





'''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__   (*A__      :	Optional[Any]							,			**A__      :	List[str]				)					-> str:
									pass

@is_pipeline_test
@require_vision
@require_torch
class       UpperCAmelCase (						unittest.TestCase  ):
		UpperCAmelCase					:	List[str] 			=		MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING




		def 				UpperCAmelCase__   (self      :	Tuple							,			A__      :	Dict							,			A__      :	Optional[int]							,			A__      :	int				)					-> Optional[int]:
						lowercase         = pipeline(
						    "zero-shot-object-detection"							,			model="hf-internal-testing/tiny-random-owlvit-object-detection"				)

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




		def 				UpperCAmelCase__   (self      :	Union[str, Any]							,			A__      :	Optional[int]							,			A__      :	int				)					-> Dict:
						lowercase         = object_detector(examples[0]							,			threshold=0.0				)

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




		@require_tf
		@unittest.skip("Zero Shot Object Detection not implemented in TF"				)
		def 				UpperCAmelCase__   (self      :	Union[str, Any]				)					-> Tuple:
						pass




		@require_torch
		def 				UpperCAmelCase__   (self      :	Tuple				)					-> List[Any]:
						lowercase         = pipeline(
						    "zero-shot-object-detection"							,			model="hf-internal-testing/tiny-random-owlvit-object-detection"				)

						lowercase         = object_detector(
						    "./tests/fixtures/tests_samples/COCO/000000039769.png"							,			candidate_labels=["cat", "remote", "couch"]							,			threshold=0.6_4							,			)

						self.assertEqual(
						    nested_simplify(A__							,			decimals=4				)							,			[
						        {"score": 0.7_2_3_5, "label": "cat", "box": {"xmin": 2_0_4, "ymin": 1_6_7, "xmax": 2_3_2, "ymax": 1_9_0}},
						        {"score": 0.7_2_1_8, "label": "remote", "box": {"xmin": 2_0_4, "ymin": 1_6_7, "xmax": 2_3_2, "ymax": 1_9_0}},
						        {"score": 0.7_1_8_4, "label": "couch", "box": {"xmin": 2_0_4, "ymin": 1_6_7, "xmax": 2_3_2, "ymax": 1_9_0}},
						        {"score": 0.6_7_4_8, "label": "remote", "box": {"xmin": 5_7_1, "ymin": 8_3, "xmax": 5_9_8, "ymax": 1_0_3}},
						        {"score": 0.6_6_5_6, "label": "cat", "box": {"xmin": 5_7_1, "ymin": 8_3, "xmax": 5_9_8, "ymax": 1_0_3}},
						        {"score": 0.6_6_1_4, "label": "couch", "box": {"xmin": 5_7_1, "ymin": 8_3, "xmax": 5_9_8, "ymax": 1_0_3}},
						        {"score": 0.6_4_5_6, "label": "remote", "box": {"xmin": 4_9_4, "ymin": 1_0_5, "xmax": 5_2_1, "ymax": 1_2_7}},
						        {"score": 0.6_4_2, "label": "remote", "box": {"xmin": 6_7, "ymin": 2_7_4, "xmax": 9_3, "ymax": 2_9_7}},
						        {"score": 0.6_4_1_9, "label": "cat", "box": {"xmin": 4_9_4, "ymin": 1_0_5, "xmax": 5_2_1, "ymax": 1_2_7}},
						    ]							,			)

						lowercase         = object_detector(
						    [
						        {
						            "image": "./tests/fixtures/tests_samples/COCO/000000039769.png",
						            "candidate_labels": ["cat", "remote", "couch"],
						        }
						    ]							,			threshold=0.6_4							,			)

						self.assertEqual(
						    nested_simplify(A__							,			decimals=4				)							,			[
						        [
						            {"score": 0.7_2_3_5, "label": "cat", "box": {"xmin": 2_0_4, "ymin": 1_6_7, "xmax": 2_3_2, "ymax": 1_9_0}},
						            {"score": 0.7_2_1_8, "label": "remote", "box": {"xmin": 2_0_4, "ymin": 1_6_7, "xmax": 2_3_2, "ymax": 1_9_0}},
						            {"score": 0.7_1_8_4, "label": "couch", "box": {"xmin": 2_0_4, "ymin": 1_6_7, "xmax": 2_3_2, "ymax": 1_9_0}},
						            {"score": 0.6_7_4_8, "label": "remote", "box": {"xmin": 5_7_1, "ymin": 8_3, "xmax": 5_9_8, "ymax": 1_0_3}},
						            {"score": 0.6_6_5_6, "label": "cat", "box": {"xmin": 5_7_1, "ymin": 8_3, "xmax": 5_9_8, "ymax": 1_0_3}},
						            {"score": 0.6_6_1_4, "label": "couch", "box": {"xmin": 5_7_1, "ymin": 8_3, "xmax": 5_9_8, "ymax": 1_0_3}},
						            {"score": 0.6_4_5_6, "label": "remote", "box": {"xmin": 4_9_4, "ymin": 1_0_5, "xmax": 5_2_1, "ymax": 1_2_7}},
						            {"score": 0.6_4_2, "label": "remote", "box": {"xmin": 6_7, "ymin": 2_7_4, "xmax": 9_3, "ymax": 2_9_7}},
						            {"score": 0.6_4_1_9, "label": "cat", "box": {"xmin": 4_9_4, "ymin": 1_0_5, "xmax": 5_2_1, "ymax": 1_2_7}},
						        ]
						    ]							,			)




		@require_torch
		@slow
		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> List[str]:
						lowercase         = pipeline("zero-shot-object-detection"				)

						lowercase         = object_detector(
						    "http://images.cocodataset.org/val2017/000000039769.jpg"							,			candidate_labels=["cat", "remote", "couch"]							,			)
						self.assertEqual(
						    nested_simplify(A__							,			decimals=4				)							,			[
						        {"score": 0.2_8_6_8, "label": "cat", "box": {"xmin": 3_2_4, "ymin": 2_0, "xmax": 6_4_0, "ymax": 3_7_3}},
						        {"score": 0.2_7_7, "label": "remote", "box": {"xmin": 4_0, "ymin": 7_2, "xmax": 1_7_7, "ymax": 1_1_5}},
						        {"score": 0.2_5_3_7, "label": "cat", "box": {"xmin": 1, "ymin": 5_5, "xmax": 3_1_5, "ymax": 4_7_2}},
						        {"score": 0.1_4_7_4, "label": "remote", "box": {"xmin": 3_3_5, "ymin": 7_4, "xmax": 3_7_1, "ymax": 1_8_7}},
						        {"score": 0.1_2_0_8, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 6_4_2, "ymax": 4_7_6}},
						    ]							,			)

						lowercase         = 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(A__							,			decimals=4				)							,			[
						        [
						            {"score": 0.2_8_6_8, "label": "cat", "box": {"xmin": 3_2_4, "ymin": 2_0, "xmax": 6_4_0, "ymax": 3_7_3}},
						            {"score": 0.2_7_7, "label": "remote", "box": {"xmin": 4_0, "ymin": 7_2, "xmax": 1_7_7, "ymax": 1_1_5}},
						            {"score": 0.2_5_3_7, "label": "cat", "box": {"xmin": 1, "ymin": 5_5, "xmax": 3_1_5, "ymax": 4_7_2}},
						            {"score": 0.1_4_7_4, "label": "remote", "box": {"xmin": 3_3_5, "ymin": 7_4, "xmax": 3_7_1, "ymax": 1_8_7}},
						            {"score": 0.1_2_0_8, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 6_4_2, "ymax": 4_7_6}},
						        ],
						        [
						            {"score": 0.2_8_6_8, "label": "cat", "box": {"xmin": 3_2_4, "ymin": 2_0, "xmax": 6_4_0, "ymax": 3_7_3}},
						            {"score": 0.2_7_7, "label": "remote", "box": {"xmin": 4_0, "ymin": 7_2, "xmax": 1_7_7, "ymax": 1_1_5}},
						            {"score": 0.2_5_3_7, "label": "cat", "box": {"xmin": 1, "ymin": 5_5, "xmax": 3_1_5, "ymax": 4_7_2}},
						            {"score": 0.1_4_7_4, "label": "remote", "box": {"xmin": 3_3_5, "ymin": 7_4, "xmax": 3_7_1, "ymax": 1_8_7}},
						            {"score": 0.1_2_0_8, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 6_4_2, "ymax": 4_7_6}},
						        ],
						    ]							,			)




		@require_tf
		@unittest.skip("Zero Shot Object Detection not implemented in TF"				)
		def 				UpperCAmelCase__   (self      :	List[str]				)					-> int:
						pass




		@require_torch
		@slow
		def 				UpperCAmelCase__   (self      :	Optional[Any]				)					-> Optional[Any]:
						lowercase         = 0.2
						lowercase         = pipeline("zero-shot-object-detection"				)

						lowercase         = object_detector(
						    "http://images.cocodataset.org/val2017/000000039769.jpg"							,			candidate_labels=["cat", "remote", "couch"]							,			threshold=A__							,			)
						self.assertEqual(
						    nested_simplify(A__							,			decimals=4				)							,			[
						        {"score": 0.2_8_6_8, "label": "cat", "box": {"xmin": 3_2_4, "ymin": 2_0, "xmax": 6_4_0, "ymax": 3_7_3}},
						        {"score": 0.2_7_7, "label": "remote", "box": {"xmin": 4_0, "ymin": 7_2, "xmax": 1_7_7, "ymax": 1_1_5}},
						        {"score": 0.2_5_3_7, "label": "cat", "box": {"xmin": 1, "ymin": 5_5, "xmax": 3_1_5, "ymax": 4_7_2}},
						    ]							,			)





		@require_torch
		@slow
		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> Tuple:
						lowercase         = 2
						lowercase         = pipeline("zero-shot-object-detection"				)

						lowercase         = object_detector(
						    "http://images.cocodataset.org/val2017/000000039769.jpg"							,			candidate_labels=["cat", "remote", "couch"]							,			top_k=A__							,			)
						self.assertEqual(
						    nested_simplify(A__							,			decimals=4				)							,			[
						        {"score": 0.2_8_6_8, "label": "cat", "box": {"xmin": 3_2_4, "ymin": 2_0, "xmax": 6_4_0, "ymax": 3_7_3}},
						        {"score": 0.2_7_7, "label": "remote", "box": {"xmin": 4_0, "ymin": 7_2, "xmax": 1_7_7, "ymax": 1_1_5}},
						    ]							,			)











'''simple docstring'''

import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate

@dataclass(frozen=_lowercase  )
class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	str 			=		field(default='''image-classification'''			,       metadata={'''include_in_asdict_even_if_is_default''': True}  )
		UpperCAmelCase					:	ClassVar[Features] 			=		Features({'''image''': Image()}  )
		UpperCAmelCase					:	ClassVar[Features] 			=		Features({'''labels''': ClassLabel}  )
		UpperCAmelCase					:	str 			=		"image"
		UpperCAmelCase					:	str 			=		"labels"




		def 				UpperCAmelCase__   (self      :	List[str]							,			A__      :	Union[str, Any]				)					-> Union[str, Any]:
						if self.label_column not in features:
										raise ValueError(f'Column {self.label_column} is not present in features.'				)
						if not isinstance(features[self.label_column]							,			A__				):
										raise ValueError(f'Column {self.label_column} is not a ClassLabel.'				)
						lowercase         = copy.deepcopy(self				)
						lowercase         = self.label_schema.copy()
						lowercase         = features[self.label_column]
						lowercase         = label_schema
						return task_template





		@property
		def 				UpperCAmelCase__   (self      :	List[Any]				)					-> Dict[str, str]:
						return {
						    self.image_column: "image",
						    self.label_column: "labels",
						}




