55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
import numpy as np
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def compute_iou_from_boxes(box1, box2):
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"""
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Each box of the form (x1, y1, delx, dely)
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"""
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ax1, ay1, aw, ah = box1
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bx1, by1, bw, bh = box2
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ax2, ay2, bx2, by2 = ax1 + aw, ay1 + ah, bx1 + bw, by1 + bh
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if (ax1 > bx2) or (bx1 > ax2) or (ay1 > by2) or (by1 > ay2):
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return 0
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intersection = (min(ax2, bx2) - max(ax1, bx1)) * (min(ay2, by2) - max(ay1, by1))
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area_a = (ax2 - ax1) * (ay2 - ay1)
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area_b = (bx2 - bx1) * (by2 - by1)
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union = area_a + area_b - intersection
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return intersection / union
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def find_max_overlap(box, box_list):
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best_candidate = max(box_list, key=lambda x: compute_iou_from_boxes(box, x))
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iou = compute_iou_from_boxes(box, best_candidate)
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return best_candidate, iou
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def compute_page_iou(results_box_list, gt_box_list):
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results = results_box_list.copy()
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gt = gt_box_list.copy()
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if (not results) or (not gt):
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return 0
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iou_sum = 0
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denominator = max(len(results), len(gt))
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while gt and results:
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gt_box = gt.pop()
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best_match, best_iou = find_max_overlap(gt_box, results)
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results.remove(best_match)
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iou_sum += best_iou
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score = iou_sum / denominator
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return score
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def compute_document_score(results_dict, annotation_dict):
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page_weights = np.array([len(v) for v in annotation_dict.values()])
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page_weights = page_weights / sum(page_weights)
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scores = []
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for key in annotation_dict:
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scores.append(compute_page_iou(results_dict[key], annotation_dict[key]))
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scores = np.array(scores)
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doc_score = np.average(scores, weights=page_weights)
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return doc_score
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def compute_document_score_tables(results_dict, annotation_dict):
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pass
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