



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  __snake_case      :







								'''simple docstring'''






								@staticmethod
								def _a      (							*a_  ,  **a_		):
												pass

@is_pipeline_test
@require_vision
@require_torch
class  __snake_case      (   unittest.TestCase):







							'''simple docstring'''






							UpperCamelCase__				:      str         =					MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING


							def _a      (							self  ,  a_  ,  a_  ,  a_		):
											a__				      =		pipeline(
											    """zero-shot-object-detection"""  ,  model="""hf-internal-testing/tiny-random-owlvit-object-detection"""		)

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


							def _a      (							self  ,  a_  ,  a_		):
											a__				      =		object_detector(examples[0]  ,  threshold=0.0		)

											a__				      =		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 _a      (							self		):
											pass


							@require_torch
							def _a      (							self		):
											a__				      =		pipeline(
											    """zero-shot-object-detection"""  ,  model="""hf-internal-testing/tiny-random-owlvit-object-detection"""		)

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

											self.assertEqual(
											    nested_simplify(a_  ,  decimals=4		)  ,  [
											        {"""score""": 0.7_235, """label""": """cat""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
											        {"""score""": 0.7_218, """label""": """remote""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
											        {"""score""": 0.7_184, """label""": """couch""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
											        {"""score""": 0.6_748, """label""": """remote""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
											        {"""score""": 0.6_656, """label""": """cat""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
											        {"""score""": 0.6_614, """label""": """couch""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
											        {"""score""": 0.6_456, """label""": """remote""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
											        {"""score""": 0.642, """label""": """remote""", """box""": {"""xmin""": 67, """ymin""": 274, """xmax""": 93, """ymax""": 297}},
											        {"""score""": 0.6_419, """label""": """cat""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
											    ]  ,  )

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

											self.assertEqual(
											    nested_simplify(a_  ,  decimals=4		)  ,  [
											        [
											            {"""score""": 0.7_235, """label""": """cat""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
											            {"""score""": 0.7_218, """label""": """remote""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
											            {"""score""": 0.7_184, """label""": """couch""", """box""": {"""xmin""": 204, """ymin""": 167, """xmax""": 232, """ymax""": 190}},
											            {"""score""": 0.6_748, """label""": """remote""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
											            {"""score""": 0.6_656, """label""": """cat""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
											            {"""score""": 0.6_614, """label""": """couch""", """box""": {"""xmin""": 571, """ymin""": 83, """xmax""": 598, """ymax""": 103}},
											            {"""score""": 0.6_456, """label""": """remote""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
											            {"""score""": 0.642, """label""": """remote""", """box""": {"""xmin""": 67, """ymin""": 274, """xmax""": 93, """ymax""": 297}},
											            {"""score""": 0.6_419, """label""": """cat""", """box""": {"""xmin""": 494, """ymin""": 105, """xmax""": 521, """ymax""": 127}},
											        ]
											    ]  ,  )


							@require_torch
							@slow
							def _a      (							self		):
											a__				      =		pipeline("""zero-shot-object-detection"""		)

											a__				      =		object_detector(
											    """http://images.cocodataset.org/val2017/000000039769.jpg"""  ,  candidate_labels=["""cat""", """remote""", """couch"""]  ,  )
											self.assertEqual(
											    nested_simplify(a_  ,  decimals=4		)  ,  [
											        {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
											        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
											        {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
											        {"""score""": 0.1_474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
											        {"""score""": 0.1_208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
											    ]  ,  )

											a__				      =		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_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
											            {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
											            {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
											            {"""score""": 0.1_474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
											            {"""score""": 0.1_208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
											        ],
											        [
											            {"""score""": 0.2_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
											            {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
											            {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
											            {"""score""": 0.1_474, """label""": """remote""", """box""": {"""xmin""": 335, """ymin""": 74, """xmax""": 371, """ymax""": 187}},
											            {"""score""": 0.1_208, """label""": """couch""", """box""": {"""xmin""": 4, """ymin""": 0, """xmax""": 642, """ymax""": 476}},
											        ],
											    ]  ,  )


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


							@require_torch
							@slow
							def _a      (							self		):
											a__				      =		0.2
											a__				      =		pipeline("""zero-shot-object-detection"""		)

											a__				      =		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_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
											        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
											        {"""score""": 0.2_537, """label""": """cat""", """box""": {"""xmin""": 1, """ymin""": 55, """xmax""": 315, """ymax""": 472}},
											    ]  ,  )







							@require_torch
							@slow
							def _a      (							self		):
											a__				      =		2
											a__				      =		pipeline("""zero-shot-object-detection"""		)

											a__				      =		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_868, """label""": """cat""", """box""": {"""xmin""": 324, """ymin""": 20, """xmax""": 640, """ymax""": 373}},
											        {"""score""": 0.277, """label""": """remote""", """box""": {"""xmin""": 40, """ymin""": 72, """xmax""": 177, """ymax""": 115}},
											    ]  ,  )






import os
from datetime import datetime as dt

from github import Github


UpperCAmelCase							 =					[
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """enhancement""",
    """new pipeline/model""",
    """new scheduler""",
    """wip""",
]

def 			A_      (	):

				"""simple docstring"""
				a__				      =		Github(os.environ["""GITHUB_TOKEN"""]		)
				a__				      =		g.get_repo("""huggingface/diffusers"""		)
				a__				      =		repo.get_issues(state="""open"""		)

				for issue in open_issues:
								a__				      =		sorted(issue.get_comments() ,		key=lambda __a		: i.created_at ,		reverse=__a		)
								a__				      =		comments[0] if len(__a		) > 0 else None
								if (
								    last_comment is not None
								    and last_comment.user.login == "github-actions[bot]"
								    and (dt.utcnow() - issue.updated_at).days > 7
								    and (dt.utcnow() - issue.created_at).days >= 30
								    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()		)
								):
												# Closes the issue after 7 days of inactivity since the Stalebot notification.
												issue.edit(state="""closed"""		)
								elif (
								    "stale" in issue.get_labels()
								    and last_comment is not None
								    and last_comment.user.login != "github-actions[bot]"
								):
												# Opens the issue if someone other than Stalebot commented.
												issue.edit(state="""open"""		)
												issue.remove_from_labels("""stale"""		)
								elif (
								    (dt.utcnow() - issue.updated_at).days > 23
								    and (dt.utcnow() - issue.created_at).days >= 30
								    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()		)
								):
												# Post a Stalebot notification after 23 days of inactivity.
												issue.create_comment(
												    """This issue has been automatically marked as stale because it has not had """
												    """recent activity. If you think this still needs to be addressed """
												    """please comment on this thread.\n\nPlease note that issues that do not follow the """
												    """[contributing guidelines](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md) """
												    """are likely to be ignored."""		)
												issue.add_to_labels("""stale"""		)


if __name__ == "__main__":
	main()

