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How to use diff_objects method in Kiwi

Best Python code snippet using Kiwi_python

detection_analyzer.py

Source:detection_analyzer.py

1"""2Copyright (c) 2018-2021 Intel Corporation3Licensed under the Apache License, Version 2.0 (the "License");4you may not use this file except in compliance with the License.5You may obtain a copy of the License at6      http://www.apache.org/licenses/LICENSE-2.07Unless required by applicable law or agreed to in writing, software8distributed under the License is distributed on an "AS IS" BASIS,9WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.10See the License for the specific language governing permissions and11limitations under the License.12"""13from collections import Counter14import numpy as np15from .base_data_analyzer import BaseDataAnalyzer16from ..logging import print_info17class DetectionDataAnalyzer(BaseDataAnalyzer):18    __provider__ = 'DetectionAnnotation'19    def analyze(self, result: list, meta, count_objects=True):20        data_analysis = {}21        counter = Counter()22        all_boxes = 023        diff_objects = 024        width = 025        height = 026        width_diff = 027        height_diff = 028        size = len(result)29        for data in result:30            all_boxes += data.size31            width += np.sum(data.x_maxs - data.x_mins)32            height += np.sum(data.y_maxs - data.y_mins)33            if 'difficult_boxes' in data.metadata:34                diff_objects += len(data.metadata['difficult_boxes'])35                for i in data.metadata['difficult_boxes']:36                    width_diff += (data.x_maxs[i] - data.x_mins[i])37                    height_diff += (data.y_maxs[i] - data.y_mins[i])38            counter.update(data.labels)39        if count_objects:40            data_analysis['annotations_size'] = self.object_count(result)41        print_info('Total boxes {}'.format(all_boxes))42        data_analysis['all_boxes'] = all_boxes43        label_map = meta.get('label_map', {})44        for key in counter:45            if key in label_map:46                print_info('{name}: {value}'.format(name=label_map[key], value=counter[key]))47                data_analysis[label_map[key]] = counter[key]48            else:49                print_info('class_{key}: {value}'.format(key=key, value=counter[key]))50                data_analysis['class_{}'.format(key)] = counter[key]51        if size > 0:52            avg_num_diff_objects = diff_objects/size53            avg_num_all_objects = all_boxes/size54            avg_width = width/all_boxes55            avg_height = height/all_boxes56            print_info(57                'Average number of difficult objects (boxes) per image: {average}'.format(average=avg_num_diff_objects)58            )59            print_info(60                'Average number of objects (boxes) per image: {average}'.format(average=avg_num_all_objects)61            )62            print_info(63                'Average size detection object: width: {width}, '64                'height: {height}'.format(width=avg_width, height=avg_height)65            )66            data_analysis['average_num_difficult_objects'] = avg_num_diff_objects67            data_analysis['average_num_all_objects'] = avg_num_all_objects68            data_analysis['average_width'] = avg_width69            data_analysis['average_height'] = avg_height70            if diff_objects > 0:71                avg_width_diff_objects = width_diff/diff_objects72                avg_height_diff_objects = height_diff / diff_objects73                print_info(74                    'Average size difficult object: width: {width}, '75                    'height: {height}\n'.format(width=avg_width_diff_objects, height=avg_height_diff_objects)76                )77                data_analysis['average_width_difficult_objects'] = avg_width_diff_objects78                data_analysis['average_height_difficult_objects'] = avg_height_diff_objects...

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