具体地,你可能需要在初始化环境时设置一个`render_mode`参数,然后直接使用`env.render()`,而不再需要`mode`参数。 这是一个例子,假设`env_name`是你希望使用的环境名称: env = gym.make(env_name, render_mode='rgb_array') env.render() 注意,具体的API变更可能因环境而异,所以建议查阅针对你所使用环境...
When I use two different size ofenv.render(mode='rgb_array')andenv.render(mode='depth_array', such as (width, height) = (64, 64) in depth_array and (256, 256) in rgb_array, output np.array is too strange. However, When I use both render as rgb_array, I can get expected ima...
I need to the following on macos Big Sur 11.4, python3.9.5, gym==0.18.3 to get frame as an array which is not returned by default for bipedal walker env. import gym env = gym.make('BipedalWalker-v3') state = env.render(mode='rgb_array') ...
env= gym.make("CartPole-v1") num=0foriinrange(3000): state=env.reset()whileTrue: num+=1screen= env.render(mode='rgb_array') img=Image.fromarray(screen) filename='./img/screen_image'+str(num)+'.png'print('save img at'+filename) img.save(filename) action=env.action_space.sample...
python ./isaacgymenvs/train.py task=Ant 注意上述 “task=Ant”之间没有空格奥 过了好一会才到第7轮,默认情况下运行train函数都会显示一个预览窗口也就是渲染界面,因为开着渲染训练会很慢,所以官方给出了禁用渲染的方式,即:鼠标点击渲染界面,摁下键盘上的“v”键,这样训练就会运行的非常快,如果你想看看训练...
)if__name__ =='__main__':importgymnasiumasgym# env = MOHalfCheetahEnv(render_mode="human")# env = MOHalfCheetahEnv()# env = mo_gym.make('mo-halfcheetah-v4') # 无done 1000次# env = gym.make("HalfCheetah-v4") # 无done 1000次env = gym.make("wx-half-v1", disable_env_che...
return self.env.render(mode, **kwargs) File "F:\miniconda3\envs\Gym\lib\site-packages\gym\envs\atari\environment.py", line 264, in render from gym.envs.classic_control import rendering ImportError: cannot import name 'rendering' from 'gym.envs.classic_control' (F:\miniconda3\envs\Gym...
env=gym.make('Breakout-v0')env.reset()for_inrange(100):plt.imshow(env.render(mode='rgb_array'))display.display(plt.gcf())display.clear_output(wait=True)action=env.action_space.sample()env.step(action) ② 不断修改RGB data以实现多帧图像渲染(仅调用1次imshow,速度快) ...
创建的Panda环境命名为gym-panda,文件名为panda_env.py。按照Gym的规则,文件框架应该这样: importgymfrom gymimporterror,spaces,utilsfrom gym.utilsimportseedingimportosimportpybullet as pimportpybullet_dataimportmathimportnumpy as npimportrandomclassPandaEnv(gym.Env):metadata= {...
envs = gym.vector.make('MyGymExamples:MyGymExamples/CliffWalkingEnv-v0', num_envs=3, disable_env_checker=False, render_mode='rgb_array', # 从这开始为环境的自身参数 map_size=(4,12), pix_square_size=30) observations, infos = envs.reset() ...