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