Large update with mostly rewritten character subsystem
This commit is contained in:
Segey Lapin
191
proto2/tests/test-collect-data.gd
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191
proto2/tests/test-collect-data.gd
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extends Spatial
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var ch
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var current_data = {}
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var nn
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func train(quality):
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var inputs = []
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var dk = current_data.keys()
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dk.sort()
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for k in dk:
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if k == "quality":
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continue
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inputs.push_back(current_data[k])
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nn.train(inputs, [quality])
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func guess():
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var inputs = []
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var dk = current_data.keys()
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dk.sort()
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for k in dk:
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if k == "quality":
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continue
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inputs.push_back(current_data[k])
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var outputs = nn.feedforward(inputs)
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$VBoxContainer/Label.text = str(outputs[0])
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func train_by_data():
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var data = []
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var fd = File.new()
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if fd.file_exists("res://tests/training_set.json"):
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fd.open("res://tests/training_set.json", File.READ)
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var json = JSON.parse(fd.get_as_text())
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data = json.result
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fd.close()
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for t in range(data.size() * 5):
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var inputs = []
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var dataset = data[randi() % data.size()]
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var dk = dataset.keys()
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dk.sort()
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for k in dk:
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if k == "quality":
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continue
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inputs.push_back(dataset[k])
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nn.train(inputs, [dataset["quality"]])
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var cdirty = false
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func change_scroll_value(value, mod_name):
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characters.set_modifier_value(ch, mod_name, float(value) / 100.0)
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cdirty = true
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func update_controls():
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for c in $VBoxContainer/s/b.get_children():
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c.queue_free()
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var mod_list = Array(characters.get_modifier_list(ch))
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mod_list.sort()
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for m in mod_list:
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var item = HBoxContainer.new()
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$VBoxContainer/s/b.add_child(item)
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var t = Label.new()
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item.add_child(t)
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t.rect_min_size.x = 100.0
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t.text = m
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var scroll = HScrollBar.new()
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item.add_child(scroll)
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scroll.rect_min_size.x = 100.0
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scroll.rect_min_size.y = 4.0
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scroll.min_value = -100.0
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scroll.max_value = 100.0
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scroll.value = characters.get_modifier_value(ch, m) * 100.0
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scroll.connect("value_changed", self, "change_scroll_value", [m])
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func save_data(quality):
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var data = []
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var fd = File.new()
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if fd.file_exists("res://tests/training_set.json"):
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fd.open("res://tests/training_set.json", File.READ)
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var json = JSON.parse(fd.get_as_text())
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data = json.result
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fd.close()
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current_data["quality"] = quality
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data.push_back(current_data)
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fd.open("res://tests/training_set.json", File.WRITE)
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fd.store_string(JSON.print(data, "\t", true))
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fd.close()
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print(current_data.keys().size())
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func get_skeleton(base: Node):
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var queue = [base]
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var skel: Skeleton
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while queue.size() > 0:
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var item = queue[0]
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queue.pop_front()
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if item is Skeleton:
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skel = item
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break
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for c in item.get_children():
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queue.push_back(c)
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return skel
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func get_head_pos():
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var skel = get_skeleton(ch)
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var head_id = skel.find_bone("head")
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var xform = skel.get_bone_global_pose(head_id)
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return skel.global_transform.xform(xform.origin)
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var rotate = 0
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func select_ok():
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train(0.5)
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save_data(0.5)
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remove()
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call_deferred("spawn")
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func select_bad():
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train(0.0)
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save_data(0.0)
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remove()
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call_deferred("spawn")
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func select_good():
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train(1.0)
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save_data(1.0)
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remove()
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call_deferred("spawn")
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func trigger_cam():
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if $r/Camera.current:
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$r/face_cam.global_transform.origin = get_head_pos() + Vector3(0, 0, 0.4)
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$r/face_cam.make_current()
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elif $r/face_cam.current:
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$r/Camera.make_current()
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func trigger_rotate():
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rotate += 1
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match(rotate):
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0:
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$r.rotation.y = 0.0
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1:
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$r.rotation.y = PI / 2.0
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2:
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$r.rotation.y = PI
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3:
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$r.rotation.y = PI * 3.0 / 4.0
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5:
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rotate = 0
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$r.rotation.y = 0.0
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func _ready():
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$r/Camera.fov = 50.0
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$VBoxContainer/bad.connect("pressed", self, "select_bad")
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$VBoxContainer/ok.connect("pressed", self, "select_ok")
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$VBoxContainer/good.connect("pressed", self, "select_good")
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$VBoxContainer/face_trig.connect("pressed", self, "trigger_cam")
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$VBoxContainer/rotate.connect("pressed", self, "trigger_rotate")
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# characters.set_root_scene(self)
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call_deferred("init_tail")
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func init_tail():
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remove()
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spawn()
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nn = NeuralNetwork.new(current_data.keys().size(), 160, 1)
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train_by_data()
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guess()
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print(characters.get_modifier_list(ch))
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var gender = -1
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func spawn():
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if randf() >= 0.5:
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gender = 1
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else:
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gender = 0
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ch = characters.spawn_character(gender, Transform().rotated(Vector3(0, 1, 0), PI))
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current_data["gender"] = gender
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var mod_name_list = characters.get_modifier_list(ch)
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for cset in range(mod_name_list.size()):
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var _mod_id = mod_name_list[cset]
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var _mod_val = randf() * 1.5 - 0.75
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characters.set_modifier_value(ch, _mod_id, _mod_val)
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current_data[_mod_id] = _mod_val
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# characters.modify(ch)
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characters.update()
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if nn:
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guess()
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update_controls()
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func remove():
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if ch:
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characters.remove(ch)
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func _process(delta):
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if rotate == 4:
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$r.rotation.y += delta
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if cdirty:
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characters.update()
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var mod_name_list = characters.get_modifier_list(ch)
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for cset in range(mod_name_list.size()):
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var _mod_id = mod_name_list[cset]
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current_data[_mod_id] = characters.get_modifier_value(ch, _mod_id)
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