How to use the airsim.client.ImageType.Scene function in airsim
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nesl / UnrealAirSimDRL / Deep_Reinforcement_Learning / Library / ClientAirSimEnvironments / AutoCarUnrealEnvironment.py View on Github 
def get_new_images(self):
# Construct the Images State Vector
# Order is Front Center, Front Right, Front Left
tic = time.time()
self.client.simPause(True)
if (self.image_mask_FC_FR_FL[0] and self.image_mask_FC_FR_FL[1] and self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False), # Front Center
client.ImageRequest("1", client.ImageType.Scene, False, False), # Front Right
client.ImageRequest("2", client.ImageType.Scene, False, False)]) # Front Left
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
#plt.imshow(img_rgb_FR)
#plt.show()
#time.sleep(2)
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]img_rgb_FR = img_rgba_FR[:,:,0:3]
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]
# Can either use the RGBA images or the RGB Images
self.images_rgba = np.dstack((img_rgba_FC,img_rgba_FR,img_rgba_FL))
self.images_rgb = np.dstack((img_rgb_FC,img_rgb_FR,img_rgb_FL))
self.time_to_grab_images = time.time() - tic
print("Time to Grab Images: ", self.time_to_grab_images)
# We Just want front
elif (self.image_mask_FC_FR_FL[0] and not self.image_mask_FC_FR_FL[1] and not self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False)])
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
self.images_rgba = img_rgba_FC
self.images_rgb = img_rgb_FC
self.time_to_grab_images = time.time() - tic
print("Time to Grab Images: ", self.time_to_grab_images)
else:
print("A screw up in set new images")img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]
# Can either use the RGBA images or the RGB Images
self.images_rgba = np.dstack((img_rgba_FC,img_rgba_FR,img_rgba_FL))
self.images_rgb = np.dstack((img_rgb_FC,img_rgb_FR,img_rgb_FL))
self.time_to_grab_images = time.time() - tic
# We Just want front view
elif (self.image_mask_FC_FR_FL[0] and not self.image_mask_FC_FR_FL[1] and not self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False)]) # Front Center
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
self.images_rgba = img_rgba_FC
self.images_rgb = img_rgb_FC
self.time_to_grab_images = time.time() - tic
self.client.simPause(False)pos[2] - self.initial_position[vn][2],
vel[0] - self.initial_velocity[vn][0],
vel[1] - self.initial_velocity[vn][1],
vel[2] - self.initial_velocity[vn][2],
acc[0], acc[1], acc[2],
angVel[0], angVel[1], angVel[2],
angAcc[0], angAcc[1], angAcc[2]])
# Posx, Posy, PosZ, Vx, Vy, Vz, Ax, Ay, Az, AngVelx, AngVely, AngVelz, AngAccx, AngAccy, AngAccz
# Construct the Images State Vector
# Order is Front Center, Front Right, Front Left
for vn in self.vehicle_names:
if (self.image_mask_FC_FR_FL[0] and self.image_mask_FC_FR_FL[1] and self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False), # Front Center
client.ImageRequest("1", client.ImageType.Scene, False, False), # Front Right
client.ImageRequest("2", client.ImageType.Scene, False, False)], vehicle_name = vn) # Front Left
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
#plt.imshow(img_rgb_FR)
#plt.show()
#time.sleep(2)
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]def get_new_images(self):
# Construct the Images State Vector
# Order is Front Center, Front Right, Front Left
tic = time.time()
self.client.simPause(True)
if (self.image_mask_FC_FR_FL[0] and self.image_mask_FC_FR_FL[1] and self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False), # Front Center
client.ImageRequest("1", client.ImageType.Scene, False, False), # Front Right
client.ImageRequest("2", client.ImageType.Scene, False, False)]) # Front Left
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]
# Can either use the RGBA images or the RGB Images
self.images_rgba = np.dstack((img_rgba_FC,img_rgba_FR,img_rgba_FL))
self.images_rgb = np.dstack((img_rgb_FC,img_rgb_FR,img_rgb_FL))img_rgb_FR = img_rgba_FR[:,:,0:3]
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]
# Can either use the RGBA images or the RGB Images
self.images_rgba[vehicleName] = np.dstack((img_rgba_FC,img_rgba_FR,img_rgba_FL))
self.images_rgb[vehicleName] = np.dstack((img_rgb_FC,img_rgb_FR,img_rgb_FL))
print('Images Collected!')
print("Time to Grab Images: ", time.time() - tic)
# We Just want front
elif (self.image_mask_FC_FR_FL[0] and not self.image_mask_FC_FR_FL[1] and not self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False)], vehicle_name = vehicleName)
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
self.images_rgba[vehicleName] = img_rgba_FC
self.images_rgb[vehicleName] = img_rgb_FC
print('Images Collected!')
print("Time to Grab Images: ", time.time() - tic)
else:
print("A screw up in set new images")pos[1] - self.initial_position[vn][1],
pos[2] - self.initial_position[vn][2],
vel[0] - self.initial_velocity[vn][0],
vel[1] - self.initial_velocity[vn][1],
vel[2] - self.initial_velocity[vn][2],
acc[0], acc[1], acc[2],
angVel[0], angVel[1], angVel[2],
angAcc[0], angAcc[1], angAcc[2]])
# Posx, Posy, PosZ, Vx, Vy, Vz, Ax, Ay, Az, AngVelx, AngVely, AngVelz, AngAccx, AngAccy, AngAccz
# Construct the Images State Vector
# Order is Front Center, Front Right, Front Left
for vn in self.vehicle_names:
if (self.image_mask_FC_FR_FL[0] and self.image_mask_FC_FR_FL[1] and self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False), # Front Center
client.ImageRequest("1", client.ImageType.Scene, False, False), # Front Right
client.ImageRequest("2", client.ImageType.Scene, False, False)], vehicle_name = vn) # Front Left
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
#plt.imshow(img_rgb_FR)
#plt.show()
#time.sleep(2)
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)def get_new_images(self, vehicleName):
# Wait to grad images
tic = time.time()
print("Collecting Images from AirSim")
if (self.image_mask_FC_FR_FL[0] and self.image_mask_FC_FR_FL[1] and self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([
client.ImageRequest("0", client.ImageType.Scene, False, False), # Front Center
client.ImageRequest("1", client.ImageType.Scene, False, False), # Front Right
client.ImageRequest("2", client.ImageType.Scene, False, False)], vehicle_name = vehicleName) # Front Left
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]
# Can either use the RGBA images or the RGB Images
self.images_rgba[vehicleName] = np.dstack((img_rgba_FC,img_rgba_FR,img_rgba_FL))
self.images_rgb[vehicleName] = np.dstack((img_rgb_FC,img_rgb_FR,img_rgb_FL))def get_new_images(self):
# Construct the Images State Vector
# Order is Front Center, Front Right, Front Left
tic = time.time()
self.client.simPause(True)
if (self.image_mask_FC_FR_FL[0] and self.image_mask_FC_FR_FL[1] and self.image_mask_FC_FR_FL[2]):
images = self.client.simGetImages([client.ImageRequest("0", client.ImageType.Scene, False, False), # Front Center
client.ImageRequest("1", client.ImageType.Scene, False, False), # Front Right
client.ImageRequest("2", client.ImageType.Scene, False, False)]) # Front Left
img1d_FC = np.fromstring(images[0].image_data_uint8, dtype=np.uint8)
img_rgba_FC = np.array(img1d_FC.reshape(images[0].height, images[0].width, 4), dtype = np.uint8)
img_rgb_FC = img_rgba_FC[:,:,0:3]
img1d_FR = np.fromstring(images[1].image_data_uint8, dtype=np.uint8)
img_rgba_FR = np.array(img1d_FR.reshape(images[1].height, images[1].width, 4), dtype = np.uint8)
img_rgb_FR = img_rgba_FR[:,:,0:3]
img1d_FL = np.fromstring(images[2].image_data_uint8, dtype=np.uint8)
img_rgba_FL = np.array(img1d_FL.reshape(images[2].height, images[2].width, 4), dtype = np.uint8)
img_rgb_FL = img_rgba_FL[:,:,0:3]
# Can either use the RGBA images or the RGB Images
self.images_rgba = np.dstack((img_rgba_FC,img_rgba_FR,img_rgba_FL))
self.images_rgb = np.dstack((img_rgb_FC,img_rgb_FR,img_rgb_FL))
self.time_to_grab_images = time.time() - ticairsim
Open source simulator based on Unreal Engine for autonomous vehicles from Microsoft AI & Research
Package Health Score
66 / 100Popular airsim functions
- airsim.CarClient
- airsim.client
- airsim.client.CarClient
- airsim.client.CarControls
- airsim.client.ImageRequest
- airsim.client.ImageType
- airsim.client.ImageType.Scene
- airsim.ImageRequest
- airsim.ImageType
- airsim.ImageType.Scene
- airsim.MultirotorClient
- airsim.Pose
- airsim.to_quaternion
- airsim.types.Pose
- airsim.types.Vector3r
- airsim.Vector3r
- airsim.VehicleClient
- airsim.wait_key
- airsim.write_file
- airsim.YawMode