def _evaluate_impl()

in easycv/core/evaluation/ocr_eval.py [0:0]


    def _evaluate_impl(self, gt, pred):

        def get_union(pD, pG):
            return Polygon(pD).union(Polygon(pG)).area

        def get_intersection_over_union(pD, pG):
            return get_intersection(pD, pG) / get_union(pD, pG)

        def get_intersection(pD, pG):
            return Polygon(pD).intersection(Polygon(pG)).area

        def compute_ap(confList, matchList, numGtCare):
            correct = 0
            AP = 0
            if len(confList) > 0:
                confList = np.array(confList)
                matchList = np.array(matchList)
                sorted_ind = np.argsort(-confList)
                confList = confList[sorted_ind]
                matchList = matchList[sorted_ind]
                for n in range(len(confList)):
                    match = matchList[n]
                    if match:
                        correct += 1
                        AP += float(correct) / (n + 1)

                if numGtCare > 0:
                    AP /= numGtCare

            return AP

        perSampleMetrics = {}

        matchedSum = 0

        Rectangle = namedtuple('Rectangle', 'xmin ymin xmax ymax')

        numGlobalCareGt = 0
        numGlobalCareDet = 0

        arrGlobalConfidences = []
        arrGlobalMatches = []

        recall = 0
        precision = 0
        hmean = 0

        detMatched = 0

        iouMat = np.empty([1, 1])

        gtPols = []
        detPols = []

        gtPolPoints = []
        detPolPoints = []

        # Array of Ground Truth Polygons' keys marked as don't Care
        gtDontCarePolsNum = []
        # Array of Detected Polygons' matched with a don't Care GT
        detDontCarePolsNum = []

        pairs = []
        detMatchedNums = []

        arrSampleConfidences = []
        arrSampleMatch = []

        evaluationLog = ''

        for n in range(len(gt)):
            points = gt[n]['points']
            # transcription = gt[n]['text']
            dontCare = gt[n]['ignore']
            #             points = Polygon(points)
            #             points = points.buffer(0)
            if not Polygon(points).is_valid or not Polygon(points).is_simple:
                continue

            gtPol = points
            gtPols.append(gtPol)
            gtPolPoints.append(points)
            if dontCare:
                gtDontCarePolsNum.append(len(gtPols) - 1)

        evaluationLog += 'GT polygons: ' + str(len(gtPols)) + (
            ' (' + str(len(gtDontCarePolsNum)) +
            " don't care)\n" if len(gtDontCarePolsNum) > 0 else '\n')

        for n in range(len(pred)):
            points = pred[n]['points']
            #             points = Polygon(points)
            #             points = points.buffer(0)
            if not Polygon(points).is_valid or not Polygon(points).is_simple:
                continue

            detPol = points
            detPols.append(detPol)
            detPolPoints.append(points)
            if len(gtDontCarePolsNum) > 0:
                for dontCarePol in gtDontCarePolsNum:
                    dontCarePol = gtPols[dontCarePol]
                    intersected_area = get_intersection(dontCarePol, detPol)
                    pdDimensions = Polygon(detPol).area
                    precision = 0 if pdDimensions == 0 else intersected_area / pdDimensions
                    if (precision > self.area_precision_constraint):
                        detDontCarePolsNum.append(len(detPols) - 1)
                        break

        evaluationLog += 'DET polygons: ' + str(len(detPols)) + (
            ' (' + str(len(detDontCarePolsNum)) +
            " don't care)\n" if len(detDontCarePolsNum) > 0 else '\n')

        if len(gtPols) > 0 and len(detPols) > 0:
            # Calculate IoU and precision matrixs
            outputShape = [len(gtPols), len(detPols)]
            iouMat = np.empty(outputShape)
            gtRectMat = np.zeros(len(gtPols), np.int8)
            detRectMat = np.zeros(len(detPols), np.int8)
            for gtNum in range(len(gtPols)):
                for detNum in range(len(detPols)):
                    pG = gtPols[gtNum]
                    pD = detPols[detNum]
                    iouMat[gtNum, detNum] = get_intersection_over_union(pD, pG)

            for gtNum in range(len(gtPols)):
                for detNum in range(len(detPols)):
                    if gtRectMat[gtNum] == 0 and detRectMat[
                            detNum] == 0 and gtNum not in gtDontCarePolsNum and detNum not in detDontCarePolsNum:
                        if iouMat[gtNum, detNum] > self.iou_constraint:
                            gtRectMat[gtNum] = 1
                            detRectMat[detNum] = 1
                            detMatched += 1
                            pairs.append({'gt': gtNum, 'det': detNum})
                            detMatchedNums.append(detNum)
                            evaluationLog += 'Match GT #' + \
                                             str(gtNum) + ' with Det #' + str(detNum) + '\n'

        numGtCare = (len(gtPols) - len(gtDontCarePolsNum))
        numDetCare = (len(detPols) - len(detDontCarePolsNum))
        if numGtCare == 0:
            recall = float(1)
            precision = float(0) if numDetCare > 0 else float(1)
        else:
            recall = float(detMatched) / numGtCare
            precision = 0 if numDetCare == 0 else float(
                detMatched) / numDetCare

        hmean = 0 if (precision +
                      recall) == 0 else 2.0 * precision * recall / (
                          precision + recall)

        matchedSum += detMatched
        numGlobalCareGt += numGtCare
        numGlobalCareDet += numDetCare

        perSampleMetrics = {
            'gtCare': numGtCare,
            'detCare': numDetCare,
            'detMatched': detMatched,
        }
        return perSampleMetrics