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Modified debug module to conform to clean code standards 

Signed-off-by: Jim Martens <github@2martens.de>
This commit is contained in:
Jim Martens 2019-07-10 12:12:13 +02:00
parent 4cf6723c28
commit a90c6c7c92
1 changed files with 23 additions and 9 deletions
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32
src/twomartens/masterthesis/debug.py
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@ -19,7 +19,7 @@
Handle debug functionality.
Functions:
save_ssd_train_images(images, labels, output_path):
save_ssd_train_images(...):
saves the first batch of SSD train images with overlaid ground truth bounding boxes
"""
import os
@ -29,19 +29,33 @@ import numpy as np
from matplotlib import pyplot
from PIL import Image
from twomartens.masterthesis import config
from twomartens.masterthesis.ssd_keras.eval_utils import coco_utils
def save_ssd_train_images(images: np.ndarray, labels: np.ndarray, output_path: str, custom_string: str = None) -> None:
annotation_file_train = f"{config.get_property('Paths.coco')}/annotations/instances_train2014.json"
_, _, _, classes_to_names = coco_utils.get_coco_category_maps(annotation_file_train)
def save_ssd_train_images(images: np.ndarray, labels: np.ndarray,
output_path: str, coco_path: str,
image_size: int, get_coco_cat_maps_func: callable,
custom_string: str = None) -> None:
"""
Saves given images and labels to given output path.
The images are saved both in a raw version and with bounding boxes printed on them.
Args:
images: a NumPy array of images
labels: a NumPy array of labels
output_path: path to save the images in
coco_path: path to the COCO data set
image_size: size of the resized images
get_coco_cat_maps_func: callable that returns the COCO category maps for a given annotation file
custom_string: optional custom string that is prepended to file names
"""
annotation_file_train = f"{coco_path}/annotations/instances_train2014.json"
_, _, _, classes_to_names = get_coco_cat_maps_func(annotation_file_train)
colors = pyplot.cm.hsv(np.linspace(0, 1, 81)).tolist()
os.makedirs(output_path, exist_ok=True)
nr_images = len(images)
nr_digits = math.ceil(math.log10(nr_images))
image_size = config.get_property("Parameters.ssd_image_size")
custom_string = f"{custom_string}_" if custom_string is not None else ""
for i, train_image in enumerate(images):
@ -70,5 +84,5 @@ def save_ssd_train_images(images: np.ndarray, labels: np.ndarray, output_path: s
linewidth=2))
current_axis.text(xmin, ymin, label, size='x-large', color='white',
bbox={'facecolor': color, 'alpha': 1.0})
pyplot.savefig(f"{output_path}/bboxes{str(i).zfill(nr_digits)}.png")
pyplot.savefig(f"{output_path}/{custom_string}bboxes{str(i).zfill(nr_digits)}.png")
pyplot.close(figure)