'''simple docstring'''

import unittest

from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_tf,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
 from PIL import Image
else:


 class     __UpperCAmelCase       :





   @staticmethod
   def 						UpperCAmelCase_	(	*_lowerCamelCase    ,     **_lowerCamelCase ):
      pass


@is_pipeline_test
@require_vision
@require_torch
class     __UpperCAmelCase       ( unittest.TestCase		):
  __A :				Tuple											= MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING





  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase ):
     lowerCAmelCase_			=      pipeline(
         '''zero-shot-object-detection'''    ,     model='''hf-internal-testing/tiny-random-owlvit-object-detection''' )

     lowerCAmelCase_			=      [
         {
             '''image''': '''./tests/fixtures/tests_samples/COCO/000000039769.png''',
             '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
         }
     ]
     return object_detector, examples





  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase    ,     _lowerCamelCase ):
     lowerCAmelCase_			=      object_detector(examples[0]    ,     threshold=0.0 )

     lowerCAmelCase_			=      len(_lowercase )
     self.assertGreater(_lowercase    ,     0 )
     self.assertEqual(
         _lowercase    ,     [
             {
                 '''score''': ANY(_lowercase ),
                 '''label''': ANY(_lowercase ),
                 '''box''': {'''xmin''': ANY(_lowercase ), '''ymin''': ANY(_lowercase ), '''xmax''': ANY(_lowercase ), '''ymax''': ANY(_lowercase )},
             }
             for i in range(_lowercase )
         ]    ,     )





  @require_tf
  @unittest.skip('''Zero Shot Object Detection not implemented in TF''' )
  def 						UpperCAmelCase_	(	self ):
     pass





  @require_torch
  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      pipeline(
         '''zero-shot-object-detection'''    ,     model='''hf-internal-testing/tiny-random-owlvit-object-detection''' )

     lowerCAmelCase_			=      object_detector(
         '''./tests/fixtures/tests_samples/COCO/000000039769.png'''    ,     candidate_labels=['''cat''', '''remote''', '''couch''']    ,     threshold=0.64    ,     )

     self.assertEqual(
         nested_simplify(_lowercase    ,     decimals=4 )    ,     [
             {'''score''': 0.72_35, '''label''': '''cat''', '''box''': {'''xmin''': 204, '''ymin''': 167, '''xmax''': 232, '''ymax''': 190}},
             {'''score''': 0.72_18, '''label''': '''remote''', '''box''': {'''xmin''': 204, '''ymin''': 167, '''xmax''': 232, '''ymax''': 190}},
             {'''score''': 0.71_84, '''label''': '''couch''', '''box''': {'''xmin''': 204, '''ymin''': 167, '''xmax''': 232, '''ymax''': 190}},
             {'''score''': 0.67_48, '''label''': '''remote''', '''box''': {'''xmin''': 571, '''ymin''': 83, '''xmax''': 598, '''ymax''': 103}},
             {'''score''': 0.66_56, '''label''': '''cat''', '''box''': {'''xmin''': 571, '''ymin''': 83, '''xmax''': 598, '''ymax''': 103}},
             {'''score''': 0.66_14, '''label''': '''couch''', '''box''': {'''xmin''': 571, '''ymin''': 83, '''xmax''': 598, '''ymax''': 103}},
             {'''score''': 0.64_56, '''label''': '''remote''', '''box''': {'''xmin''': 494, '''ymin''': 105, '''xmax''': 521, '''ymax''': 127}},
             {'''score''': 0.6_42, '''label''': '''remote''', '''box''': {'''xmin''': 67, '''ymin''': 274, '''xmax''': 93, '''ymax''': 297}},
             {'''score''': 0.64_19, '''label''': '''cat''', '''box''': {'''xmin''': 494, '''ymin''': 105, '''xmax''': 521, '''ymax''': 127}},
         ]    ,     )

     lowerCAmelCase_			=      object_detector(
         [
             {
                 '''image''': '''./tests/fixtures/tests_samples/COCO/000000039769.png''',
                 '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
             }
         ]    ,     threshold=0.64    ,     )

     self.assertEqual(
         nested_simplify(_lowercase    ,     decimals=4 )    ,     [
             [
                 {'''score''': 0.72_35, '''label''': '''cat''', '''box''': {'''xmin''': 204, '''ymin''': 167, '''xmax''': 232, '''ymax''': 190}},
                 {'''score''': 0.72_18, '''label''': '''remote''', '''box''': {'''xmin''': 204, '''ymin''': 167, '''xmax''': 232, '''ymax''': 190}},
                 {'''score''': 0.71_84, '''label''': '''couch''', '''box''': {'''xmin''': 204, '''ymin''': 167, '''xmax''': 232, '''ymax''': 190}},
                 {'''score''': 0.67_48, '''label''': '''remote''', '''box''': {'''xmin''': 571, '''ymin''': 83, '''xmax''': 598, '''ymax''': 103}},
                 {'''score''': 0.66_56, '''label''': '''cat''', '''box''': {'''xmin''': 571, '''ymin''': 83, '''xmax''': 598, '''ymax''': 103}},
                 {'''score''': 0.66_14, '''label''': '''couch''', '''box''': {'''xmin''': 571, '''ymin''': 83, '''xmax''': 598, '''ymax''': 103}},
                 {'''score''': 0.64_56, '''label''': '''remote''', '''box''': {'''xmin''': 494, '''ymin''': 105, '''xmax''': 521, '''ymax''': 127}},
                 {'''score''': 0.6_42, '''label''': '''remote''', '''box''': {'''xmin''': 67, '''ymin''': 274, '''xmax''': 93, '''ymax''': 297}},
                 {'''score''': 0.64_19, '''label''': '''cat''', '''box''': {'''xmin''': 494, '''ymin''': 105, '''xmax''': 521, '''ymax''': 127}},
             ]
         ]    ,     )





  @require_torch
  @slow
  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      pipeline('''zero-shot-object-detection''' )

     lowerCAmelCase_			=      object_detector(
         '''http://images.cocodataset.org/val2017/000000039769.jpg'''    ,     candidate_labels=['''cat''', '''remote''', '''couch''']    ,     )
     self.assertEqual(
         nested_simplify(_lowercase    ,     decimals=4 )    ,     [
             {'''score''': 0.28_68, '''label''': '''cat''', '''box''': {'''xmin''': 324, '''ymin''': 20, '''xmax''': 640, '''ymax''': 373}},
             {'''score''': 0.2_77, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 177, '''ymax''': 115}},
             {'''score''': 0.25_37, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 315, '''ymax''': 472}},
             {'''score''': 0.14_74, '''label''': '''remote''', '''box''': {'''xmin''': 335, '''ymin''': 74, '''xmax''': 371, '''ymax''': 187}},
             {'''score''': 0.12_08, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 642, '''ymax''': 476}},
         ]    ,     )

     lowerCAmelCase_			=      object_detector(
         [
             {
                 '''image''': '''http://images.cocodataset.org/val2017/000000039769.jpg''',
                 '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
             },
             {
                 '''image''': '''http://images.cocodataset.org/val2017/000000039769.jpg''',
                 '''candidate_labels''': ['''cat''', '''remote''', '''couch'''],
             },
         ]    ,     )
     self.assertEqual(
         nested_simplify(_lowercase    ,     decimals=4 )    ,     [
             [
                 {'''score''': 0.28_68, '''label''': '''cat''', '''box''': {'''xmin''': 324, '''ymin''': 20, '''xmax''': 640, '''ymax''': 373}},
                 {'''score''': 0.2_77, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 177, '''ymax''': 115}},
                 {'''score''': 0.25_37, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 315, '''ymax''': 472}},
                 {'''score''': 0.14_74, '''label''': '''remote''', '''box''': {'''xmin''': 335, '''ymin''': 74, '''xmax''': 371, '''ymax''': 187}},
                 {'''score''': 0.12_08, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 642, '''ymax''': 476}},
             ],
             [
                 {'''score''': 0.28_68, '''label''': '''cat''', '''box''': {'''xmin''': 324, '''ymin''': 20, '''xmax''': 640, '''ymax''': 373}},
                 {'''score''': 0.2_77, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 177, '''ymax''': 115}},
                 {'''score''': 0.25_37, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 315, '''ymax''': 472}},
                 {'''score''': 0.14_74, '''label''': '''remote''', '''box''': {'''xmin''': 335, '''ymin''': 74, '''xmax''': 371, '''ymax''': 187}},
                 {'''score''': 0.12_08, '''label''': '''couch''', '''box''': {'''xmin''': 4, '''ymin''': 0, '''xmax''': 642, '''ymax''': 476}},
             ],
         ]    ,     )





  @require_tf
  @unittest.skip('''Zero Shot Object Detection not implemented in TF''' )
  def 						UpperCAmelCase_	(	self ):
     pass





  @require_torch
  @slow
  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      0.2
     lowerCAmelCase_			=      pipeline('''zero-shot-object-detection''' )

     lowerCAmelCase_			=      object_detector(
         '''http://images.cocodataset.org/val2017/000000039769.jpg'''    ,     candidate_labels=['''cat''', '''remote''', '''couch''']    ,     threshold=_lowercase    ,     )
     self.assertEqual(
         nested_simplify(_lowercase    ,     decimals=4 )    ,     [
             {'''score''': 0.28_68, '''label''': '''cat''', '''box''': {'''xmin''': 324, '''ymin''': 20, '''xmax''': 640, '''ymax''': 373}},
             {'''score''': 0.2_77, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 177, '''ymax''': 115}},
             {'''score''': 0.25_37, '''label''': '''cat''', '''box''': {'''xmin''': 1, '''ymin''': 55, '''xmax''': 315, '''ymax''': 472}},
         ]    ,     )







  @require_torch
  @slow
  def 						UpperCAmelCase_	(	self ):
     lowerCAmelCase_			=      2
     lowerCAmelCase_			=      pipeline('''zero-shot-object-detection''' )

     lowerCAmelCase_			=      object_detector(
         '''http://images.cocodataset.org/val2017/000000039769.jpg'''    ,     candidate_labels=['''cat''', '''remote''', '''couch''']    ,     top_k=_lowercase    ,     )
     self.assertEqual(
         nested_simplify(_lowercase    ,     decimals=4 )    ,     [
             {'''score''': 0.28_68, '''label''': '''cat''', '''box''': {'''xmin''': 324, '''ymin''': 20, '''xmax''': 640, '''ymax''': 373}},
             {'''score''': 0.2_77, '''label''': '''remote''', '''box''': {'''xmin''': 40, '''ymin''': 72, '''xmax''': 177, '''ymax''': 115}},
         ]    ,     )











'''simple docstring'''
import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict





@pytest.mark.parametrize(
    'split_dict'       ,[
        SplitDict(),
        SplitDict({'train': SplitInfo(name='train'       ,num_bytes=1337       ,num_examples=42       ,dataset_name='my_dataset'     )}     ),
        SplitDict({'train': SplitInfo(name='train'       ,num_bytes=1337       ,num_examples=42     )}     ),
        SplitDict({'train': SplitInfo()}     ),
    ]       ,)
def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		List[str]:
			A_									= split_dict._to_yaml_list()
			assert len(SCREAMING_SNAKE_CASE_     ) == len(SCREAMING_SNAKE_CASE_     )
			A_									= SplitDict._from_yaml_list(SCREAMING_SNAKE_CASE_     )
			for split_name, split_info in split_dict.items():
						# dataset_name field is deprecated, and is therefore not part of the YAML dump
						A_									= None
						# the split name of split_dict takes over the name of the split info object
						A_									= split_name
			assert split_dict == reloaded






@pytest.mark.parametrize(
    'split_info'       ,[SplitInfo(), SplitInfo(dataset_name=SCREAMING_SNAKE_CASE_     ), SplitInfo(dataset_name='my_dataset'     )]     )
def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_     )		->		Optional[Any]:
			# For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
			# field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
			A_									= asdict(SplitDict({'train': split_info}     )     )
			assert "dataset_name" in split_dict_asdict["train"]
			assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name




