
import unittest

from transformers import (
    MODEL_FOR_OBJECT_DETECTION_MAPPING,
    AutoFeatureExtractor,
    AutoModelForObjectDetection,
    ObjectDetectionPipeline,
    is_vision_available,
    pipeline,
)
from transformers.testing_utils import (
    is_pipeline_test,
    nested_simplify,
    require_pytesseract,
    require_tf,
    require_timm,
    require_torch,
    require_vision,
    slow,
)

from .test_pipelines_common import ANY


if is_vision_available():
				from PIL import Image
else:







				class        lowerCAmelCase__      :

										@staticmethod
										def  A_				(			*a       ,							**a				)					->      Union[str, Any]:


												'''simple docstring'''

												pass







@is_pipeline_test
@require_vision
@require_timm
@require_torch
class        lowerCAmelCase__      (   unittest.TestCase	):
						UpperCamelCase_							: int	=		MODEL_FOR_OBJECT_DETECTION_MAPPING

						def  A_				(			self       ,							a       ,							a       ,							a				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	ObjectDetectionPipeline(model=a       ,							image_processor=a				)
								return object_detector, ["./tests/fixtures/tests_samples/COCO/000000039769.png"]

						def  A_				(			self       ,							a       ,							a				)					->      Any:


								'''simple docstring'''

								_UpperCamelCase						    =	object_detector("""./tests/fixtures/tests_samples/COCO/000000039769.png"""       ,							threshold=0.0				)

								self.assertGreater(len(a				)       ,							0				)
								for detected_object in outputs:
										self.assertEqual(
										    a       ,							{
										        """score""": ANY(a				),
										        """label""": ANY(a				),
										        """box""": {"""xmin""": ANY(a				), """ymin""": ANY(a				), """xmax""": ANY(a				), """ymax""": ANY(a				)},
										    }       ,							)

								import datasets

								_UpperCamelCase						    =	datasets.load_dataset("""hf-internal-testing/fixtures_image_utils"""       ,							"""image"""       ,							split="""test"""				)

								_UpperCamelCase						    =	[
								    Image.open("""./tests/fixtures/tests_samples/COCO/000000039769.png"""				),
								    """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    # RGBA
								    dataset[0]["""file"""],
								    # LA
								    dataset[1]["""file"""],
								    # L
								    dataset[2]["""file"""],
								]
								_UpperCamelCase						    =	object_detector(a       ,							threshold=0.0				)

								self.assertEqual(len(a				)       ,							len(a				)				)
								for outputs in batch_outputs:
										self.assertGreater(len(a				)       ,							0				)
										for detected_object in outputs:
												self.assertEqual(
												    a       ,							{
												        """score""": ANY(a				),
												        """label""": ANY(a				),
												        """box""": {"""xmin""": ANY(a				), """ymin""": ANY(a				), """xmax""": ANY(a				), """ymax""": ANY(a				)},
												    }       ,							)

						@require_tf
						@unittest.skip("""Object detection not implemented in TF"""				)
						def  A_				(			self				)					->      Optional[Any]:


								'''simple docstring'''

								pass

						@require_torch
						def  A_				(			self				)					->      Optional[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	"""hf-internal-testing/tiny-detr-mobilenetsv3"""

								_UpperCamelCase						    =	AutoModelForObjectDetection.from_pretrained(a				)
								_UpperCamelCase						    =	AutoFeatureExtractor.from_pretrained(a				)
								_UpperCamelCase						    =	ObjectDetectionPipeline(model=a       ,							feature_extractor=a				)

								_UpperCamelCase						    =	object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""       ,							threshold=0.0				)

								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        {"""score""": 0.3376, """label""": """LABEL_0""", """box""": {"""xmin""": 1_59, """ymin""": 1_20, """xmax""": 4_80, """ymax""": 3_59}},
								        {"""score""": 0.3376, """label""": """LABEL_0""", """box""": {"""xmin""": 1_59, """ymin""": 1_20, """xmax""": 4_80, """ymax""": 3_59}},
								    ]       ,							)

								_UpperCamelCase						    =	object_detector(
								    [
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    ]       ,							threshold=0.0       ,							)

								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        [
								            {"""score""": 0.3376, """label""": """LABEL_0""", """box""": {"""xmin""": 1_59, """ymin""": 1_20, """xmax""": 4_80, """ymax""": 3_59}},
								            {"""score""": 0.3376, """label""": """LABEL_0""", """box""": {"""xmin""": 1_59, """ymin""": 1_20, """xmax""": 4_80, """ymax""": 3_59}},
								        ],
								        [
								            {"""score""": 0.3376, """label""": """LABEL_0""", """box""": {"""xmin""": 1_59, """ymin""": 1_20, """xmax""": 4_80, """ymax""": 3_59}},
								            {"""score""": 0.3376, """label""": """LABEL_0""", """box""": {"""xmin""": 1_59, """ymin""": 1_20, """xmax""": 4_80, """ymax""": 3_59}},
								        ],
								    ]       ,							)

						@require_torch
						@slow
						def  A_				(			self				)					->      Union[str, Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	"""facebook/detr-resnet-50"""

								_UpperCamelCase						    =	AutoModelForObjectDetection.from_pretrained(a				)
								_UpperCamelCase						    =	AutoFeatureExtractor.from_pretrained(a				)
								_UpperCamelCase						    =	ObjectDetectionPipeline(model=a       ,							feature_extractor=a				)

								_UpperCamelCase						    =	object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""				)
								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        {"""score""": 0.9982, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 1_75, """ymax""": 1_17}},
								        {"""score""": 0.9960, """label""": """remote""", """box""": {"""xmin""": 3_33, """ymin""": 72, """xmax""": 3_68, """ymax""": 1_87}},
								        {"""score""": 0.9955, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_39, """ymax""": 4_73}},
								        {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								        {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								    ]       ,							)

								_UpperCamelCase						    =	object_detector(
								    [
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    ]				)
								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        [
								            {"""score""": 0.9982, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 1_75, """ymax""": 1_17}},
								            {"""score""": 0.9960, """label""": """remote""", """box""": {"""xmin""": 3_33, """ymin""": 72, """xmax""": 3_68, """ymax""": 1_87}},
								            {"""score""": 0.9955, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_39, """ymax""": 4_73}},
								            {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								            {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								        ],
								        [
								            {"""score""": 0.9982, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 1_75, """ymax""": 1_17}},
								            {"""score""": 0.9960, """label""": """remote""", """box""": {"""xmin""": 3_33, """ymin""": 72, """xmax""": 3_68, """ymax""": 1_87}},
								            {"""score""": 0.9955, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_39, """ymax""": 4_73}},
								            {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								            {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								        ],
								    ]       ,							)

						@require_torch
						@slow
						def  A_				(			self				)					->      Any:


								'''simple docstring'''

								_UpperCamelCase						    =	"""facebook/detr-resnet-50"""

								_UpperCamelCase						    =	pipeline("""object-detection"""       ,							model=a				)

								_UpperCamelCase						    =	object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""				)
								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        {"""score""": 0.9982, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 1_75, """ymax""": 1_17}},
								        {"""score""": 0.9960, """label""": """remote""", """box""": {"""xmin""": 3_33, """ymin""": 72, """xmax""": 3_68, """ymax""": 1_87}},
								        {"""score""": 0.9955, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_39, """ymax""": 4_73}},
								        {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								        {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								    ]       ,							)

								_UpperCamelCase						    =	object_detector(
								    [
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								        """http://images.cocodataset.org/val2017/000000039769.jpg""",
								    ]				)
								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        [
								            {"""score""": 0.9982, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 1_75, """ymax""": 1_17}},
								            {"""score""": 0.9960, """label""": """remote""", """box""": {"""xmin""": 3_33, """ymin""": 72, """xmax""": 3_68, """ymax""": 1_87}},
								            {"""score""": 0.9955, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_39, """ymax""": 4_73}},
								            {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								            {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								        ],
								        [
								            {"""score""": 0.9982, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 70, """xmax""": 1_75, """ymax""": 1_17}},
								            {"""score""": 0.9960, """label""": """remote""", """box""": {"""xmin""": 3_33, """ymin""": 72, """xmax""": 3_68, """ymax""": 1_87}},
								            {"""score""": 0.9955, """label""": """couch""", """box""": {"""xmin""": 0, """ymin""": 1, """xmax""": 6_39, """ymax""": 4_73}},
								            {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								            {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								        ],
								    ]       ,							)

						@require_torch
						@slow
						def  A_				(			self				)					->      List[Any]:


								'''simple docstring'''

								_UpperCamelCase						    =	0.9985
								_UpperCamelCase						    =	"""facebook/detr-resnet-50"""

								_UpperCamelCase						    =	pipeline("""object-detection"""       ,							model=a				)

								_UpperCamelCase						    =	object_detector("""http://images.cocodataset.org/val2017/000000039769.jpg"""       ,							threshold=a				)
								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        {"""score""": 0.9988, """label""": """cat""", """box""": {"""xmin""": 13, """ymin""": 52, """xmax""": 3_14, """ymax""": 4_70}},
								        {"""score""": 0.9987, """label""": """cat""", """box""": {"""xmin""": 3_45, """ymin""": 23, """xmax""": 6_40, """ymax""": 3_68}},
								    ]       ,							)







						@require_torch
						@require_pytesseract
						@slow
						def  A_				(			self				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	"""Narsil/layoutlmv3-finetuned-funsd"""
								_UpperCamelCase						    =	0.9993

								_UpperCamelCase						    =	pipeline("""object-detection"""       ,							model=a       ,							threshold=a				)

								_UpperCamelCase						    =	object_detector(
								    """https://huggingface.co/spaces/impira/docquery/resolve/2359223c1837a7587402bda0f2643382a6eefeab/invoice.png"""				)
								self.assertEqual(
								    nested_simplify(a       ,							decimals=4				)       ,							[
								        {"""score""": 0.9993, """label""": """I-ANSWER""", """box""": {"""xmin""": 2_94, """ymin""": 2_54, """xmax""": 3_43, """ymax""": 2_64}},
								        {"""score""": 0.9993, """label""": """I-ANSWER""", """box""": {"""xmin""": 2_94, """ymin""": 2_54, """xmax""": 3_43, """ymax""": 2_64}},
								    ]       ,							)





lowerCamelCase__	=							[
    "DownloadConfig",
    "DownloadManager",
    "DownloadMode",
    "StreamingDownloadManager",
]

from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager



