Unlock 30% off on Manual Testing Annual Plans this Holiday Season.

Copied to Clipboard!

How to use tags_stats method in avocado

Best Python code snippet using avocado_python

main.py

Source:main.py

1from typing import List, Set2import debug_load_envs  # before import sly3import supervisely as sly4from project_commons import ProjectCommons5from ann_provider import AnnProvider, AnnMemCache, AnnDiskCacheRemovable, AnnDiskCachePersistent6from tags_stats import TagsStatsConstructor, TagsStats, TagMetaChecks7import globals as g8def beware_of_nonexistent_tags(selected_tags: List[str], project: ProjectCommons) -> None:9    project_tag_names = set(t.name for t in project.meta.tag_metas)10    nonexistent_tags = [t for t in selected_tags if t not in project_tag_names]11    if len(nonexistent_tags):12        raise ValueError(f'Tags not found in project: {nonexistent_tags}')13def debug_log_tag_stats(tag_meta: sly.TagMeta, tags_stats: TagsStats) -> None:14    name = tag_meta.name15    tag_checks = TagMetaChecks(tag_meta)16    sly.logger.debug(f'Tag info: {name=} '17                     f'{tag_checks.has_appropriate_targets()=} '18                     f'{tag_checks.has_appropriate_value_type()=} '19                     f'{tags_stats.is_in_use(name)=} '20                     f'{tags_stats.has_single_geom_type(name)=} '21                     f'{tags_stats.objects_covered_cnt([name])=}')22def tag_is_appropriate(tag_name: str, project: ProjectCommons, tags_stats: TagsStats) -> bool:23    tag_meta = project.meta.tag_metas.get(tag_name)24    tag_checks = TagMetaChecks(tag_meta)25    if not tag_checks.has_appropriate_targets():26        sly.logger.warn(f'Inappropriate tag: wrong targets (like "images_only"). {tag_name=}')27    elif not tag_checks.has_appropriate_value_type():28        sly.logger.warn(f'Inappropriate tag: wrong value type (not None). {tag_name=}')29    elif not tags_stats.is_in_use(tag_name):30        sly.logger.warn(f'Inappropriate tag: not associated with any object. {tag_name=}')31    elif not tags_stats.has_single_geom_type(tag_name):32        raise ValueError(f'Inappropriate tag: associated with objects of different shapes. {tag_name=}')33    else:34        return True35    return False36def ensure_tag_set_is_appropriate(tag_names: List[str], tags_stats: TagsStats) -> None:37    if not tags_stats.have_not_intersected(tag_names):38        example = tags_stats.example_intersected(tag_names)39        raise ValueError(f'Inappropriate tag set: object associated with some tags is found. '40                         f'Wrong tags example: {example}')41    class_names_rest = tags_stats.classes_not_covered_entirely(tag_names)42    class_tag_name_inters = set(tag_names).intersection(class_names_rest)43    if class_tag_name_inters:44        raise ValueError(f'Inappropriate tag set: some tag has same name with remaining class. '45                         f'Wrong names: {class_tag_name_inters}')46    obj_covered_cnt = tags_stats.objects_covered_cnt(tag_names)47    total_obj_cnt = tags_stats.objects_count48    if class_names_rest:49        sly.logger.warn(f'There are objects in project which are not associated with any of selected tags. '50                        f'Covered: {(obj_covered_cnt / total_obj_cnt):.1%}. '51                        f'Total number of objects: {total_obj_cnt}. '52                        f'Number of object covered by selected tags: {obj_covered_cnt}. '53                        f'Remaining classes: {class_names_rest}')54    tags_with_images = tags_stats.tags_associated_with_images(tag_names)55    if tags_with_images:56        sly.logger.warn(f'Some of selected tags are associated with images, those associations will be remained. '57                        f'Tag names: {tags_with_images}')58    sly.logger.info(f'Tags for conversion: {tag_names}')59class ProjectMetaConstructor:60    def __init__(self, src_project_meta: sly.ProjectMeta, tags_stats: TagsStats):61        self._src_project_meta = src_project_meta62        self._tags_stats = tags_stats63    def create_new_tags(self, appropriate_tags: List[str]) -> sly.TagMetaCollection:64        src_tag_names = set(t.name for t in self._src_project_meta.tag_metas)65        tag_names_remaining = self._tags_stats.tags_associated_with_images(appropriate_tags)66        tags_names_to_del = set(appropriate_tags) - tag_names_remaining67        res_tag_names = src_tag_names - tags_names_to_del68        res_tags_lst = [t.clone() for t in self._src_project_meta.tag_metas if t.name in res_tag_names]69        res_tags = sly.TagMetaCollection(res_tags_lst)70        return res_tags71    def create_new_classes(self, appropriate_tags: List[str]) -> sly.ObjClassCollection:72        class_names_remaining = self._tags_stats.classes_not_covered_entirely(appropriate_tags)73        res_classes_lst = [self._src_project_meta.obj_classes.get(c).clone() for c in class_names_remaining]74        for tag_name in appropriate_tags:75            src_tag_meta = self._src_project_meta.tag_metas.get(tag_name)76            geom_type = self._tags_stats.geometry_type(tag_name)77            new_cls = sly.ObjClass(name=tag_name,78                                   geometry_type=geom_type,79                                   color=src_tag_meta.color,80                                   hotkey=src_tag_meta.hotkey)81            res_classes_lst.append(new_cls)82        res_classes = sly.ObjClassCollection(res_classes_lst)83        return res_classes84    def create_new_project_meta(self, appropriate_tags: List[str]) -> sly.ProjectMeta:85        res_tags = self.create_new_tags(appropriate_tags)86        res_classes = self.create_new_classes(appropriate_tags)87        res_meta = self._src_project_meta.clone(obj_classes=res_classes, tag_metas=res_tags)88        return res_meta89class AnnConvertor:90    def __init__(self, appropriate_tags: List[str], src_meta: sly.ProjectMeta, res_meta: sly.ProjectMeta):91        self.tags_to_convert = set(appropriate_tags)92        self.src_meta = src_meta93        self.res_meta = res_meta94    def convert(self, ann: sly.Annotation):95        res_labels = self._convert_labels(ann.labels)96        res_img_tags = self._convert_tags(ann.img_tags, tags_to_rm=set())97        res_ann = ann.clone(labels=res_labels, img_tags=res_img_tags)98        return res_ann99    def _convert_tags(self, tags: sly.TagCollection, tags_to_rm: Set[str]):100        return sly.TagCollection([self._convert_tag(t) for t in tags if t.name not in tags_to_rm])101    def _convert_tag(self, tag: sly.Tag):102        new_tag_meta = self.res_meta.tag_metas.get(tag.name)103        return tag.clone(meta=new_tag_meta)104    def _convert_labels(self, labels: List[sly.Label]):105        return [self._convert_label(lbl) for lbl in labels]106    def _convert_label(self, label: sly.Label):107        important_tags = self.tags_to_convert.intersection(t.name for t in label.tags)108        assert len(important_tags) < 2109        if not important_tags:110            new_name = label.obj_class.name111        else:112            new_name = next(iter(important_tags))113        new_cls = self.res_meta.obj_classes.get(new_name)114        new_tags = self._convert_tags(label.tags, tags_to_rm=important_tags)115        return label.clone(obj_class=new_cls, tags=new_tags)116class DatasetShadowCreator:117    def __init__(self, api: sly.Api, res_project_id: int):118        self._api = api119        self._res_project_id = res_project_id120        self._map = {}121    def get_new(self, src_ds_info):122        res_info = self._map.get(src_ds_info.id)123        if res_info is None:124            res_info = self._api.dataset.create(self._res_project_id, src_ds_info.name,125                                                change_name_if_conflict=True)126            self._map[src_ds_info.id] = res_info127        return res_info128@sly.timeit129def tags_to_classes(api: sly.Api, selected_tags: List[str], result_project_name: str):130    project = ProjectCommons(api, g.project_id)131    if not result_project_name:132        result_project_name = f'{project.info.name} Untagged'133    # Step 0: collect tag associations134    beware_of_nonexistent_tags(selected_tags, project)135    # ann_cache = AnnDiskCachePersistent(g.temp_data_directory)   # for debugging purposes136    if len(project) < g.anns_in_memory_limit:137        ann_cache = AnnMemCache()138    else:139        ann_cache = AnnDiskCacheRemovable(g.temp_data_directory)140    sly.logger.debug(f'Ann cache type: {type(ann_cache)}')141    ann_provider = AnnProvider(api, project, ann_cache=ann_cache)142    tags_stats_constructor = TagsStatsConstructor(project.meta)143    progress = sly.Progress('Collecting tags data', len(project), min_report_percent=5)144    for ann in ann_provider.get_anns():145        tags_stats_constructor.update_with_annotation(ann)146        progress.iter_done_report()147    tags_stats = tags_stats_constructor.get_stats()148    sly.logger.info('Tag statistics are collected', extra={149        'total_tags_cnt': len(project.meta.tag_metas),150        'total_objects_cnt': tags_stats.objects_count151    })152    for tag_meta in project.meta.tag_metas:153        debug_log_tag_stats(tag_meta, tags_stats)154    # Step 1: check selected tags155    appropriate_tag_names = [t for t in set(selected_tags) if tag_is_appropriate(t, project, tags_stats)]156    ensure_tag_set_is_appropriate(appropriate_tag_names, tags_stats)157    # Step 2: convert annotations & upload158    meta_constructor = ProjectMetaConstructor(project.meta, tags_stats)159    res_meta = meta_constructor.create_new_project_meta(appropriate_tag_names)160    sly.logger.info(f'Resulting tags: {sorted(t.name for t in res_meta.tag_metas)}')161    sly.logger.info(f'Resulting classes: {sorted(c.name for c in res_meta.obj_classes)}')162    res_project_info = api.project.create(g.workspace_id, result_project_name,163                                          type=sly.ProjectType.IMAGES, change_name_if_conflict=True)164    api.project.update_meta(res_project_info.id, res_meta.to_json())165    sly.logger.info(f'Resulting project name: {res_project_info.name!r}')166    ann_convertor = AnnConvertor(appropriate_tag_names, src_meta=project.meta, res_meta=res_meta)167    dataset_creator = DatasetShadowCreator(api, res_project_info.id)168    progress = sly.Progress('Converting classes', len(project))169    for ds_info, img_ids, img_hashes, img_names in project.iterate_batched():170        res_ds_info = dataset_creator.get_new(ds_info)171        anns = ann_provider.get_anns_by_img_ids(ds_info.id, img_ids)172        res_anns = [ann_convertor.convert(ann) for ann in anns]173        new_img_infos = api.image.upload_hashes(res_ds_info.id, names=img_names, hashes=img_hashes)174        api.annotation.upload_anns([i.id for i in new_img_infos], res_anns)175        progress.iters_done_report(len(img_ids))176    sly.logger.debug('Finished tags_to_classes')177if __name__ == '__main__':178    sly.logger.info(179        'Script arguments',180        extra={181            'context.teamId': g.team_id,182            'context.workspaceId': g.workspace_id,183            'modal.state.slyProjectId': g.project_id,184            'modal.state.selectedTags.tags': g.selected_tags,185            'modal.state.resultProjectName': g.res_project_name186        },187    )188    tags_to_classes(g.api, g.selected_tags, g.res_project_name)189    try:190        sly.app.fastapi.shutdown()191    except KeyboardInterrupt:...

concept_stats.py

Source:concept_stats.py

1#-----------------------------------------------------------------------2# concept_stats.py3#-----------------------------------------------------------------------4# Author: Brian Nemsick (bnensick3)5# Semester: Fall 20146# Team: Intelligent Review7#-----------------------------------------------------------------------8# Purpose: to calculate static concept statistics in ITS.9# Including:10#	1. Cross Corrolation P(A|B), given tag B is tagged, what is the 11#	probability that A is also tagged.12#	2. Tag use in terms of total questions.13#-----------------------------------------------------------------------14import its_query as itsq15from its_definitions import get_category16class concept_stats(object):17	18	its_query_handle = None19	its_table_handle = None20	21	#-------------------------------------------------------------------22	# Index Defines (Constants) for general_stats23	#-------------------------------------------------------------------24	NAME = 0;25	TAGS_ID = 1;26	COUNT = 2;27	MAPPED_ID = 3;28	TOTAL_CORR = 4;29	general_stats = []30	31	#Used to map tags_id to indexes for cross correlation32	#cross_key[0] = tag033	cross_key = []34	35	#total_correlation[0] = total_correlation[cross_key[0]]36	total_correlation = []37	38	#total_questions39	total_questions = []40	41	#-------------------------------------------------------------------42	# Format of cross_correlation:43	#-------------------------------------------------------------------44	# 	  Tag0 | Tag1 | ... | TagN|45	#-------------------------------------------------------------------46	# Tag0	1  |  ... | ... |47	#-------------------------------------------------------------------48	# Tag1 ...                                   49	#-------------------------------------------------------------------50	# Tag2 ...    								   51	#-------------------------------------------------------------------52	cross_correlation = []53	54	55	def __init__(self):56		57		#Open connection to read from ITS database58		self.its_query_handle = itsq.its_query()59		self.its_query_handle.open_connection()60		61		#Calculate static concept statistics62		self.calc_concept_stats()63		64		#Close connection to read from ITS database65		self.its_query_handle.close_connection()66		67	def calc_concept_stats(self):68		69		#---------------------------------------------------------------70		# Tags Query -> general_stats71		#---------------------------------------------------------------72		# Find tags (actual name), tags_id, total occurrence for ITS73		# assignment 1-7.74		#---------------------------------------------------------------75		questions_id_query =  "SELECT id FROM questions WHERE " + get_category(0)76		tags_stats_query = "SELECT tags.name, questions_tags.tags_id, COUNT(*) FROM questions_tags INNER JOIN tags ON tags.id = questions_tags.tags_id WHERE questions_tags.questions_id IN (" + questions_id_query + ") GROUP BY questions_tags.tags_id HAVING COUNT(*) >= 1" 77		tags_stats = self.its_query_handle.exec_its_query(tags_stats_query)78		79		num_tags = len(tags_stats) #Number of active tags80		81		#Insert into data arrays82		for i in range (0,num_tags):83			self.general_stats.append([str(tags_stats[i][self.NAME]),int(tags_stats[i][self.TAGS_ID]),int(tags_stats[i][self.COUNT]),i,0])84			self.cross_key.append(int(tags_stats[i][self.TAGS_ID]))85			self.total_questions.append(int(tags_stats[i][self.COUNT]))86		87		88		#---------------------------------------------------------------89		# Cross Corrolation Query -> cross_correlation90		#---------------------------------------------------------------91		# Find cross corrolation of all tags used by ITS92		# Defined as the P(A|B) - Conditional Probability93		#---------------------------------------------------------------94		for B in range (0, num_tags):95			96			#Calculate once to improve computation speed97			current_tags_id = str(self.general_stats[B][self.TAGS_ID])98			current_tags_total_questions = int(self.general_stats[B][self.COUNT])99			100			#Declare an empty 0's array101			current_cross_corr = [0] * num_tags102			cross_corr_concepts_query = "SELECT tags_id,COUNT(*) FROM questions_tags WHERE (questions_id IN (SELECT questions_id FROM questions_tags WHERE tags_id = " + current_tags_id  + " )) AND questions_id IN (SELECT id FROM questions WHERE " + get_category(0) +") GROUP BY tags_id HAVING COUNT(*) >= 1"103			cross_corr_concepts = self.its_query_handle.exec_its_query(cross_corr_concepts_query)104			105			for A in range (0, len(cross_corr_concepts)):106				if (int(cross_corr_concepts[A][0]) != 0):107					ind = self.cross_key.index(int(cross_corr_concepts[A][0]))108					current_cross_corr[ind] = float(float(cross_corr_concepts[A][1])/current_tags_total_questions)109				110			#Add data to class variable111			self.cross_correlation.append(current_cross_corr)112			113			#Total correlation correction for tags with limited questions114			current_total_corr = sum(current_cross_corr)115			116			self.general_stats[B][self.TOTAL_CORR] = current_total_corr 117			self.total_correlation.append(current_total_corr)...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.