"""Dronescapes representations -- adds various loading/writing/image showing capabilities to dronescapes tasks""" from pathlib import Path import numpy as np import torch as tr import flow_vis from overrides import overrides from matplotlib.cm import hot # pylint: disable=no-name-in-module from .multitask_dataset import NpzRepresentation class DepthRepresentation(NpzRepresentation): """DepthRepresentation. Implements depth task-specific stuff, like hotmap.""" def __init__(self, *args, min_depth: float, max_depth: float, **kwargs): super().__init__(*args, **kwargs) self.min_depth = min_depth self.max_depth = max_depth @overrides def plot_fn(self, x: tr.Tensor) -> np.ndarray: x = x.detach().cpu().numpy() x = np.clip(x, self.min_depth, self.max_depth) x = np.nan_to_num((x - x.min()) / (x.max() - x.min()), 0) y = hot(x.squeeze())[..., 0:3] y = np.uint8(y * 255) return y class OpticalFlowRepresentation(NpzRepresentation): """OpticalFlowRepresentation. Implements depth task-specific stuff, like using flow_vis.""" @overrides def plot_fn(self, x: tr.Tensor) -> np.ndarray: return flow_vis.flow_to_color(x.squeeze().nan_to_num(0).detach().cpu().numpy()) class SemanticRepresentation(NpzRepresentation): """SemanticRepresentation. Implements depth task-specific stuff, like using flow_vis.""" def __init__(self, *args, classes: int | list[str], color_map: list[tuple[int, int, int]], **kwargs): super().__init__(*args, **kwargs) self.classes = list(range(classes)) if isinstance(classes, int) else classes self.n_classes = len(self.classes) self.color_map = color_map assert len(color_map) == self.n_classes, (color_map, self.n_classes) @overrides def load_from_disk(self, path: Path) -> tr.Tensor: res = super().load_from_disk(path) assert len(res.shape) == 2, f"Only argmaxed data supported, got: {res.shape}" return res @overrides def plot_fn(self, x: tr.Tensor) -> np.ndarray: x = x.squeeze().nan_to_num(0).detach().cpu().numpy() new_images = np.zeros((*x.shape, 3), dtype=np.uint8) for i in range(self.n_classes): new_images[x == i] = self.color_map[i] return new_images