236 lines
8.1 KiB
Python
236 lines
8.1 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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from collections import namedtuple
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import numpy as np
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from shapely.geometry import Polygon
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"""
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reference from :
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https://github.com/MhLiao/DB/blob/3c32b808d4412680310d3d28eeb6a2d5bf1566c5/concern/icdar2015_eval/detection/iou.py#L8
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"""
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class DetectionIoUEvaluator(object):
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def __init__(self, iou_constraint=0.5, area_precision_constraint=0.5):
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self.iou_constraint = iou_constraint
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self.area_precision_constraint = area_precision_constraint
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def evaluate_image(self, gt, pred):
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def get_union(pD, pG):
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return Polygon(pD).union(Polygon(pG)).area
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def get_intersection_over_union(pD, pG):
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return get_intersection(pD, pG) / get_union(pD, pG)
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def get_intersection(pD, pG):
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return Polygon(pD).intersection(Polygon(pG)).area
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def compute_ap(confList, matchList, numGtCare):
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correct = 0
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AP = 0
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if len(confList) > 0:
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confList = np.array(confList)
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matchList = np.array(matchList)
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sorted_ind = np.argsort(-confList)
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confList = confList[sorted_ind]
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matchList = matchList[sorted_ind]
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for n in range(len(confList)):
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match = matchList[n]
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if match:
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correct += 1
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AP += float(correct) / (n + 1)
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if numGtCare > 0:
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AP /= numGtCare
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return AP
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perSampleMetrics = {}
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matchedSum = 0
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Rectangle = namedtuple('Rectangle', 'xmin ymin xmax ymax')
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numGlobalCareGt = 0
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numGlobalCareDet = 0
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arrGlobalConfidences = []
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arrGlobalMatches = []
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recall = 0
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precision = 0
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hmean = 0
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detMatched = 0
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iouMat = np.empty([1, 1])
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gtPols = []
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detPols = []
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gtPolPoints = []
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detPolPoints = []
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# Array of Ground Truth Polygons' keys marked as don't Care
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gtDontCarePolsNum = []
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# Array of Detected Polygons' matched with a don't Care GT
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detDontCarePolsNum = []
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pairs = []
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detMatchedNums = []
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arrSampleConfidences = []
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arrSampleMatch = []
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evaluationLog = ""
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# print(len(gt))
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for n in range(len(gt)):
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points = gt[n]['points']
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# transcription = gt[n]['text']
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dontCare = gt[n]['ignore']
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# points = Polygon(points)
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# points = points.buffer(0)
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if not Polygon(points).is_valid or not Polygon(points).is_simple:
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continue
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gtPol = points
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gtPols.append(gtPol)
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gtPolPoints.append(points)
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if dontCare:
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gtDontCarePolsNum.append(len(gtPols) - 1)
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evaluationLog += "GT polygons: " + str(len(gtPols)) + (
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" (" + str(len(gtDontCarePolsNum)) + " don't care)\n"
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if len(gtDontCarePolsNum) > 0 else "\n")
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for n in range(len(pred)):
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points = pred[n]['points']
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# points = Polygon(points)
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# points = points.buffer(0)
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if not Polygon(points).is_valid or not Polygon(points).is_simple:
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continue
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detPol = points
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detPols.append(detPol)
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detPolPoints.append(points)
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if len(gtDontCarePolsNum) > 0:
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for dontCarePol in gtDontCarePolsNum:
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dontCarePol = gtPols[dontCarePol]
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intersected_area = get_intersection(dontCarePol, detPol)
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pdDimensions = Polygon(detPol).area
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precision = 0 if pdDimensions == 0 else intersected_area / pdDimensions
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if (precision > self.area_precision_constraint):
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detDontCarePolsNum.append(len(detPols) - 1)
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break
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evaluationLog += "DET polygons: " + str(len(detPols)) + (
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" (" + str(len(detDontCarePolsNum)) + " don't care)\n"
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if len(detDontCarePolsNum) > 0 else "\n")
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if len(gtPols) > 0 and len(detPols) > 0:
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# Calculate IoU and precision matrixs
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outputShape = [len(gtPols), len(detPols)]
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iouMat = np.empty(outputShape)
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gtRectMat = np.zeros(len(gtPols), np.int8)
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detRectMat = np.zeros(len(detPols), np.int8)
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for gtNum in range(len(gtPols)):
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for detNum in range(len(detPols)):
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pG = gtPols[gtNum]
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pD = detPols[detNum]
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iouMat[gtNum, detNum] = get_intersection_over_union(pD, pG)
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for gtNum in range(len(gtPols)):
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for detNum in range(len(detPols)):
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if gtRectMat[gtNum] == 0 and detRectMat[
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detNum] == 0 and gtNum not in gtDontCarePolsNum and detNum not in detDontCarePolsNum:
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if iouMat[gtNum, detNum] > self.iou_constraint:
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gtRectMat[gtNum] = 1
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detRectMat[detNum] = 1
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detMatched += 1
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pairs.append({'gt': gtNum, 'det': detNum})
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detMatchedNums.append(detNum)
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evaluationLog += "Match GT #" + \
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str(gtNum) + " with Det #" + str(detNum) + "\n"
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numGtCare = (len(gtPols) - len(gtDontCarePolsNum))
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numDetCare = (len(detPols) - len(detDontCarePolsNum))
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if numGtCare == 0:
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recall = float(1)
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precision = float(0) if numDetCare > 0 else float(1)
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else:
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recall = float(detMatched) / numGtCare
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precision = 0 if numDetCare == 0 else float(detMatched) / numDetCare
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hmean = 0 if (precision + recall) == 0 else 2.0 * \
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precision * recall / (precision + recall)
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matchedSum += detMatched
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numGlobalCareGt += numGtCare
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numGlobalCareDet += numDetCare
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perSampleMetrics = {
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'precision': precision,
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'recall': recall,
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'hmean': hmean,
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'pairs': pairs,
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'iouMat': [] if len(detPols) > 100 else iouMat.tolist(),
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'gtPolPoints': gtPolPoints,
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'detPolPoints': detPolPoints,
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'gtCare': numGtCare,
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'detCare': numDetCare,
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'gtDontCare': gtDontCarePolsNum,
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'detDontCare': detDontCarePolsNum,
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'detMatched': detMatched,
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'evaluationLog': evaluationLog
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}
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return perSampleMetrics
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def combine_results(self, results):
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numGlobalCareGt = 0
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numGlobalCareDet = 0
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matchedSum = 0
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for result in results:
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numGlobalCareGt += result['gtCare']
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numGlobalCareDet += result['detCare']
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matchedSum += result['detMatched']
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methodRecall = 0 if numGlobalCareGt == 0 else float(
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matchedSum) / numGlobalCareGt
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methodPrecision = 0 if numGlobalCareDet == 0 else float(
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matchedSum) / numGlobalCareDet
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methodHmean = 0 if methodRecall + methodPrecision == 0 else 2 * \
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methodRecall * methodPrecision / (methodRecall + methodPrecision)
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# print(methodRecall, methodPrecision, methodHmean)
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# sys.exit(-1)
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methodMetrics = {
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'precision': methodPrecision,
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'recall': methodRecall,
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'hmean': methodHmean
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}
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return methodMetrics
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if __name__ == '__main__':
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evaluator = DetectionIoUEvaluator()
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gts = [[{
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'points': [(0, 0), (1, 0), (1, 1), (0, 1)],
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'text': 1234,
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'ignore': False,
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}, {
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'points': [(2, 2), (3, 2), (3, 3), (2, 3)],
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'text': 5678,
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'ignore': False,
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}]]
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preds = [[{
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'points': [(0.1, 0.1), (1, 0), (1, 1), (0, 1)],
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'text': 123,
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'ignore': False,
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}]]
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results = []
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for gt, pred in zip(gts, preds):
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results.append(evaluator.evaluate_image(gt, pred))
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metrics = evaluator.combine_results(results)
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print(metrics)
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