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"""utils.py: Helper Functions to keep this Repo Standalone"""
# System Imports
from math import sin, cos, radians, sqrt
__author__ = "Johannes Bayer"
__copyright__ = "Copyright 2023, DFKI"
__license__ = "CC"
__version__ = "0.0.1"
__email__ = "johannes.bayer@dfki.de"
__status__ = "Prototype"
def shift(p, q):
"""Shifts a Point by another point"""
return [p[0]+q[0], p[1]+q[1]]
def rotate(p, angle):
"""Rotates a Point by an Angle"""
return [p[0] * cos(angle) - p[1] * sin(angle),
p[0] * sin(angle) + p[1] * cos(angle)]
def scale(p, scale_x, scale_y):
"""Scales a Point in two Dimensions"""
return [p[0]*scale_x, p[1]*scale_y]
def transform(port, bb):
"""Transforms a Point from Unit Space (classes ports) to Global Bounding Box (image)"""
p = shift(port['position'], (-.5, -0.5)) # Normalize: [0.0, 1.0]^2 -> [-0.5, 0-5]^2
p = scale(p, 1.0, -1.0) # Flip
p = rotate(p, -radians(bb['rotation']))
p = scale(p, bb["xmax"] - bb["xmin"], bb["ymax"] - bb["ymin"])
p = shift(p, [(bb["xmin"]+bb["xmax"])/2, (bb["ymin"]+bb["ymax"])/2])
return {"name": port['name'], "position": p}
def bbdist(bb1, bb2):
"""Calculates the Distance between two Bounding Box Annotations"""
return sqrt(((bb1["xmin"]+bb1["xmax"])/2 - (bb2["xmin"]+bb2["xmax"])/2)**2 +
((bb1["ymin"]+bb1["ymax"])/2 - (bb2["ymin"]+bb2["ymax"])/2)**2)
def overlap(bbox1, bbox2):
if bbox1["xmin"] > bbox2["xmax"] or bbox1["xmax"] < bbox2["xmin"]:
return False
if bbox1["ymin"] > bbox2["ymax"] or bbox1["ymax"] < bbox2["ymin"]:
return False
return True
def associated_keypoints(instances, shape):
"""Returns the points with same group id as the provided polygon"""
return [point for point in instances["points"]
if point["group"] == shape["group"] and point["class"] == "connector"]
def IoU(bb1, bb2):
"""Intersection over Union"""
intersection = 1
union = 1
return intersection/union
if __name__ == "__main__":
import sys
from loader import read_pascal_voc, write_pascal_voc
import numpy as np
import random
if len(sys.argv) == 3:
source = sys.argv[1]
target = sys.argv[2]
ann1, ann2 = [[bbox for bbox in read_pascal_voc(path)['bboxes'] if bbox['class'] == "text"]
for path in [source, target]]
if not len(ann1) == len(ann2):
print(f"Warning: Unequal Text Count ({len(ann1)} vs. {len(ann2)}), cropping..")
consensus = min(len(ann1), len(ann2))
ann1 = ann1[:consensus]
ann2 = ann2[:consensus]
x1 = np.array([(bbox['xmin']+bbox['xmax'])/2 for bbox in ann1])
y1 = np.array([(bbox['ymin']+bbox['ymax'])/2 for bbox in ann1])
x2 = np.array([(bbox['xmin']+bbox['xmax'])/2 for bbox in ann2])
y2 = np.array([(bbox['ymin']+bbox['ymax'])/2 for bbox in ann2])
x1 = ((x1-np.min(x1))/(np.max(x1)-np.min(x1))) * (np.max(x2)-np.min(x2)) + np.min(x2)
y1 = ((y1-np.min(y1))/(np.max(y1)-np.min(y1))) * (np.max(y2)-np.min(y2)) + np.min(y2)
dist = np.sqrt((x1-x2[np.newaxis].T)**2 + (y1-y2[np.newaxis].T)**2)
indices_1 = np.arange(len(ann1))
indices_2 = np.arange(len(ann2))
print(np.sum(np.diagonal(dist)))
for i in range(10000):
if random.random() > 0.5:
max_dist_pos = np.argmax(np.diagonal(dist)) # Mitigate Largest Cost
else:
max_dist_pos = random.randint(0, len(ann1)-1)
if np.min(dist[max_dist_pos, :]) < np.min(dist[:, max_dist_pos]):
min_dist_pos = np.argmin(dist[max_dist_pos, :])
dist[:, [max_dist_pos, min_dist_pos]] = dist[:, [min_dist_pos, max_dist_pos]] # Swap Columns
indices_1[[max_dist_pos, min_dist_pos]] = indices_1[[min_dist_pos, max_dist_pos]]
else:
min_dist_pos = np.argmin(dist[:, max_dist_pos])
dist[[max_dist_pos, min_dist_pos], :] = dist[[min_dist_pos, max_dist_pos], :] # Swap Rows
indices_2[[max_dist_pos, min_dist_pos]] = indices_2[[min_dist_pos, max_dist_pos]]
print(np.sum(np.diagonal(dist)))
wb = read_pascal_voc(target)
for i in range(len(ann1)):
ann2[indices_2[i]]['text'] = ann1[indices_1[i]]['text']
bbox_match = [bbox for bbox in wb['bboxes']
if bbox['xmin'] == ann2[indices_2[i]]['xmin'] and
bbox['xmax'] == ann2[indices_2[i]]['xmax'] and
bbox['ymin'] == ann2[indices_2[i]]['ymin'] and
bbox['ymax'] == ann2[indices_2[i]]['ymax']]
if len(bbox_match) == 1:
bbox_match[0]['text'] = ann1[indices_1[i]]['text']
bbox_match[0]['rotation'] = ann1[indices_1[i]]['rotation']
write_pascal_voc(wb)
else:
print("Args: source target")
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