e7b28f5bda
Merge in RR/cv-analysis from remove_pil to master
Squashed commit of the following:
commit 83c8d88f3d48404251470176c70979ee75ae068b
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Jul 21 10:51:51 2022 +0200
remove deprecated server tests
commit cebc03b5399ac257a74036b41997201f882f5b74
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Thu Jul 21 10:51:08 2022 +0200
remove deprecated server tests
commit ce2845b0c51f001b7b5b8b195d6bf7e034ec4e39
Author: Julius Unverfehrt <julius.unverfehrt@iqser.com>
Date: Wed Jul 20 17:05:00 2022 +0200
repair tests to work without pillow WIP
commit 023fdab8322f28359a24c63e32635a3d0deccbe4
Author: Isaac Riley <Isaac.Riley@iqser.com>
Date: Wed Jul 20 16:40:36 2022 +0200
fixed typo
commit 33850ca83a175f74789ae6b9bebd057ed84b7fb3
Author: Isaac Riley <Isaac.Riley@iqser.com>
Date: Wed Jul 20 16:38:37 2022 +0200
fixed import from refactored open_img.py
commit dbc6d345f074e538948e2c4f94ebed8a5ef520bc
Author: Isaac Riley <Isaac.Riley@iqser.com>
Date: Wed Jul 20 16:32:42 2022 +0200
removed PIL from production code, now inly in scripts
84 lines
2.4 KiB
Python
84 lines
2.4 KiB
Python
import numpy as np
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from cv_analysis.utils.structures import Rectangle
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def xyxy_from_object(box_object):
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try:
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x1, y1, x2, y2 = box_object.xyxy()
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except:
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try:
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x1 = box_object["x"]
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y1 = box_object["y"]
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x2 = x1 + box_object["width"]
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y2 = y1 + box_object["height"]
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except:
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x1, y1, x2, y2 = box_object
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return x1, y1, x2, y2
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def xywh_from_object(box_object):
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try:
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x, y, w, h = box_object.xywh()
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except:
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try:
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x = box_object["x"]
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y = box_object["y"]
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w = box_object["width"]
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h = box_object["height"]
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except:
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x, y, w, h = box_object
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return x, y, w, h
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def compute_iou_from_boxes(box1: Rectangle, box2: list):
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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 = xywh_from_object(box1)
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bx1, by1, bw, bh = xywh_from_object(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(page["cells"]) for page in annotation_dict["pages"]])
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page_weights = page_weights / sum(page_weights)
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scores = []
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for i in range(len(annotation_dict["pages"])):
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scores.append(compute_page_iou(results_dict["pages"][i]["cells"], annotation_dict["pages"][i]["cells"]))
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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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