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"""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)
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