"""Anomaly Visualization.""" # Copyright (C) 2020 Intel Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions # and limitations under the License. from pathlib import Path from typing import Optional, Tuple import cv2 import matplotlib.pyplot as plt import numpy as np class Visualizer: """Anomaly Visualization. The visualizer object is responsible for collating all the images passed to it into a single image. This can then either be logged by accessing the `figure` attribute or can be saved directly by calling `save()` method. Example: >>> visualizer = Visualizer(num_rows=1, num_cols=5, figure_size=(12, 3)) >>> visualizer.add_image(image=image, title="Image") >>> visualizer.close() Args: num_rows (int): Number of rows of images in the figure. num_cols (int): Number of columns/images in each row. figure_size (Tuple[int, int]): Size of output figure """ def __init__(self, num_rows: int, num_cols: int, figure_size: Tuple[int, int]): self.figure_index: int = 0 self.figure, self.axis = plt.subplots(num_rows, num_cols, figsize=figure_size) self.figure.subplots_adjust(right=0.9) for axis in self.axis: axis.axes.xaxis.set_visible(False) axis.axes.yaxis.set_visible(False) def add_image(self, image: np.ndarray, title: str, color_map: Optional[str] = None, index: Optional[int] = None): """Add image to figure. Args: image (np.ndarray): Image which should be added to the figure. title (str): Image title shown on the plot. color_map (Optional[str]): Name of matplotlib color map used to map scalar data to colours. Defaults to None. index (Optional[int]): Figure index. Defaults to None. """ if index is None: index = self.figure_index self.figure_index += 1 self.axis[index].imshow(image, color_map, vmin=0, vmax=255) self.axis[index].title.set_text(title) def add_text(self, image: np.ndarray, text: str, font: int = cv2.FONT_HERSHEY_PLAIN): """Puts text on an image. Args: image (np.ndarray): Input image. text (str): Text to add. font (Optional[int]): cv2 font type. Defaults to 0. Returns: np.ndarray: Image with text. """ image = image.copy() font_size = image.shape[1] // 256 + 1 # Text scale is calculated based on the reference size of 256 for i, line in enumerate(text.split("\n")): (text_w, text_h), baseline = cv2.getTextSize(line.strip(), font, font_size, thickness=1) offset = i * text_h cv2.rectangle(image, (0, offset + baseline // 2), (0 + text_w, 0 + text_h + offset), (255, 255, 255), -1) cv2.putText(image, line.strip(), (0, (baseline // 2 + text_h) + offset), font, font_size, (0, 0, 255)) return image def show(self): """Show image on a matplotlib figure.""" self.figure.show() def save(self, filename: Path): """Save image. Args: filename (Path): Filename to save image """ filename.parent.mkdir(parents=True, exist_ok=True) self.figure.savefig(filename, dpi=100) def close(self): """Close figure.""" plt.close(self.figure)