def test_complicated_object_vec_to_scene(self):
steps = 50
_, _, images, objects = simulator.magic_ponies(
self._task_complicated_object_test,
self._ball_user_input_big,
steps=steps,
stride=1,
need_images=True,
need_featurized_objects=True)
objects = phyre.simulation.Simulation(
featurized_objects=objects).featurized_objects.features
for i in range(len(images)):
image = images[i]
original_object_vec = objects[i]
object_vec = original_object_vec
for j in range(5):
# Test no loss of information in conversion
self.assertTrue(
np.allclose(original_object_vec,
simulator.scene_to_featurized_objects(
phyre.objects_util.
featurized_objects_vector_to_scene(
object_vec)).features,
atol=1e-4))
object_vec = simulator.scene_to_featurized_objects(
phyre.objects_util.featurized_objects_vector_to_scene(
object_vec)).features[0]
self.assertTrue((image == simulator.scene_to_raster(
phyre.objects_util.featurized_objects_vector_to_scene(
object_vec))).all())
def test_render_with_input(self):
scene = simulator.simulate_task_with_input(self._task,
self._box_user_input,
steps=1).sceneList[0]
array = simulator.scene_to_raster(scene)
self.assertEqual(len(array.shape), 2)
self.assertEqual(array.shape[0], self._task.scene.height)
self.assertEqual(array.shape[1], self._task.scene.width)
def test_add_input_and_ponies(self):
steps = 10
task_simulation = simulator.simulate_task_with_input(
self._task, self._ball_user_input, steps=steps, stride=1)
is_solved, had_occlusions, images, scenes = simulator.magic_ponies(
self._task,
self._ball_user_input,
steps=steps,
stride=1,
need_images=True,
need_featurized_objects=True)
self.assertEqual(is_solved, task_simulation.isSolution)
self.assertEqual(len(images), steps)
self.assertEqual(len(task_simulation.sceneList), steps)
self.assertEqual(
had_occlusions, task_simulation.sceneList[0].user_input_status ==
scene_if.UserInputStatus.HAD_OCCLUSIONS)
# Check images match target scenes
self.assertFalse(
np.array_equal(
images[0],
simulator.scene_to_raster(task_simulation.sceneList[-1])))
self.assertTrue((images[-1] == simulator.scene_to_raster(
task_simulation.sceneList[-1])).all())
# Test just images works
_, _, only_images, _ = simulator.magic_ponies(
self._task,
self._ball_user_input,
steps=steps,
stride=1,
need_images=True,
need_featurized_objects=False)
self.assertTrue(np.array_equal(images, only_images))
# Test just scenes works
_, _, _, only_scenes = simulator.magic_ponies(
self._task,
self._ball_user_input,
steps=steps,
stride=1,
need_images=False,
need_featurized_objects=True)
self.assertTrue(np.array_equal(scenes, only_scenes))
def test_add_input_and_ponies(self):
raise unittest.SkipTest
steps = 10
task_simulation = simulator.simulate_task_with_input(
self._task, self._box_user_input, steps=steps, stride=1)
is_solved, had_occlusions, images = simulator.magic_ponies(
self._task, self._box_compressed_user_input, steps=steps, stride=1)
self.assertEqual(is_solved, task_simulation.isSolution)
self.assertEqual(len(images), steps)
self.assertEqual(len(task_simulation.sceneList), steps)
self.assertEqual(
had_occlusions, task_simulation.sceneList[0].user_input_status ==
scene_if.UserInputStatus.HAD_OCCLUSIONS)
self.assertFalse((images[0] == simulator.scene_to_raster(
task_simulation.sceneList[-1])).all())
self.assertTrue((images[-1] == simulator.scene_to_raster(
task_simulation.sceneList[-1])).all())
def test_object_vec_to_scene(self):
steps = 50
_, _, images, objects = simulator.magic_ponies(
self._task_object_test,
self._ball_user_input_small,
steps=steps,
stride=1,
need_images=True,
need_featurized_objects=True)
objects = phyre.simulation.Simulation(
featurized_objects=objects).featurized_objects.features
for i in range(len(images)):
image = images[i]
object_vec = objects[i]
self.assertTrue(
np.allclose(
object_vec,
simulator.scene_to_featurized_objects(
phyre.objects_util.featurized_objects_vector_to_scene(
object_vec)).features,
atol=1e-4))
self.assertTrue((image == simulator.scene_to_raster(
phyre.objects_util.featurized_objects_vector_to_scene(
object_vec))).all())
def get_scene_as_base64_image(scene, resize=None):
arr = vis.observations_to_uint8_rgb(simulator.scene_to_raster(scene))
return get_image_as_base64(arr, resize=resize)
def render(self, scene):
assert self._config['mode'] != DEMO_MODE
pixels = simulator.scene_to_raster(scene).flatten().tolist()
return scene_if.Image(width=scene.width,
height=scene.height,
values=pixels)
def test_render(self):
array = simulator.scene_to_raster(self._task.scene)
self.assertEqual(len(array.shape), 2)
self.assertEqual(array.shape[0], self._task.scene.height)
self.assertEqual(array.shape[1], self._task.scene.width)
# plt.imshow(phyre.vis.observations_to_float_rgb(initial_scene))
# plt.show()
from phyre import simulator as sim
actions = simulator.build_discrete_action_space(max_actions=1000)
action = actions[20] # Successful action for 3:28
action, is_valid = simulator.get_user_input(
action) # Phyre representation of the action
# If you want to brute force every solution until you get a success
# from phyre import SimulationStatus
# for action in actions:
# status = simulator.simulate_single(task_index, action, need_images=False)
# if status == SimulationStatus.SOLVED:
# Simulates task with the action, returning Thrift representations of intermediate images every frame
# Increase stride to decrease simulation time
result = sim.simulate_task_with_input(simulator.get_task(0), action, stride=1)
# Convert Thrift scene to array of pixels
images = [sim.scene_to_raster(scene) for scene in result.sceneList]
ims = [phyre.vis.observations_to_float_rgb(image) for image in images]
# Displays the simulation
delay = 0.0005 # Delay between frames
img = plt.imshow(ims[0])
for image in ims[1:]:
img.set_data(image)
plt.pause(delay)
plt.draw()