





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 SCREAMING_SNAKE_CASE_ :





											"""simple docstring"""


											@staticmethod
											def 					__magic_name__ ( *_lowerCAmelCase	,  **_lowerCAmelCase	):
																pass

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





					"""simple docstring"""


					A__				 =    MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING





					def 					__magic_name__ ( 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 					__magic_name__ ( self	,  _lowerCAmelCase	,  _lowerCAmelCase	):
										lowerCamelCase__       =       object_detector(examples[0]	,  threshold=0.0	)

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





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





					@require_torch
					def 					__magic_name__ ( 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(_lowerCAmelCase	,  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}},
										    ]	,  )

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

										self.assertEqual(
										    nested_simplify(_lowerCAmelCase	,  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 					__magic_name__ ( 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(_lowerCAmelCase	,  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}},
										    ]	,  )

										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(_lowerCAmelCase	,  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 					__magic_name__ ( self	):
										pass





					@require_torch
					@slow
					def 					__magic_name__ ( 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=_lowerCAmelCase	,  )
										self.assertEqual(
										    nested_simplify(_lowerCAmelCase	,  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 					__magic_name__ ( 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=_lowerCAmelCase	,  )
										self.assertEqual(
										    nested_simplify(_lowerCAmelCase	,  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}},
										    ]	,  )








from __future__ import annotations

class SCREAMING_SNAKE_CASE_ :





					"""simple docstring"""


					def __init__( self	,  _lowerCAmelCase	,  _lowerCAmelCase	):
										lowerCamelCase__    ,		lowerCamelCase__       =       text, pattern
										lowerCamelCase__    ,		lowerCamelCase__       =       len(_lowerCAmelCase	), len(_lowerCAmelCase	)





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):

										for i in range(self.patLen - 1	,  -1	,  -1	):
															if char == self.pattern[i]:
																				return i
										return -1





					def 					__magic_name__ ( self	,  _lowerCAmelCase	):

										for i in range(self.patLen - 1	,  -1	,  -1	):
															if self.pattern[i] != self.text[current_pos + i]:
																				return current_pos + i
										return -1






					def 					__magic_name__ ( self	):
										# searches pattern in text and returns index positions
										lowerCamelCase__       =       []
										for i in range(self.textLen - self.patLen + 1	):
															lowerCamelCase__       =       self.mismatch_in_text(_lowerCAmelCase	)
															if mismatch_index == -1:
																				positions.append(_lowerCAmelCase	)
															else:
																				lowerCamelCase__       =       self.match_in_pattern(self.text[mismatch_index]	)
																				lowerCamelCase__       =       (
																				    mismatch_index - match_index
																				)  # shifting index lgtm [py/multiple-definition]
										return positions

A_												=     "ABAABA"
A_												=     "AB"
A_												=     BoyerMooreSearch(text, pattern)
A_												=     bms.bad_character_heuristic()

if len(positions) == 0:
						print("No match found")
else:
						print("Pattern found in following positions: ")
						print(positions)

