


"""simple docstring"""







# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser
def  a__      (    ):


  '''simple docstring'''







  lowerCAmelCase					:					List[Any]								=							ArgumentParser("Accelerate CLI tool"    ,				usage="accelerate <command> [<args>]"    ,				allow_abbrev=SCREAMING_SNAKE_CASE    )
  lowerCAmelCase					:					Any								=							parser.add_subparsers(help="accelerate command helpers"    )

  # Register commands
  get_config_parser(subparsers=SCREAMING_SNAKE_CASE    )
  env_command_parser(subparsers=SCREAMING_SNAKE_CASE    )
  launch_command_parser(subparsers=SCREAMING_SNAKE_CASE    )
  tpu_command_parser(subparsers=SCREAMING_SNAKE_CASE    )
  test_command_parser(subparsers=SCREAMING_SNAKE_CASE    )

  # Let's go
  lowerCAmelCase					:					Union[str, Any]								=							parser.parse_args()

  if not hasattr(SCREAMING_SNAKE_CASE    ,				"func"    ):
    parser.print_help()
    exit(1    )

  # Run
  args.func(SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
     main()









"""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 				SCREAMING_SNAKE_CASE__    :
            """simple docstring"""


            @staticmethod
            def 	lowercase__							(						*snake_case__		,					**snake_case__						):






              """simple docstring"""





              pass


@is_pipeline_test
@require_vision
@require_torch
class 				SCREAMING_SNAKE_CASE__    (		unittest.TestCase    ):
       """simple docstring"""


       a  :    Optional[Any]       =MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING

       def 	lowercase__							(						self		,					snake_case__		,					snake_case__		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					str								=							pipeline(
             "zero-shot-object-detection"		,					model="hf-internal-testing/tiny-random-owlvit-object-detection"						)

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

       def 	lowercase__							(						self		,					snake_case__		,					snake_case__						):






         """simple docstring"""





         lowerCAmelCase					:					Optional[Any]								=							object_detector(examples[0]		,					threshold=0.0						)

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

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






         """simple docstring"""





         pass

       @require_torch
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					str								=							pipeline(
             "zero-shot-object-detection"		,					model="hf-internal-testing/tiny-random-owlvit-object-detection"						)

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

         self.assertEqual(
             nested_simplify(snake_case__		,					decimals=4						)		,					[
                 {"score": 0.7235, "label": "cat", "box": {"xmin": 204, "ymin": 167, "xmax": 232, "ymax": 190}},
                 {"score": 0.7218, "label": "remote", "box": {"xmin": 204, "ymin": 167, "xmax": 232, "ymax": 190}},
                 {"score": 0.7184, "label": "couch", "box": {"xmin": 204, "ymin": 167, "xmax": 232, "ymax": 190}},
                 {"score": 0.6748, "label": "remote", "box": {"xmin": 571, "ymin": 83, "xmax": 598, "ymax": 103}},
                 {"score": 0.6656, "label": "cat", "box": {"xmin": 571, "ymin": 83, "xmax": 598, "ymax": 103}},
                 {"score": 0.6614, "label": "couch", "box": {"xmin": 571, "ymin": 83, "xmax": 598, "ymax": 103}},
                 {"score": 0.6456, "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": 0.6419, "label": "cat", "box": {"xmin": 494, "ymin": 105, "xmax": 521, "ymax": 127}},
             ]		,					)

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

         self.assertEqual(
             nested_simplify(snake_case__		,					decimals=4						)		,					[
                 [
                     {"score": 0.7235, "label": "cat", "box": {"xmin": 204, "ymin": 167, "xmax": 232, "ymax": 190}},
                     {"score": 0.7218, "label": "remote", "box": {"xmin": 204, "ymin": 167, "xmax": 232, "ymax": 190}},
                     {"score": 0.7184, "label": "couch", "box": {"xmin": 204, "ymin": 167, "xmax": 232, "ymax": 190}},
                     {"score": 0.6748, "label": "remote", "box": {"xmin": 571, "ymin": 83, "xmax": 598, "ymax": 103}},
                     {"score": 0.6656, "label": "cat", "box": {"xmin": 571, "ymin": 83, "xmax": 598, "ymax": 103}},
                     {"score": 0.6614, "label": "couch", "box": {"xmin": 571, "ymin": 83, "xmax": 598, "ymax": 103}},
                     {"score": 0.6456, "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": 0.6419, "label": "cat", "box": {"xmin": 494, "ymin": 105, "xmax": 521, "ymax": 127}},
                 ]
             ]		,					)

       @require_torch
       @slow
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Dict								=							pipeline("zero-shot-object-detection"						)

         lowerCAmelCase					:					Dict								=							object_detector(
             "http://images.cocodataset.org/val2017/000000039769.jpg"		,					candidate_labels=["cat", "remote", "couch"]		,					)
         self.assertEqual(
             nested_simplify(snake_case__		,					decimals=4						)		,					[
                 {"score": 0.2868, "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": 0.2537, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 315, "ymax": 472}},
                 {"score": 0.1474, "label": "remote", "box": {"xmin": 335, "ymin": 74, "xmax": 371, "ymax": 187}},
                 {"score": 0.1208, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 642, "ymax": 476}},
             ]		,					)

         lowerCAmelCase					:					Dict								=							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(snake_case__		,					decimals=4						)		,					[
                 [
                     {"score": 0.2868, "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": 0.2537, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 315, "ymax": 472}},
                     {"score": 0.1474, "label": "remote", "box": {"xmin": 335, "ymin": 74, "xmax": 371, "ymax": 187}},
                     {"score": 0.1208, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 642, "ymax": 476}},
                 ],
                 [
                     {"score": 0.2868, "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": 0.2537, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 315, "ymax": 472}},
                     {"score": 0.1474, "label": "remote", "box": {"xmin": 335, "ymin": 74, "xmax": 371, "ymax": 187}},
                     {"score": 0.1208, "label": "couch", "box": {"xmin": 4, "ymin": 0, "xmax": 642, "ymax": 476}},
                 ],
             ]		,					)

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






         """simple docstring"""





         pass

       @require_torch
       @slow
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					Dict								=							0.2
         lowerCAmelCase					:					List[Any]								=							pipeline("zero-shot-object-detection"						)

         lowerCAmelCase					:					Union[str, Any]								=							object_detector(
             "http://images.cocodataset.org/val2017/000000039769.jpg"		,					candidate_labels=["cat", "remote", "couch"]		,					threshold=snake_case__		,					)
         self.assertEqual(
             nested_simplify(snake_case__		,					decimals=4						)		,					[
                 {"score": 0.2868, "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": 0.2537, "label": "cat", "box": {"xmin": 1, "ymin": 55, "xmax": 315, "ymax": 472}},
             ]		,					)







       @require_torch
       @slow
       def 	lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase					:					int								=							2
         lowerCAmelCase					:					Any								=							pipeline("zero-shot-object-detection"						)

         lowerCAmelCase					:					Any								=							object_detector(
             "http://images.cocodataset.org/val2017/000000039769.jpg"		,					candidate_labels=["cat", "remote", "couch"]		,					top_k=snake_case__		,					)
         self.assertEqual(
             nested_simplify(snake_case__		,					decimals=4						)		,					[
                 {"score": 0.2868, "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}},
             ]		,					)





