sys.path.append(os.path.join(os.getcwd())) # HACK add the root folder
from lib.config import CONF
from lib.projection import ProjectionHelper
SCANNET_LIST = CONF.SCANNETV2_LIST
SCANNET_DATA = CONF.PATH.SCANNET_DATA
SCANNET_FRAME_ROOT = CONF.SCANNET_FRAMES
SCANNET_FRAME_PATH = os.path.join(SCANNET_FRAME_ROOT, "{}") # name of the file
ENET_FEATURE_PATH = CONF.ENET_FEATURES_PATH
ENET_FEATURE_DATABASE = CONF.MULTIVIEW
# projection
INTRINSICS = [[37.01983, 0, 20, 0],[0, 38.52470, 15.5, 0],[0, 0, 1, 0],[0, 0, 0, 1]]
PROJECTOR = ProjectionHelper(INTRINSICS, 0.1, 4.0, [41, 32], 0.05)
def get_scene_list():
with open(SCANNET_LIST, 'r') as f:
return sorted(list(set(f.read().splitlines())))
def to_tensor(arr):
return torch.Tensor(arr).cuda()
def resize_crop_image(image, new_image_dims):
image_dims = [image.shape[1], image.shape[0]]
if image_dims == new_image_dims:
return image
resize_width = int(math.floor(new_image_dims[1] * float(image_dims[0]) / float(image_dims[1])))
image = transforms.Resize([new_image_dims[1], resize_width], interpolation=Image.NEAREST)(Image.fromarray(image))
image = transforms.CenterCrop([new_image_dims[1], new_image_dims[0]])(image)
from lib.projection import ProjectionHelper
# data path
SCANNET_LIST = CONF.SCANNETV2_LIST
SCANNET_DATA = CONF.PREP_SCANS
PROJECTION_ROOT = CONF.PROJECTION
PROJECTION_PATH = os.path.join(PROJECTION_ROOT, "{}_{}.npy") # scene_id, mode
# scannet data
# NOTE: read only!
SCANNET_FRAME_ROOT = CONF.SCANNET_FRAMES
SCANNET_FRAME_PATH = os.path.join(SCANNET_FRAME_ROOT, "{}") # name of the file
# projection
INTRINSICS = [[37.01983, 0, 20, 0],[0, 38.52470, 15.5, 0],[0, 0, 1, 0],[0, 0, 0, 1]]
PROJECTOR = ProjectionHelper(INTRINSICS, 0.1, 4.0, [41, 32], 0.05)
def get_scene_list():
with open(SCANNET_LIST, 'r') as f:
scene_list = sorted(list(set(f.read().splitlines())))
return scene_list
def load_scene(scene_list):
scene_data = {}
for scene_id in scene_list:
scene_data[scene_id] = np.load(os.path.join(SCANNET_DATA, scene_id)+".npy")[:, :3]
return scene_data
def resize_crop_image(image, new_image_dims):