#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "Christian Heider Nielsen"
__doc__ = r"""
Created on 29/03/2020
"""
from typing import Tuple
__all__ = ["CamVid"]
from draugr.torch_utilities import SupervisedDataset
[docs]class CamVid(SupervisedDataset):
"""description"""
def __getitem__(self, index):
raise NotImplementedError
def __len__(self):
raise NotImplementedError
@property
def predictor_shape(self) -> Tuple[int, ...]:
"""description"""
return self.image_size
@property
def response_shape(self) -> Tuple[int, ...]:
"""description"""
return (self.response_channels,)
predictor_channels = 3 # RGB input
colors_dict = {
(64, 128, 64): "Animal",
(192, 0, 128): "Archway",
(0, 128, 192): "Bicyclist",
(0, 128, 64): "Bridge",
(128, 0, 0): "Building",
(64, 0, 128): "Car",
(64, 0, 192): "CartLuggagePram",
(192, 128, 64): "Child",
(192, 192, 128): "Column_Pole",
(64, 64, 128): "Fence",
(128, 0, 192): "LaneMkgsDriv",
(192, 0, 64): "LaneMkgsNonDriv",
(128, 128, 64): "Misc_Text",
(192, 0, 192): "MotorcycleScooter",
(128, 64, 64): "OtherMoving",
(64, 192, 128): "ParkingBlock",
(64, 64, 0): "Pedestrian",
(128, 64, 128): "Road",
(128, 128, 192): "RoadShoulder",
(0, 0, 192): "Sidewalk",
(192, 128, 128): "SignSymbol",
(128, 128, 128): "Sky",
(64, 128, 192): "SUVPickupTruck",
(0, 0, 64): "TrafficCone",
(0, 64, 64): "TrafficLight",
(192, 64, 128): "Train",
(128, 128, 0): "Tree",
(192, 128, 192): "Truck_Bus",
(64, 0, 64): "Tunnel",
(192, 192, 0): "VegetationMisc",
(0, 0, 0): "Void",
(64, 192, 0): "Wall",
}
response_channels = len(colors_dict.keys())
image_size = (256, 256)
image_size_T = image_size[::-1]
