')
objects_in_script[obj] = self.script_objects_id
# add edges
graph_dict["edges"].append({"relation_type": "INSIDE", "from_id": self.script_objects_id, "to_id": room_id})
self.script_objects_id += 1
# change the id in script
for script_line in script:
for parameter in script_line.parameters:
parameter.instance = objects_in_script[(parameter.name, parameter.instance)]
return objects_in_script, first_room, room_mapping
def prepare_from_precondition(self, precond, objects_in_script, graph_dict):
object_placing = self.object_placing
objects_to_place = list(object_placing.keys())
relation_script_precond_simulator = self.relation_script_precond_simulator
states_script_precond_simulator = self.states_script_precond_simulator
open_closed = self.open_closed
on_off = self.on_off
clean_dirty = self.clean_dirty
plugged_in_out = self.plugged_in_out
for p in precond:
for k, v in p.items():
if k == 'location':
# handle when adding missing scripts
continue
if k in relation_script_precond_simulator:
src_name, src_id = v[0]
tgt_name, tgt_id = v[1]
src_id = int(src_id)
tgt_id = int(tgt_id)
src_id = objects_in_script[(src_name.lower().replace(' ', '_'), src_id)]
tgt_id = objects_in_script[(tgt_name.lower().replace(' ', '_'), tgt_id)]
graph_dict['edges'].append({'relation_type': relation_script_precond_simulator[k], 'from_id': src_id, 'to_id': tgt_id})
if k == 'atreach':
graph_dict['edges'].append({'relation_type': relation_script_precond_simulator[k], 'from_id': tgt_id, 'to_id': src_id})
elif k in states_script_precond_simulator:
obj_id = objects_in_script[(v[0].lower().replace(' ', '_'), int(v[1]))]
for node in graph_dict['nodes']:
if node['id'] == obj_id:
if k in ['is_on', 'is_off']:
on_off.set_node_state(node, states_script_precond_simulator[k])
elif k in ['open', 'closed']:
open_closed.set_node_state(node, states_script_precond_simulator[k])
elif k in ['dirty', 'clean']:
clean_dirty.set_node_state(node, states_script_precond_simulator[k])
elif k in ['plugged', 'unplugged']:
plugged_in_out.set_node_state(node, states_script_precond_simulator[k])
elif k == 'sitting':
if "SITTING" not in node["states"]: node["states"].append("SITTING")
elif k == 'lying':
if "LYING" not in node["states"]: node["states"].append("LYING")
break
elif k in ["occupied", "free"]:
obj_id = objects_in_script[(v[0].lower().replace(' ', '_'), int(v[1]))]
for node in graph_dict['nodes']:
if node['id'] == obj_id:
if k == 'free':
self._change_to_totally_free(node, graph_dict)
elif k == 'occupied':
self._change_to_occupied(node, graph_dict, objects_to_place)
break
def merge_object_name(self, object_name):
if object_name in self.script_object2unity_object:
unity_name = self.script_object2unity_object[object_name][0].replace('_', '')
else:
unity_name = object_name.replace('_', '')
if unity_name not in self.unity_object2script_object:
return object_name
return self.unity_object2script_object[unity_name]
def add_random_objs_graph_dict(self, graph_dict, n):
object_placing = self.object_placing
relation_placing_simulator = self.relation_placing_simulator
objects_to_place = list(object_placing.keys())
random.shuffle(objects_to_place)
rooms_id = [node["id"] for node in filter(lambda v: v['class_name'] in self.possible_rooms, graph_dict["nodes"])]
def _add_node(src_name, tgt_node, tgt_name):
tgt_id = tgt_node["id"]
self._add_missing_node(graph_dict, self.random_objects_id, src_name, "placable_objects")
specified_room_id = [edge["to_id"] for edge in filter(lambda v: v["from_id"] == tgt_id and v["relation_type"] == "INSIDE" and v["to_id"] in rooms_id, graph_dict["edges"])][0]
graph_dict["edges"].append({'relation_type': "INSIDE", "from_id": self.random_objects_id, "to_id": specified_room_id})
graph_dict["edges"].append({'relation_type': relation_placing_simulator[tgt_name["relation"].lower()], "from_id": self.random_objects_id, "to_id": tgt_id})
graph_dict["edges"].append({'relation_type': "CLOSE", "from_id": self.random_objects_id, "to_id": tgt_id})
graph_dict["edges"].append({'relation_type': "CLOSE", "from_id": tgt_id, "to_id": self.random_objects_id})
self.random_objects_id += 1
while n > 0:
src_name = random.choice(objects_to_place)
tgt_names = copy.deepcopy(object_placing[src_name])
# Merge object names
src_name = self.merge_object_name(src_name)
for tgt_name in tgt_names:
tgt_name['destination'] = self.merge_object_name(tgt_name['destination'])
random.shuffle(tgt_names)
for tgt_name in tgt_names:
tgt_nodes = [i for i in filter(lambda v: v["class_name"] == tgt_name['destination'], graph_dict["nodes"])]
if len(tgt_nodes) != 0:
max_occupancies = max(SitExecutor._MAX_OCCUPANCIES.get(tgt_name['destination'], 0), LieExecutor._MAX_OCCUPANCIES.get(tgt_name['destination'], 0))
if max_occupancies == 0:
tgt_node = random.choice(tgt_nodes)
_add_node(src_name, tgt_node, tgt_name)
n -= 1
break
else:
# find node with available space
free_tgt_nodes = []
for tgt_node in tgt_nodes:
occupied_edges = [_edge for _edge in filter(lambda v: v["relation_type"] == "ON" and v["to_id"] == tgt_node["id"] , graph_dict["edges"])]
if len(occupied_edges) < max_occupancies:
free_tgt_nodes.append(tgt_node)
if len(free_tgt_nodes) != 0:
tgt_node = random.choice(free_tgt_nodes)
_add_node(src_name, tgt_node, tgt_name)
n -= 1
break
def random_change_object_state(self, objects_in_script, graph_dict, id_checker):
open_closed = self.open_closed
on_off = self.on_off
clean_dirty = self.clean_dirty
plugged_in_out = self.plugged_in_out
object_states = self.object_states
states_mapping = self.states_mapping
available_states = ['dirty', 'clean', 'open', 'closed', 'free', 'occupied', 'plugged', 'unplugged', 'on', 'off']
for node in graph_dict["nodes"]:
if id_checker(node["id"]):
if node["class_name"] in object_states:
possible_states = object_states[node["class_name"]]
possible_states = [i for i in filter(lambda v: v in available_states, possible_states)]
if len(possible_states) == 0:
continue
state = random.choice(possible_states)
if state in ['free', 'occupied']:
# implemeted with `add_random_objs_graph_dict`
pass
else:
state = states_mapping[state]
if state in ['dirty', 'clean']:
clean_dirty.sample_state(node)
elif state in ['on', 'off']:
on_off.sample_state(node)
elif state in ['open', 'closed']:
open_closed.sample_state(node)
elif state in ['plugged_in', 'plugged_out']:
plugged_in_out.sample_state(node)
def _remove_one_random_nodes(self, graph_dict):
start_id = 2000
random_nodes_ids = [node["id"] for node in filter(lambda v: v["id"] >= start_id, graph_dict["nodes"])]
if len(random_nodes_ids) != 0:
remove_id = np.min(random_nodes_ids)
graph_dict["nodes"] = [node for node in filter(lambda v: v["id"] != remove_id, graph_dict["nodes"])]
graph_dict["edges"] = [edge for edge in filter(lambda v: v["from_id"] != remove_id and v["to_id"] != remove_id, graph_dict["edges"])]
def _change_to_occupied(self, node, graph_dict, objects_to_place):
if node["class_name"] in SitExecutor._MAX_OCCUPANCIES or node["class_name"] in LieExecutor._MAX_OCCUPANCIES:
name = node["class_name"]
max_occupancy = SitExecutor._MAX_OCCUPANCIES[name] if name in SitExecutor._MAX_OCCUPANCIES else LieExecutor._MAX_OCCUPANCIES[name]
occupied_edges = [_edge for _edge in filter(lambda v: v["relation_type"] == "ON" and v["to_id"] == node["id"] , graph_dict["edges"])]
current_state = 'free' if len(occupied_edges) < max(max_occupancy-1, 1) else "occupied"
if current_state != "occupied":
rooms_id = [_node["id"] for _node in filter(lambda v: v["category"] == 'Rooms', graph_dict["nodes"])]
room_id = None
for edge in graph_dict["edges"]:
if edge["relation_type"] == "INSIDE" and edge["from_id"] == node["id"] and edge["to_id"] in rooms_id:
room_id = edge["to_id"]
assert room_id is not None, print("{}({}) doesn't exist in any room".format(node["class_name"], node["id"]))
number_objects_to_add = max_occupancy - len(occupied_edges)
if number_objects_to_add < 0:
import ipdb
ipdb.set_trace()
object_placing = self.object_placing
random.shuffle(objects_to_place)
for src_name in objects_to_place:
tgt_names = object_placing[src_name]
src_name = self.merge_object_name(src_name)
for tgt_name in tgt_names:
tgt_name['destination'] = self.merge_object_name(tgt_name['destination'])
if name in [i["destination"] for i in filter(lambda v: v["relation"] == 'ON', tgt_names)]:
self._remove_one_random_nodes(graph_dict)
self._add_missing_node(graph_dict, self.random_objects_id, src_name, 'placable_objects')
graph_dict["edges"].append({"relation_type": "INSIDE", "from_id": self.random_objects_id, "to_id": room_id})
graph_dict["edges"].append({"relation_type": "ON", "from_id": self.random_objects_id, "to_id": node["id"]})
graph_dict["edges"].append({"relation_type": "CLOSE", "from_id": self.random_objects_id, "to_id": node["id"]})
graph_dict["edges"].append({"relation_type": "CLOSE", "from_id": node["id"], "to_id": self.random_objects_id})
self.random_objects_id += 1
number_objects_to_add -= 0
if number_objects_to_add <= 0:
break
def _change_to_totally_free(self, node, graph_dict):
if node["class_name"] in SitExecutor._MAX_OCCUPANCIES or node["class_name"] in LieExecutor._MAX_OCCUPANCIES:
occupied_edges = [_edge for _edge in filter(lambda v: v["relation_type"] == "ON" and v["to_id"] == node["id"] , graph_dict["edges"])]
occupied_nodes_id = [_edge["from_id"] for _edge in occupied_edges]
removed_edges = []
for occupied_node_id in occupied_nodes_id:
removed_edges += [edge for edge in filter(lambda v: v["from_id"] == occupied_node_id and v["to_id"] == node["id"], graph_dict["edges"])]
removed_edges += [edge for edge in filter(lambda v: v["from_id"] == node["id"] and v["to_id"] == occupied_node_id, graph_dict["edges"])]
for edge in removed_edges:
graph_dict["edges"].remove(edge)
floor_id = [_node["id"] for _node in filter(lambda v: v["class_name"] == 'floor', graph_dict["nodes"])]
for obj_id in occupied_nodes_id:
to_id = random.choice(floor_id)
graph_dict["edges"].append({"relation_type": "ON", "from_id": obj_id, "to_id": to_id})
graph_dict["edges"].append({"relation_type": "CLOSE", "from_id": obj_id, "to_id": to_id})
graph_dict["edges"].append({"relation_type": "CLOSE", "from_id": to_id, "to_id": obj_id})
def check_objs_in_room(self, graph_dict):
rooms_id = [node["id"] for node in filter(lambda v: v["category"] == 'Rooms', graph_dict["nodes"])]
other_id = [node["id"] for node in filter(lambda v: v["category"] != 'Rooms', graph_dict["nodes"])]
id2name = {node["id"]: node["class_name"] for node in graph_dict["nodes"]}
for id in other_id:
in_room = []
for edge in graph_dict["edges"]:
if edge["from_id"] == id and edge["relation_type"] == "INSIDE" and edge["to_id"] in rooms_id:
in_room.append(edge["to_id"])
if len(in_room) > 1:
print("src object: {}({})".format(id2name[id], id), "in_rooms:", ', '.join([id2name for i in in_room]))
print("exist in more than one room")
elif len(in_room) == 0:
print("src object: {}({})".format(id2name[id], id))