mirror of
https://github.com/illiumst/marl-factory-grid.git
synced 2025-10-31 12:37:27 +01:00
added policy_adaption
This commit is contained in:
romue
@@ -1,64 +0,0 @@
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from gym.envs.registration import register
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# Env registration
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# ==========================
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register(
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id='CarRacingColor-v0',
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entry_point='car_racing_variants.car_racing:CarRacing',
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max_episode_steps=1000,
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reward_threshold=900.0,
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kwargs={
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'modification': 'color',
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},
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)
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register(
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id='CarRacingColor3-v0',
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entry_point='car_racing_variants.car_racing:CarRacing',
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max_episode_steps=1000,
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reward_threshold=900.0,
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kwargs={
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'modification': 'color3',
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},
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)
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register(
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id='CarRacingBar-v0',
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entry_point='car_racing_variants.car_racing:CarRacing',
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max_episode_steps=1000,
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reward_threshold=900.0,
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kwargs={
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'modification': 'bar',
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},
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)
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register(
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id='CarRacingBlob-v0',
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entry_point='car_racing_variants.car_racing:CarRacing',
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max_episode_steps=1000,
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reward_threshold=900.0,
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kwargs={
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'modification': 'blob',
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},
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)
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register(
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id='CarRacingNoise-v0',
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entry_point='car_racing_variants.car_racing:CarRacing',
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max_episode_steps=1000,
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reward_threshold=900.0,
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kwargs={
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'modification': 'noise',
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},
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)
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register(
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id='CarRacingVideo-v0',
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entry_point='car_racing_variants.car_racing:CarRacing',
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max_episode_steps=1000,
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reward_threshold=900.0,
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kwargs={
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'modification': 'video',
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},
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)
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@@ -1,289 +0,0 @@
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"""This file is based on the car_dynamics.py in OpenAI's gym.
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Description
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We provide some modified CarRacing environments here:
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* CarRacingColor-v0
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Both the lane and the grass colors are perturbed at the env.reset() with scalar noises.
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* CarRacingColor3-v0
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Both the lane and the grass colors are perturbed at the env.reset() with 3d noises.
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* CarRacingBar-v0
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We add vertical bars on the left and right side of the screen.
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* CarRacingBlob-v0
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A red blob that follows the car at a fixed position in the car's frame.
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* CarRacingNoise-v0
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We replace the green background with noise.
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* CarRacingVideo-v0
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We replace the green background with frames from a video, the user is
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responsible for creating these frames and pass the directory.
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These environments were first used in the paper "Neuroevolution of Self-Interpretable Agent"
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https://attentionagent.github.io/
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Author
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Yujin Tang (yujintang@google.com)
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"""
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import numpy as np
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import math
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import Box2D
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from Box2D.b2 import (edgeShape, circleShape, fixtureDef, polygonShape, revoluteJointDef, contactListener, shape)
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# Top-down car dynamics simulation.
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#
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# Some ideas are taken from this great tutorial http://www.iforce2d.net/b2dtut/top-down-car by Chris Campbell.
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# This simulation is a bit more detailed, with wheels rotation.
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#
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# Created by Oleg Klimov. Licensed on the same terms as the rest of OpenAI Gym.
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SIZE = 0.02
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ENGINE_POWER = 100000000*SIZE*SIZE
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WHEEL_MOMENT_OF_INERTIA = 4000*SIZE*SIZE
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FRICTION_LIMIT = 1000000*SIZE*SIZE # friction ~= mass ~= size^2 (calculated implicitly using density)
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WHEEL_R = 27
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WHEEL_W = 14
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WHEELPOS = [
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(-55,+80), (+55,+80),
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(-55,-82), (+55,-82)
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]
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HULL_POLY1 =[
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(-60,+130), (+60,+130),
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(+60,+110), (-60,+110)
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]
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HULL_POLY2 =[
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(-15,+120), (+15,+120),
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(+20, +20), (-20, 20)
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]
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HULL_POLY3 =[
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(+25, +20),
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(+50, -10),
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(+50, -40),
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(+20, -90),
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(-20, -90),
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(-50, -40),
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(-50, -10),
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(-25, +20)
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]
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HULL_POLY4 =[
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(-50,-120), (+50,-120),
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(+50,-90), (-50,-90)
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]
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WHEEL_COLOR = (0.0,0.0,0.0)
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WHEEL_WHITE = (0.3,0.3,0.3)
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MUD_COLOR = (0.4,0.4,0.0)
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class Car:
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def __init__(self, world, init_angle, init_x, init_y, add_blob=False):
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self.world = world
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self.add_blob = add_blob
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fixtures = [
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fixtureDef(shape=polygonShape(
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vertices=[ (x*SIZE,y*SIZE) for x,y in HULL_POLY1 ]), density=1.0),
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fixtureDef(shape=polygonShape(
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vertices=[ (x*SIZE,y*SIZE) for x,y in HULL_POLY2 ]), density=1.0),
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fixtureDef(shape=polygonShape(
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vertices=[ (x*SIZE,y*SIZE) for x,y in HULL_POLY3 ]), density=1.0),
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fixtureDef(shape=polygonShape(
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vertices=[ (x*SIZE,y*SIZE) for x,y in HULL_POLY4 ]), density=1.0),
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]
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self.hull = self.world.CreateDynamicBody(
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position = (init_x, init_y),
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angle = init_angle,
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fixtures = fixtures,
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)
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self.hull.color = (0.8,0.0,0.0)
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self.wheels = []
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self.fuel_spent = 0.0
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WHEEL_POLY = [
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(-WHEEL_W,+WHEEL_R), (+WHEEL_W,+WHEEL_R),
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(+WHEEL_W,-WHEEL_R), (-WHEEL_W,-WHEEL_R)
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]
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for wx,wy in WHEELPOS:
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front_k = 1.0 if wy > 0 else 1.0
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w = self.world.CreateDynamicBody(
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position = (init_x+wx*SIZE, init_y+wy*SIZE),
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angle = init_angle,
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fixtures = fixtureDef(
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shape=polygonShape(vertices=[ (x*front_k*SIZE,y*front_k*SIZE) for x,y in WHEEL_POLY ]),
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density=0.1,
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categoryBits=0x0020,
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maskBits=0x001,
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restitution=0.0)
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)
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w.wheel_rad = front_k*WHEEL_R*SIZE
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w.color = WHEEL_COLOR
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w.gas = 0.0
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w.brake = 0.0
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w.steer = 0.0
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w.phase = 0.0 # wheel angle
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w.omega = 0.0 # angular velocity
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w.skid_start = None
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w.skid_particle = None
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rjd = revoluteJointDef(
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bodyA=self.hull,
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bodyB=w,
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localAnchorA=(wx*SIZE,wy*SIZE),
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localAnchorB=(0,0),
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enableMotor=True,
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enableLimit=True,
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maxMotorTorque=180*900*SIZE*SIZE,
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motorSpeed = 0,
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lowerAngle = -0.4,
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upperAngle = +0.4,
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)
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w.joint = self.world.CreateJoint(rjd)
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w.tiles = set()
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w.userData = w
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self.wheels.append(w)
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self.drawlist = self.wheels + [self.hull]
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self.particles = []
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def gas(self, gas):
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'control: rear wheel drive'
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gas = np.clip(gas, 0, 1)
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for w in self.wheels[2:4]:
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diff = gas - w.gas
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if diff > 0.1: diff = 0.1 # gradually increase, but stop immediately
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w.gas += diff
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def brake(self, b):
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'control: brake b=0..1, more than 0.9 blocks wheels to zero rotation'
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for w in self.wheels:
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w.brake = b
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def steer(self, s):
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'control: steer s=-1..1, it takes time to rotate steering wheel from side to side, s is target position'
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self.wheels[0].steer = s
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self.wheels[1].steer = s
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def step(self, dt):
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for w in self.wheels:
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# Steer each wheel
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dir = np.sign(w.steer - w.joint.angle)
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val = abs(w.steer - w.joint.angle)
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w.joint.motorSpeed = dir*min(50.0*val, 3.0)
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# Position => friction_limit
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grass = True
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friction_limit = FRICTION_LIMIT*0.6 # Grass friction if no tile
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for tile in w.tiles:
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friction_limit = max(friction_limit, FRICTION_LIMIT*tile.road_friction)
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grass = False
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# Force
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forw = w.GetWorldVector( (0,1) )
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side = w.GetWorldVector( (1,0) )
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v = w.linearVelocity
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vf = forw[0]*v[0] + forw[1]*v[1] # forward speed
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vs = side[0]*v[0] + side[1]*v[1] # side speed
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# WHEEL_MOMENT_OF_INERTIA*np.square(w.omega)/2 = E -- energy
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# WHEEL_MOMENT_OF_INERTIA*w.omega * domega/dt = dE/dt = W -- power
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# domega = dt*W/WHEEL_MOMENT_OF_INERTIA/w.omega
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w.omega += dt*ENGINE_POWER*w.gas/WHEEL_MOMENT_OF_INERTIA/(abs(w.omega)+5.0) # small coef not to divide by zero
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self.fuel_spent += dt*ENGINE_POWER*w.gas
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if w.brake >= 0.9:
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w.omega = 0
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elif w.brake > 0:
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BRAKE_FORCE = 15 # radians per second
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dir = -np.sign(w.omega)
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val = BRAKE_FORCE*w.brake
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if abs(val) > abs(w.omega): val = abs(w.omega) # low speed => same as = 0
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w.omega += dir*val
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w.phase += w.omega*dt
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vr = w.omega*w.wheel_rad # rotating wheel speed
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f_force = -vf + vr # force direction is direction of speed difference
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p_force = -vs
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# Physically correct is to always apply friction_limit until speed is equal.
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# But dt is finite, that will lead to oscillations if difference is already near zero.
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f_force *= 205000*SIZE*SIZE # Random coefficient to cut oscillations in few steps (have no effect on friction_limit)
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p_force *= 205000*SIZE*SIZE
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force = np.sqrt(np.square(f_force) + np.square(p_force))
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# Skid trace
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if abs(force) > 2.0*friction_limit:
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if w.skid_particle and w.skid_particle.grass==grass and len(w.skid_particle.poly) < 30:
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w.skid_particle.poly.append( (w.position[0], w.position[1]) )
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elif w.skid_start is None:
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w.skid_start = w.position
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else:
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w.skid_particle = self._create_particle( w.skid_start, w.position, grass )
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w.skid_start = None
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else:
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w.skid_start = None
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w.skid_particle = None
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if abs(force) > friction_limit:
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f_force /= force
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p_force /= force
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force = friction_limit # Correct physics here
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f_force *= force
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p_force *= force
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w.omega -= dt*f_force*w.wheel_rad/WHEEL_MOMENT_OF_INERTIA
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w.ApplyForceToCenter( (
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p_force*side[0] + f_force*forw[0],
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p_force*side[1] + f_force*forw[1]), True )
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def draw(self, viewer, draw_particles=True):
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if draw_particles:
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for p in self.particles:
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viewer.draw_polyline(p.poly, color=p.color, linewidth=5)
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for obj in self.drawlist:
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for i, f in enumerate(obj.fixtures):
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trans = f.body.transform
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path = [trans*v for v in f.shape.vertices]
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if self.add_blob and i == 3:
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obj_color = (0.8, 0.0, 0.)
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offset_x = f.shape.vertices[0][0] + 20
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offset_y = f.shape.vertices[0][1] + 10
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width = height = 8
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blob =[
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trans * (+offset_x, +offset_y+height),
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trans * (+offset_x+width, +offset_y+height),
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trans * (+offset_x+width, +offset_y),
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trans * (+offset_x, +offset_y),
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]
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viewer.draw_polygon(blob, color=obj_color)
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viewer.draw_polygon(path, color=obj.color)
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if "phase" not in obj.__dict__: continue
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a1 = obj.phase
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a2 = obj.phase + 1.2 # radians
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s1 = math.sin(a1)
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s2 = math.sin(a2)
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c1 = math.cos(a1)
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c2 = math.cos(a2)
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if s1>0 and s2>0: continue
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if s1>0: c1 = np.sign(c1)
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if s2>0: c2 = np.sign(c2)
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white_poly = [
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(-WHEEL_W*SIZE, +WHEEL_R*c1*SIZE), (+WHEEL_W*SIZE, +WHEEL_R*c1*SIZE),
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(+WHEEL_W*SIZE, +WHEEL_R*c2*SIZE), (-WHEEL_W*SIZE, +WHEEL_R*c2*SIZE)
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]
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viewer.draw_polygon([trans*v for v in white_poly], color=WHEEL_WHITE)
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def _create_particle(self, point1, point2, grass):
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class Particle:
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pass
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p = Particle()
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p.color = WHEEL_COLOR if not grass else MUD_COLOR
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p.ttl = 1
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p.poly = [(point1[0],point1[1]), (point2[0],point2[1])]
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p.grass = grass
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self.particles.append(p)
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while len(self.particles) > 30:
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self.particles.pop(0)
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return p
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def destroy(self):
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self.world.DestroyBody(self.hull)
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self.hull = None
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for w in self.wheels:
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self.world.DestroyBody(w)
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self.wheels = []
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@@ -1,608 +0,0 @@
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"""This file is based on the car_racing.py in OpenAI's gym.
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|
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Description
|
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We provide some modified CarRacing environments here:
|
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* CarRacingColor-v0
|
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Both the lane and the grass colors are perturbed at the env.reset() with scalar noises.
|
||||
* CarRacingColor3-v0
|
||||
Both the lane and the grass colors are perturbed at the env.reset() with 3d noises.
|
||||
* CarRacingBar-v0
|
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We add vertical bars on the left and right side of the screen.
|
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* CarRacingBlob-v0
|
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A red blob that follows the car at a fixed position in the car's frame.
|
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* CarRacingNoise-v0
|
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We replace the green background with noise.
|
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*. CarRacingVideo-v0
|
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We replace the green background with frames from a video, the user is
|
||||
responsible for creating these frames.
|
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These environments were first used in the paper "Neuroevolution of Self-Interpretable Agent"
|
||||
https://attentionagent.github.io/
|
||||
|
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Author
|
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Yujin Tang (yujintang@google.com)
|
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"""
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|
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import cv2
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import glob
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import os
|
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import sys, math
|
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import numpy as np
|
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|
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import Box2D
|
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from Box2D.b2 import (edgeShape, circleShape, fixtureDef, polygonShape, revoluteJointDef, contactListener)
|
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|
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import gym
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from gym import spaces
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from .car_dynamics import Car
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from gym.utils import colorize, seeding, EzPickle
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import pyglet
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from pyglet import gl
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# Easiest continuous control task to learn from pixels, a top-down racing environment.
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# Discrete control is reasonable in this environment as well, on/off discretization is
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# fine.
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#
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# State consists of STATE_W x STATE_H pixels.
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#
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# Reward is -0.1 every frame and +1000/N for every track tile visited, where N is
|
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# the total number of tiles visited in the track. For example, if you have finished in 732 frames,
|
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# your reward is 1000 - 0.1*732 = 926.8 points.
|
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#
|
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# Game is solved when agent consistently gets 900+ points. Track generated is random every episode.
|
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#
|
||||
# Episode finishes when all tiles are visited. Car also can go outside of PLAYFIELD, that
|
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# is far off the track, then it will get -100 and die.
|
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#
|
||||
# Some indicators shown at the bottom of the window and the state RGB buffer. From
|
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# left to right: true speed, four ABS sensors, steering wheel position and gyroscope.
|
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#
|
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# To play yourself (it's rather fast for humans), type:
|
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#
|
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# python gym/envs/box2d/car_racing.py
|
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#
|
||||
# Remember it's powerful rear-wheel drive car, don't press accelerator and turn at the
|
||||
# same time.
|
||||
#
|
||||
# Created by Oleg Klimov. Licensed on the same terms as the rest of OpenAI Gym.
|
||||
|
||||
STATE_W = 96 # less than Atari 160x192
|
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STATE_H = 96
|
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VIDEO_W = 600
|
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VIDEO_H = 400
|
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WINDOW_W = 1000
|
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WINDOW_H = 800
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|
||||
SCALE = 6.0 # Track scale
|
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TRACK_RAD = 900/SCALE # Track is heavily morphed circle with this radius
|
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PLAYFIELD = 2000/SCALE # Game over boundary
|
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FPS = 50 # Frames per second
|
||||
ZOOM = 2.7 # Camera zoom
|
||||
ZOOM_FOLLOW = True # Set to False for fixed view (don't use zoom)
|
||||
|
||||
|
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TRACK_DETAIL_STEP = 21/SCALE
|
||||
TRACK_TURN_RATE = 0.31
|
||||
TRACK_WIDTH = 40/SCALE
|
||||
BORDER = 8/SCALE
|
||||
BORDER_MIN_COUNT = 4
|
||||
|
||||
ROAD_COLOR = [0.4, 0.4, 0.4]
|
||||
|
||||
class FrictionDetector(contactListener):
|
||||
def __init__(self, env):
|
||||
contactListener.__init__(self)
|
||||
self.env = env
|
||||
def BeginContact(self, contact):
|
||||
self._contact(contact, True)
|
||||
def EndContact(self, contact):
|
||||
self._contact(contact, False)
|
||||
def _contact(self, contact, begin):
|
||||
tile = None
|
||||
obj = None
|
||||
u1 = contact.fixtureA.body.userData
|
||||
u2 = contact.fixtureB.body.userData
|
||||
if u1 and "road_friction" in u1.__dict__:
|
||||
tile = u1
|
||||
obj = u2
|
||||
if u2 and "road_friction" in u2.__dict__:
|
||||
tile = u2
|
||||
obj = u1
|
||||
if not tile:
|
||||
return
|
||||
|
||||
tile.color[0] = self.env.road_color[0]
|
||||
tile.color[1] = self.env.road_color[1]
|
||||
tile.color[2] = self.env.road_color[2]
|
||||
if not obj or "tiles" not in obj.__dict__:
|
||||
return
|
||||
if begin:
|
||||
obj.tiles.add(tile)
|
||||
# print tile.road_friction, "ADD", len(obj.tiles)
|
||||
if not tile.road_visited:
|
||||
tile.road_visited = True
|
||||
self.env.reward += 1000.0/len(self.env.track)
|
||||
self.env.tile_visited_count += 1
|
||||
else:
|
||||
obj.tiles.remove(tile)
|
||||
# print tile.road_friction, "DEL", len(obj.tiles) -- should delete to zero when on grass (this works)
|
||||
|
||||
class CarRacing(gym.Env, EzPickle):
|
||||
metadata = {
|
||||
'render.modes': ['human', 'rgb_array', 'state_pixels'],
|
||||
'video.frames_per_second' : FPS
|
||||
}
|
||||
|
||||
def __init__(self, verbose=1, **kwargs):
|
||||
EzPickle.__init__(self)
|
||||
self.seed()
|
||||
|
||||
self.road_color = ROAD_COLOR[:]
|
||||
self.grass_color = [0.4, 0.8, 0.4, 1]
|
||||
if 'modification' in kwargs:
|
||||
self._modification_type = kwargs['modification']
|
||||
else:
|
||||
self._modification_type = ''
|
||||
|
||||
self.contactListener_keepref = FrictionDetector(self)
|
||||
self.world = Box2D.b2World((0,0), contactListener=self.contactListener_keepref)
|
||||
self.viewer = None
|
||||
self.invisible_state_window = None
|
||||
self.invisible_video_window = None
|
||||
self.road = None
|
||||
self.car = None
|
||||
self.reward = 0.0
|
||||
self.prev_reward = 0.0
|
||||
self.verbose = verbose
|
||||
self.fd_tile = fixtureDef(
|
||||
shape = polygonShape(vertices=
|
||||
[(0, 0),(1, 0),(1, -1),(0, -1)]))
|
||||
|
||||
self.action_space = spaces.Box( np.array([-1,0,0]), np.array([+1,+1,+1]), dtype=np.float32) # steer, gas, brake
|
||||
self.observation_space = spaces.Box(low=0, high=255, shape=(STATE_H, STATE_W, 3), dtype=np.uint8)
|
||||
|
||||
self.step_cnt = 0
|
||||
|
||||
def seed(self, seed=None):
|
||||
self.np_random, seed = seeding.np_random(seed)
|
||||
return [seed]
|
||||
|
||||
def _destroy(self):
|
||||
if not self.road:
|
||||
return
|
||||
for t in self.road:
|
||||
self.world.DestroyBody(t)
|
||||
self.road = []
|
||||
self.car.destroy()
|
||||
|
||||
def _create_track(self):
|
||||
CHECKPOINTS = 12
|
||||
|
||||
# Create checkpoints
|
||||
checkpoints = []
|
||||
for c in range(CHECKPOINTS):
|
||||
alpha = 2*math.pi*c/CHECKPOINTS + self.np_random.uniform(0, 2*math.pi*1/CHECKPOINTS)
|
||||
rad = self.np_random.uniform(TRACK_RAD/3, TRACK_RAD)
|
||||
if c==0:
|
||||
alpha = 0
|
||||
rad = 1.5*TRACK_RAD
|
||||
if c==CHECKPOINTS-1:
|
||||
alpha = 2*math.pi*c/CHECKPOINTS
|
||||
self.start_alpha = 2*math.pi*(-0.5)/CHECKPOINTS
|
||||
rad = 1.5*TRACK_RAD
|
||||
checkpoints.append( (alpha, rad*math.cos(alpha), rad*math.sin(alpha)) )
|
||||
|
||||
# print "\n".join(str(h) for h in checkpoints)
|
||||
# self.road_poly = [ ( # uncomment this to see checkpoints
|
||||
# [ (tx,ty) for a,tx,ty in checkpoints ],
|
||||
# (0.7,0.7,0.9) ) ]
|
||||
self.road = []
|
||||
|
||||
# Go from one checkpoint to another to create track
|
||||
x, y, beta = 1.5*TRACK_RAD, 0, 0
|
||||
dest_i = 0
|
||||
laps = 0
|
||||
track = []
|
||||
no_freeze = 2500
|
||||
visited_other_side = False
|
||||
while True:
|
||||
alpha = math.atan2(y, x)
|
||||
if visited_other_side and alpha > 0:
|
||||
laps += 1
|
||||
visited_other_side = False
|
||||
if alpha < 0:
|
||||
visited_other_side = True
|
||||
alpha += 2*math.pi
|
||||
while True: # Find destination from checkpoints
|
||||
failed = True
|
||||
while True:
|
||||
dest_alpha, dest_x, dest_y = checkpoints[dest_i % len(checkpoints)]
|
||||
if alpha <= dest_alpha:
|
||||
failed = False
|
||||
break
|
||||
dest_i += 1
|
||||
if dest_i % len(checkpoints) == 0:
|
||||
break
|
||||
if not failed:
|
||||
break
|
||||
alpha -= 2*math.pi
|
||||
continue
|
||||
r1x = math.cos(beta)
|
||||
r1y = math.sin(beta)
|
||||
p1x = -r1y
|
||||
p1y = r1x
|
||||
dest_dx = dest_x - x # vector towards destination
|
||||
dest_dy = dest_y - y
|
||||
proj = r1x*dest_dx + r1y*dest_dy # destination vector projected on rad
|
||||
while beta - alpha > 1.5*math.pi:
|
||||
beta -= 2*math.pi
|
||||
while beta - alpha < -1.5*math.pi:
|
||||
beta += 2*math.pi
|
||||
prev_beta = beta
|
||||
proj *= SCALE
|
||||
if proj > 0.3:
|
||||
beta -= min(TRACK_TURN_RATE, abs(0.001*proj))
|
||||
if proj < -0.3:
|
||||
beta += min(TRACK_TURN_RATE, abs(0.001*proj))
|
||||
x += p1x*TRACK_DETAIL_STEP
|
||||
y += p1y*TRACK_DETAIL_STEP
|
||||
track.append( (alpha,prev_beta*0.5 + beta*0.5,x,y) )
|
||||
if laps > 4:
|
||||
break
|
||||
no_freeze -= 1
|
||||
if no_freeze==0:
|
||||
break
|
||||
# print "\n".join([str(t) for t in enumerate(track)])
|
||||
|
||||
# Find closed loop range i1..i2, first loop should be ignored, second is OK
|
||||
i1, i2 = -1, -1
|
||||
i = len(track)
|
||||
while True:
|
||||
i -= 1
|
||||
if i==0:
|
||||
return False # Failed
|
||||
pass_through_start = track[i][0] > self.start_alpha and track[i-1][0] <= self.start_alpha
|
||||
if pass_through_start and i2==-1:
|
||||
i2 = i
|
||||
elif pass_through_start and i1==-1:
|
||||
i1 = i
|
||||
break
|
||||
if self.verbose == 1:
|
||||
print("Track generation: %i..%i -> %i-tiles track" % (i1, i2, i2-i1))
|
||||
assert i1!=-1
|
||||
assert i2!=-1
|
||||
|
||||
track = track[i1:i2-1]
|
||||
|
||||
first_beta = track[0][1]
|
||||
first_perp_x = math.cos(first_beta)
|
||||
first_perp_y = math.sin(first_beta)
|
||||
# Length of perpendicular jump to put together head and tail
|
||||
well_glued_together = np.sqrt(
|
||||
np.square( first_perp_x*(track[0][2] - track[-1][2]) ) +
|
||||
np.square( first_perp_y*(track[0][3] - track[-1][3]) ))
|
||||
if well_glued_together > TRACK_DETAIL_STEP:
|
||||
return False
|
||||
|
||||
# Red-white border on hard turns
|
||||
border = [False]*len(track)
|
||||
for i in range(len(track)):
|
||||
good = True
|
||||
oneside = 0
|
||||
for neg in range(BORDER_MIN_COUNT):
|
||||
beta1 = track[i-neg-0][1]
|
||||
beta2 = track[i-neg-1][1]
|
||||
good &= abs(beta1 - beta2) > TRACK_TURN_RATE*0.2
|
||||
oneside += np.sign(beta1 - beta2)
|
||||
good &= abs(oneside) == BORDER_MIN_COUNT
|
||||
border[i] = good
|
||||
for i in range(len(track)):
|
||||
for neg in range(BORDER_MIN_COUNT):
|
||||
border[i-neg] |= border[i]
|
||||
|
||||
# Create tiles
|
||||
for i in range(len(track)):
|
||||
alpha1, beta1, x1, y1 = track[i]
|
||||
alpha2, beta2, x2, y2 = track[i-1]
|
||||
road1_l = (x1 - TRACK_WIDTH*math.cos(beta1), y1 - TRACK_WIDTH*math.sin(beta1))
|
||||
road1_r = (x1 + TRACK_WIDTH*math.cos(beta1), y1 + TRACK_WIDTH*math.sin(beta1))
|
||||
road2_l = (x2 - TRACK_WIDTH*math.cos(beta2), y2 - TRACK_WIDTH*math.sin(beta2))
|
||||
road2_r = (x2 + TRACK_WIDTH*math.cos(beta2), y2 + TRACK_WIDTH*math.sin(beta2))
|
||||
vertices = [road1_l, road1_r, road2_r, road2_l]
|
||||
self.fd_tile.shape.vertices = vertices
|
||||
t = self.world.CreateStaticBody(fixtures=self.fd_tile)
|
||||
t.userData = t
|
||||
c = 0.01*(i%3)
|
||||
t.color = [self.road_color[0] + c,
|
||||
self.road_color[1] + c,
|
||||
self.road_color[2] + c]
|
||||
t.road_visited = False
|
||||
t.road_friction = 1.0
|
||||
t.fixtures[0].sensor = True
|
||||
self.road_poly.append(( [road1_l, road1_r, road2_r, road2_l], t.color ))
|
||||
|
||||
self.road.append(t)
|
||||
if border[i]:
|
||||
side = np.sign(beta2 - beta1)
|
||||
b1_l = (x1 + side* TRACK_WIDTH *math.cos(beta1), y1 + side* TRACK_WIDTH *math.sin(beta1))
|
||||
b1_r = (x1 + side*(TRACK_WIDTH+BORDER)*math.cos(beta1), y1 + side*(TRACK_WIDTH+BORDER)*math.sin(beta1))
|
||||
b2_l = (x2 + side* TRACK_WIDTH *math.cos(beta2), y2 + side* TRACK_WIDTH *math.sin(beta2))
|
||||
b2_r = (x2 + side*(TRACK_WIDTH+BORDER)*math.cos(beta2), y2 + side*(TRACK_WIDTH+BORDER)*math.sin(beta2))
|
||||
self.road_poly.append(( [b1_l, b1_r, b2_r, b2_l], (1,1,1) if i%2==0 else (1,0,0) ))
|
||||
self.track = track
|
||||
return True
|
||||
|
||||
def reset(self):
|
||||
self._destroy()
|
||||
self.reward = 0.0
|
||||
self.prev_reward = 0.0
|
||||
self.tile_visited_count = 0
|
||||
self.t = 0.0
|
||||
self.road_poly = []
|
||||
self.froad_poly = []
|
||||
self.step_cnt = 0
|
||||
|
||||
# Color modification.
|
||||
self.road_color = np.array([0.4, 0.4, 0.4]) # Original road color.
|
||||
self.grass_color = np.array([0.4, 0.8, 0.4, 1]) # Original grass color.
|
||||
if self._modification_type == 'color':
|
||||
noise1 = np.random.uniform(-0.2, 0.2)
|
||||
noise2 = np.random.uniform(-0.2, 0.2)
|
||||
print('noise1={}'.format(noise1))
|
||||
print('noise2={}'.format(noise2))
|
||||
self.road_color += noise1
|
||||
self.grass_color[:3] += noise2
|
||||
if self._modification_type == 'color3':
|
||||
noise1 = np.random.uniform(-0.2, 0.2, 3)
|
||||
noise2 = np.random.uniform(-0.2, 0.2, 3)
|
||||
print('noise1={}'.format(noise1))
|
||||
print('noise2={}'.format(noise2))
|
||||
self.road_color += noise1
|
||||
self.grass_color[:3] += noise2
|
||||
|
||||
while True:
|
||||
success = self._create_track()
|
||||
if success:
|
||||
break
|
||||
if self.verbose == 1:
|
||||
print("retry to generate track (normal if there are not many of this messages)")
|
||||
add_blob = self._modification_type == 'blob'
|
||||
self.car = Car(self.world, *self.track[0][1:4], add_blob=add_blob)
|
||||
|
||||
return self.step(None)[0]
|
||||
|
||||
def step(self, action):
|
||||
if action is not None:
|
||||
self.car.steer(-action[0])
|
||||
self.car.gas(action[1])
|
||||
self.car.brake(action[2])
|
||||
|
||||
self.car.step(1.0/FPS)
|
||||
self.world.Step(1.0/FPS, 6*30, 2*30)
|
||||
self.t += 1.0/FPS
|
||||
|
||||
self.state = self.render("state_pixels")
|
||||
|
||||
step_reward = 0
|
||||
done = False
|
||||
if action is not None: # First step without action, called from reset()
|
||||
self.reward -= 0.1
|
||||
# We actually don't want to count fuel spent, we want car to be faster.
|
||||
# self.reward -= 10 * self.car.fuel_spent / ENGINE_POWER
|
||||
self.car.fuel_spent = 0.0
|
||||
step_reward = self.reward - self.prev_reward
|
||||
self.prev_reward = self.reward
|
||||
if self.tile_visited_count==len(self.track):
|
||||
done = True
|
||||
x, y = self.car.hull.position
|
||||
if abs(x) > PLAYFIELD or abs(y) > PLAYFIELD:
|
||||
done = True
|
||||
step_reward = -100
|
||||
|
||||
self.step_cnt += 1
|
||||
|
||||
return self.state, step_reward, done, {}
|
||||
|
||||
def render(self, mode='human'):
|
||||
assert mode in ['human', 'state_pixels', 'rgb_array']
|
||||
if self.viewer is None:
|
||||
from gym.envs.classic_control import rendering
|
||||
self.viewer = rendering.Viewer(WINDOW_W, WINDOW_H)
|
||||
self.score_label = pyglet.text.Label('0000', font_size=36,
|
||||
x=20, y=WINDOW_H*2.5/40.00, anchor_x='left', anchor_y='center',
|
||||
color=(255,255,255,255))
|
||||
self.transform = rendering.Transform()
|
||||
|
||||
if "t" not in self.__dict__: return # reset() not called yet
|
||||
|
||||
zoom = 0.1*SCALE*max(1-self.t, 0) + ZOOM*SCALE*min(self.t, 1) # Animate zoom first second
|
||||
zoom_state = ZOOM*SCALE*STATE_W/WINDOW_W
|
||||
zoom_video = ZOOM*SCALE*VIDEO_W/WINDOW_W
|
||||
scroll_x = self.car.hull.position[0]
|
||||
scroll_y = self.car.hull.position[1]
|
||||
angle = -self.car.hull.angle
|
||||
vel = self.car.hull.linearVelocity
|
||||
if np.linalg.norm(vel) > 0.5:
|
||||
angle = math.atan2(vel[0], vel[1])
|
||||
self.transform.set_scale(zoom, zoom)
|
||||
self.transform.set_translation(
|
||||
WINDOW_W/2 - (scroll_x*zoom*math.cos(angle) - scroll_y*zoom*math.sin(angle)),
|
||||
WINDOW_H/4 - (scroll_x*zoom*math.sin(angle) + scroll_y*zoom*math.cos(angle)) )
|
||||
self.transform.set_rotation(angle)
|
||||
|
||||
self.car.draw(self.viewer, mode!="state_pixels")
|
||||
|
||||
arr = None
|
||||
win = self.viewer.window
|
||||
win.switch_to()
|
||||
win.dispatch_events()
|
||||
|
||||
win.clear()
|
||||
t = self.transform
|
||||
if mode=='rgb_array':
|
||||
VP_W = VIDEO_W
|
||||
VP_H = VIDEO_H
|
||||
elif mode == 'state_pixels':
|
||||
VP_W = STATE_W
|
||||
VP_H = STATE_H
|
||||
else:
|
||||
pixel_scale = 1
|
||||
if hasattr(win.context, '_nscontext'):
|
||||
pixel_scale = win.context._nscontext.view().backingScaleFactor() # pylint: disable=protected-access
|
||||
VP_W = int(pixel_scale * WINDOW_W)
|
||||
VP_H = int(pixel_scale * WINDOW_H)
|
||||
|
||||
gl.glViewport(0, 0, VP_W, VP_H)
|
||||
t.enable()
|
||||
self.render_road()
|
||||
for geom in self.viewer.onetime_geoms:
|
||||
geom.render()
|
||||
self.viewer.onetime_geoms = []
|
||||
t.disable()
|
||||
self.render_indicators(WINDOW_W, WINDOW_H)
|
||||
|
||||
if mode == 'human':
|
||||
win.flip()
|
||||
return self.viewer.isopen
|
||||
|
||||
image_data = pyglet.image.get_buffer_manager().get_color_buffer().get_image_data()
|
||||
arr = np.fromstring(image_data.get_data(), dtype=np.uint8, sep='')
|
||||
arr = arr.reshape(VP_H, VP_W, 4)
|
||||
arr = arr[::-1, :, 0:3]
|
||||
|
||||
return arr
|
||||
|
||||
def close(self):
|
||||
if self.viewer is not None:
|
||||
self.viewer.close()
|
||||
self.viewer = None
|
||||
|
||||
def render_road(self):
|
||||
if self._modification_type in ['noise', 'video']:
|
||||
H = W = int(PLAYFIELD * 2)
|
||||
if self._modification_type == 'noise':
|
||||
background = np.random.randint(0, 256, H * W * 3).reshape([H, W, 3])
|
||||
img_path = '/tmp/screen.png'
|
||||
cv2.imwrite(img_path, background)
|
||||
else:
|
||||
video_img_dir = os.environ.get('CARRACING_VIDEO_DIR', '/tmp/car_racing_video')
|
||||
max_steps = len(glob.glob(os.path.join(video_img_dir, '*.png')))
|
||||
img_path = os.path.join(video_img_dir, '{}.png'.format((self.step_cnt + 1) % max_steps))
|
||||
image = pyglet.image.load(img_path)
|
||||
image.anchor_x = image.width // 2
|
||||
image.anchor_y = image.height // 2
|
||||
s = pyglet.sprite.Sprite(image)
|
||||
s.draw()
|
||||
else:
|
||||
gl.glBegin(gl.GL_QUADS)
|
||||
gl.glColor4f(*self.grass_color)
|
||||
gl.glVertex3f(-PLAYFIELD, +PLAYFIELD, 0)
|
||||
gl.glVertex3f(+PLAYFIELD, +PLAYFIELD, 0)
|
||||
gl.glVertex3f(+PLAYFIELD, -PLAYFIELD, 0)
|
||||
gl.glVertex3f(-PLAYFIELD, -PLAYFIELD, 0)
|
||||
gl.glColor4f(0.4, 0.9, 0.4, 1.0)
|
||||
k = PLAYFIELD/20.0
|
||||
for x in range(-20, 20, 2):
|
||||
for y in range(-20, 20, 2):
|
||||
gl.glVertex3f(k*x + k, k*y + 0, 0)
|
||||
gl.glVertex3f(k*x + 0, k*y + 0, 0)
|
||||
gl.glVertex3f(k*x + 0, k*y + k, 0)
|
||||
gl.glVertex3f(k*x + k, k*y + k, 0)
|
||||
gl.glEnd()
|
||||
|
||||
gl.glBegin(gl.GL_QUADS)
|
||||
for poly, color in self.road_poly:
|
||||
gl.glColor4f(color[0], color[1], color[2], 1)
|
||||
for p in poly:
|
||||
gl.glVertex3f(p[0], p[1], 0)
|
||||
gl.glEnd()
|
||||
|
||||
def render_indicators(self, W, H):
|
||||
gl.glBegin(gl.GL_QUADS)
|
||||
s = W/40.0
|
||||
h = H/40.0
|
||||
gl.glColor4f(0,0,0,1)
|
||||
gl.glVertex3f(W, 0, 0)
|
||||
gl.glVertex3f(W, 5*h, 0)
|
||||
gl.glVertex3f(0, 5*h, 0)
|
||||
gl.glVertex3f(0, 0, 0)
|
||||
|
||||
if self._modification_type == 'bar':
|
||||
gl.glVertex3f(W, 5*h, 0)
|
||||
gl.glVertex3f(W, H, 0)
|
||||
gl.glVertex3f(W-3*s, H, 0)
|
||||
gl.glVertex3f(W-3*s, 5*h, 0)
|
||||
|
||||
gl.glVertex3f(3*s, 5*h, 0)
|
||||
gl.glVertex3f(3*s, H, 0)
|
||||
gl.glVertex3f(0, H, 0)
|
||||
gl.glVertex3f(0, 5*h, 0)
|
||||
|
||||
def vertical_ind(place, val, color):
|
||||
gl.glColor4f(color[0], color[1], color[2], 1)
|
||||
gl.glVertex3f((place+0)*s, h + h*val, 0)
|
||||
gl.glVertex3f((place+1)*s, h + h*val, 0)
|
||||
gl.glVertex3f((place+1)*s, h, 0)
|
||||
gl.glVertex3f((place+0)*s, h, 0)
|
||||
def horiz_ind(place, val, color):
|
||||
gl.glColor4f(color[0], color[1], color[2], 1)
|
||||
gl.glVertex3f((place+0)*s, 4*h , 0)
|
||||
gl.glVertex3f((place+val)*s, 4*h, 0)
|
||||
gl.glVertex3f((place+val)*s, 2*h, 0)
|
||||
gl.glVertex3f((place+0)*s, 2*h, 0)
|
||||
true_speed = np.sqrt(np.square(self.car.hull.linearVelocity[0]) + np.square(self.car.hull.linearVelocity[1]))
|
||||
vertical_ind(5, 0.02*true_speed, (1,1,1))
|
||||
vertical_ind(7, 0.01*self.car.wheels[0].omega, (0.0,0,1)) # ABS sensors
|
||||
vertical_ind(8, 0.01*self.car.wheels[1].omega, (0.0,0,1))
|
||||
vertical_ind(9, 0.01*self.car.wheels[2].omega, (0.2,0,1))
|
||||
vertical_ind(10,0.01*self.car.wheels[3].omega, (0.2,0,1))
|
||||
horiz_ind(20, -10.0*self.car.wheels[0].joint.angle, (0,1,0))
|
||||
horiz_ind(30, -0.8*self.car.hull.angularVelocity, (1,0,0))
|
||||
gl.glEnd()
|
||||
self.score_label.text = "%04i" % self.reward
|
||||
self.score_label.draw()
|
||||
|
||||
|
||||
if __name__=="__main__":
|
||||
from pyglet.window import key
|
||||
a = np.array( [0.0, 0.0, 0.0] )
|
||||
def key_press(k, mod):
|
||||
global restart
|
||||
if k==0xff0d: restart = True
|
||||
if k==key.LEFT: a[0] = -1.0
|
||||
if k==key.RIGHT: a[0] = +1.0
|
||||
if k==key.UP: a[1] = +1.0
|
||||
if k==key.DOWN: a[2] = +0.8 # set 1.0 for wheels to block to zero rotation
|
||||
def key_release(k, mod):
|
||||
if k==key.LEFT and a[0]==-1.0: a[0] = 0
|
||||
if k==key.RIGHT and a[0]==+1.0: a[0] = 0
|
||||
if k==key.UP: a[1] = 0
|
||||
if k==key.DOWN: a[2] = 0
|
||||
env = CarRacing()
|
||||
env.render()
|
||||
env.viewer.window.on_key_press = key_press
|
||||
env.viewer.window.on_key_release = key_release
|
||||
record_video = False
|
||||
if record_video:
|
||||
from gym.wrappers.monitor import Monitor
|
||||
env = Monitor(env, '/tmp/video-test', force=True)
|
||||
isopen = True
|
||||
while isopen:
|
||||
env.reset()
|
||||
total_reward = 0.0
|
||||
steps = 0
|
||||
restart = False
|
||||
while True:
|
||||
s, r, done, info = env.step(a)
|
||||
total_reward += r
|
||||
if steps % 200 == 0 or done:
|
||||
print("\naction " + str(["{:+0.2f}".format(x) for x in a]))
|
||||
print("step {} total_reward {:+0.2f}".format(steps, total_reward))
|
||||
#import matplotlib.pyplot as plt
|
||||
#plt.imshow(s)
|
||||
#plt.savefig("test.jpeg")
|
||||
steps += 1
|
||||
isopen = env.render()
|
||||
if done or restart or isopen == False:
|
||||
break
|
||||
env.close()
|
||||
@@ -1 +0,0 @@
|
||||
VERSION='0.0.1'
|
||||
@@ -1,24 +0,0 @@
|
||||
import gym
|
||||
|
||||
env_dict = gym.envs.registration.registry.env_specs.copy()
|
||||
|
||||
|
||||
for env in env_dict:
|
||||
if 'CarRacingColor3-v0' in env:
|
||||
print("Remove {} from registry".format(env))
|
||||
del gym.envs.registration.registry.env_specs[env]
|
||||
#from environments.domain_adaption.natural_rl_environment import natural_env
|
||||
import environments.domain_adaption.car_racing_variants
|
||||
|
||||
|
||||
env = gym.make('CarRacingColor3-v0')
|
||||
env.seed(666)
|
||||
|
||||
while True:
|
||||
ob = env.reset()
|
||||
done = False
|
||||
step = 0
|
||||
while not done and 0 <= step <= 500:
|
||||
ob, reward, done, _ = env.step(env.action_space.sample())
|
||||
step += 1
|
||||
env.render()
|
||||
@@ -0,0 +1,3 @@
|
||||
from environments.policy_adaption.natural_rl_environment import matting
|
||||
from environments.policy_adaption.natural_rl_environment import imgsource
|
||||
from environments.policy_adaption.natural_rl_environment import natural_env
|
||||
@@ -11,8 +11,8 @@ import glob
|
||||
import gym
|
||||
from gym.utils import play
|
||||
|
||||
from matting import BackgroundMattingWithColor
|
||||
from imgsource import (
|
||||
from .matting import BackgroundMattingWithColor
|
||||
from .imgsource import (
|
||||
RandomImageSource,
|
||||
RandomColorSource,
|
||||
NoiseSource,
|
||||
@@ -59,6 +59,26 @@ class ReplaceBackgroundEnv(gym.ObservationWrapper):
|
||||
return env.viewer.isopen
|
||||
|
||||
|
||||
def make(name='Pong-v0', imgsource='color', files=None):
|
||||
env = gym.make(name) # gravitar, breakout, MsPacman, Space Invaders
|
||||
shape2d = env.observation_space.shape[:2]
|
||||
color = (0, 0, 0) if 'Pong' not in name else (144, 72, 17)
|
||||
if imgsource == 'video':
|
||||
imgsource = RandomVideoSource(shape2d, ['/Users/romue/PycharmProjects/EDYS/environments/policy_adaption/natural_rl_environment/videos/stars.mp4'])
|
||||
elif imgsource == "color":
|
||||
imgsource = RandomColorSource(shape2d)
|
||||
elif imgsource == "noise":
|
||||
imgsource = NoiseSource(shape2d)
|
||||
if args.imgsource == "images":
|
||||
imgsource = RandomImageSource(shape2d, files)
|
||||
else:
|
||||
raise NotImplementedError(f'{imgsource} is not supported, use one of {{video, color, noise}}')
|
||||
wrapped_env = ReplaceBackgroundEnv(
|
||||
env, BackgroundMattingWithColor(color), imgsource
|
||||
)
|
||||
return wrapped_env
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--env", help="The gym environment to base on")
|
||||
Binary file not shown.
Binary file not shown.
28
environments/policy_adaption/test.py
Normal file
28
environments/policy_adaption/test.py
Normal file
@@ -0,0 +1,28 @@
|
||||
import gym
|
||||
import glob
|
||||
from environments.policy_adaption.natural_rl_environment.imgsource import *
|
||||
from environments.policy_adaption.natural_rl_environment.natural_env import *
|
||||
|
||||
if __name__ == "__main__":
|
||||
imgsource = 'video'
|
||||
env = gym.make('SpaceInvaders-v0') # gravitar, breakout, MsPacman, Space Invaders
|
||||
shape2d = env.observation_space.shape[:2]
|
||||
print(shape2d)
|
||||
|
||||
if imgsource == 'video':
|
||||
imgsource = RandomVideoSource(shape2d, ['/Users/romue/PycharmProjects/EDYS/environments/policy_adaption/natural_rl_environment/videos/stars.mp4'])
|
||||
elif imgsource == "color":
|
||||
imgsource = RandomColorSource(shape2d)
|
||||
elif imgsource == "noise":
|
||||
imgsource = NoiseSource(shape2d)
|
||||
wrapped_env = ReplaceBackgroundEnv(
|
||||
#env, BackgroundMattingWithColor((144, 72, 17)), imgsource
|
||||
env, BackgroundMattingWithColor((0, 0, 0)), imgsource
|
||||
)
|
||||
env = wrapped_env
|
||||
|
||||
|
||||
env.reset()
|
||||
|
||||
state, *_ = env.step(env.action_space.sample())
|
||||
play.play(wrapped_env, zoom=4)
|
||||
Reference in New Issue
Block a user