
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
     import torch


if is_vision_available():
     from PIL import Image

     from transformers import MgpstrProcessor, ViTImageProcessor




@require_torch
@require_vision
class 			snake_case__   (							unittest.TestCase):

       '''simple docstring'''
       lowerCamelCase							:				Optional[Any] 				= ViTImageProcessor if is_vision_available() else None



       @property
       def 					__lowercase						(							self    ) ->      Dict:






            '''simple docstring'''





            return self.image_processor_tester.prepare_image_processor_dict()



       def 					__lowercase						(							self    ) ->      List[Any]:






            '''simple docstring'''





            __snake_case			:Union[str, Any]          =						(3, 32, 1_28)
            __snake_case			:str          =						tempfile.mkdtemp()

            # fmt: off
            __snake_case			:Dict          =						["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
            # fmt: on
            __snake_case			:str          =						dict(zip(_UpperCamelCase			,						range(len(_UpperCamelCase    )    )    )    )

            __snake_case			:int          =						os.path.join(self.tmpdirname			,						VOCAB_FILES_NAMES["""vocab_file"""]    )
            with open(self.vocab_file			,						"""w"""			,						encoding="""utf-8"""    ) as fp:
                 fp.write(json.dumps(_UpperCamelCase    ) + """\n"""    )

            __snake_case			:Any          =						{
                """do_normalize""": False,
                """do_resize""": True,
                """image_processor_type""": """ViTImageProcessor""",
                """resample""": 3,
                """size""": {"""height""": 32, """width""": 1_28},
            }
            __snake_case			:Union[str, Any]          =						os.path.join(self.tmpdirname			,						_UpperCamelCase    )
            with open(self.image_processor_file			,						"""w"""			,						encoding="""utf-8"""    ) as fp:
                 json.dump(_UpperCamelCase			,						_UpperCamelCase    )



       def 					__lowercase						(							self			,						**a__    ) ->      Tuple:






            '''simple docstring'''





            return MgpstrTokenizer.from_pretrained(self.tmpdirname			,						**_UpperCamelCase    )



       def 					__lowercase						(							self			,						**a__    ) ->      List[Any]:






            '''simple docstring'''





            return ViTImageProcessor.from_pretrained(self.tmpdirname			,						**_UpperCamelCase    )



       def 					__lowercase						(							self    ) ->      Optional[Any]:






            '''simple docstring'''





            shutil.rmtree(self.tmpdirname    )



       def 					__lowercase						(							self    ) ->      Any:






            '''simple docstring'''





            __snake_case			:Tuple          =						np.random.randint(2_55			,						size=(3, 30, 4_00)			,						dtype=np.uinta    )

            __snake_case			:int          =						Image.fromarray(np.moveaxis(_UpperCamelCase			,						0			,						-1    )    )

            return image_input



       def 					__lowercase						(							self    ) ->      str:






            '''simple docstring'''





            __snake_case			:List[str]          =						self.get_tokenizer()
            __snake_case			:Tuple          =						self.get_image_processor()

            __snake_case			:Union[str, Any]          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )
            processor.save_pretrained(self.tmpdirname    )
            __snake_case			:int          =						MgpstrProcessor.from_pretrained(self.tmpdirname			,						use_fast=_UpperCamelCase    )

            self.assertEqual(processor.char_tokenizer.get_vocab()			,						tokenizer.get_vocab()    )
            self.assertIsInstance(processor.char_tokenizer			,						_UpperCamelCase    )

            self.assertEqual(processor.image_processor.to_json_string()			,						image_processor.to_json_string()    )
            self.assertIsInstance(processor.image_processor			,						_UpperCamelCase    )



       def 					__lowercase						(							self    ) ->      Dict:






            '''simple docstring'''





            __snake_case			:Dict          =						self.get_tokenizer()
            __snake_case			:Optional[Any]          =						self.get_image_processor()

            __snake_case			:Any          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )
            processor.save_pretrained(self.tmpdirname    )

            __snake_case			:Tuple          =						self.get_tokenizer(bos_token="""(BOS)"""			,						eos_token="""(EOS)"""    )
            __snake_case			:Union[str, Any]          =						self.get_image_processor(do_normalize=_UpperCamelCase			,						padding_value=1.0    )

            __snake_case			:Tuple          =						MgpstrProcessor.from_pretrained(
                self.tmpdirname			,						bos_token="""(BOS)"""			,						eos_token="""(EOS)"""			,						do_normalize=_UpperCamelCase			,						padding_value=1.0    )

            self.assertEqual(processor.char_tokenizer.get_vocab()			,						tokenizer_add_kwargs.get_vocab()    )
            self.assertIsInstance(processor.char_tokenizer			,						_UpperCamelCase    )

            self.assertEqual(processor.image_processor.to_json_string()			,						image_processor_add_kwargs.to_json_string()    )
            self.assertIsInstance(processor.image_processor			,						_UpperCamelCase    )



       def 					__lowercase						(							self    ) ->      int:






            '''simple docstring'''





            __snake_case			:int          =						self.get_image_processor()
            __snake_case			:int          =						self.get_tokenizer()

            __snake_case			:List[str]          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )

            __snake_case			:List[str]          =						self.prepare_image_inputs()

            __snake_case			:Optional[int]          =						image_processor(_UpperCamelCase			,						return_tensors="""np"""    )
            __snake_case			:int          =						processor(images=_UpperCamelCase			,						return_tensors="""np"""    )

            for key in input_image_proc.keys():
                 self.assertAlmostEqual(input_image_proc[key].sum()			,						input_processor[key].sum()			,						delta=1e-2    )



       def 					__lowercase						(							self    ) ->      List[Any]:






            '''simple docstring'''





            __snake_case			:List[Any]          =						self.get_image_processor()
            __snake_case			:int          =						self.get_tokenizer()

            __snake_case			:Any          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )

            __snake_case			:Optional[int]          =						"""test"""

            __snake_case			:Union[str, Any]          =						processor(text=_UpperCamelCase    )

            __snake_case			:Dict          =						tokenizer(_UpperCamelCase    )
            for key in encoded_tok.keys():
                 self.assertListEqual(encoded_tok[key]			,						encoded_processor[key]    )



       def 					__lowercase						(							self    ) ->      Optional[Any]:






            '''simple docstring'''





            __snake_case			:Union[str, Any]          =						self.get_image_processor()
            __snake_case			:List[Any]          =						self.get_tokenizer()

            __snake_case			:Any          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )

            __snake_case			:Any          =						"""test"""
            __snake_case			:List[str]          =						self.prepare_image_inputs()

            __snake_case			:int          =						processor(text=_UpperCamelCase			,						images=_UpperCamelCase    )

            self.assertListEqual(list(inputs.keys()    )			,						["""pixel_values""", """labels"""]    )

            # test if it raises when no input is passed
            with pytest.raises(_UpperCamelCase    ):
                 processor()



       def 					__lowercase						(							self    ) ->      str:






            '''simple docstring'''





            __snake_case			:Union[str, Any]          =						self.get_image_processor()
            __snake_case			:List[str]          =						self.get_tokenizer()

            __snake_case			:Dict          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )

            __snake_case			:int          =						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

            __snake_case			:Any          =						processor.char_decode(_UpperCamelCase    )
            __snake_case			:Tuple          =						tokenizer.batch_decode(_UpperCamelCase    )
            __snake_case			:List[str]          =						[seq.replace(""" """			,						""""""    ) for seq in decoded_tok]

            self.assertListEqual(_UpperCamelCase			,						_UpperCamelCase    )



       def 					__lowercase						(							self    ) ->      str:






            '''simple docstring'''





            __snake_case			:Dict          =						self.get_image_processor()
            __snake_case			:str          =						self.get_tokenizer()

            __snake_case			:List[Any]          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )

            __snake_case			:int          =						None
            __snake_case			:Union[str, Any]          =						self.prepare_image_inputs()

            __snake_case			:Union[str, Any]          =						processor(text=_UpperCamelCase			,						images=_UpperCamelCase    )

            self.assertListEqual(list(inputs.keys()    )			,						processor.model_input_names    )



       def 					__lowercase						(							self    ) ->      Union[str, Any]:






            '''simple docstring'''





            __snake_case			:List[str]          =						self.get_image_processor()
            __snake_case			:int          =						self.get_tokenizer()

            __snake_case			:Union[str, Any]          =						MgpstrProcessor(tokenizer=_UpperCamelCase			,						image_processor=_UpperCamelCase    )

            __snake_case			:Any          =						torch.randn(1			,						27			,						38    )
            __snake_case			:List[Any]          =						torch.randn(1			,						27			,						5_02_57    )
            __snake_case			:List[str]          =						torch.randn(1			,						27			,						3_05_22    )

            __snake_case			:int          =						processor.batch_decode([char_input, bpe_input, wp_input]    )

            self.assertListEqual(list(results.keys()    )			,						["""generated_text""", """scores""", """char_preds""", """bpe_preds""", """wp_preds"""]    )










import glob
import os
import random
from string import ascii_lowercase, digits

import cva
lowerCamelCase__							=     """"""
lowerCamelCase__							=     """"""
lowerCamelCase__							=     """"""
lowerCamelCase__							=     1  # (0 is vertical, 1 is horizontal)






def   UpperCamelCase  (       ):




     '''simple docstring'''






     __snake_case       , __snake_case			:List[Any]          =						get_dataset(snake_case__	,snake_case__  )
     print("""Processing..."""  )
     __snake_case       , __snake_case       , __snake_case			:Tuple          =						update_image_and_anno(snake_case__	,snake_case__	,snake_case__  )

     for index, image in enumerate(snake_case__  ):
          # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
          __snake_case			:str          =						random_chars(32  )
          __snake_case			:Optional[Any]          =						paths[index].split(os.sep  )[-1].rsplit("""."""	,1  )[0]
          __snake_case			:List[str]          =						f'''{OUTPUT_DIR}/{file_name}_FLIP_{letter_code}'''
          cva.imwrite(f'''/{file_root}.jpg'''	,snake_case__	,[cva.IMWRITE_JPEG_QUALITY, 85]  )
          print(f'''Success {index+1}/{len(snake_case__  )} with {file_name}'''  )
          __snake_case			:Optional[int]          =						[]
          for anno in new_annos[index]:
               __snake_case			:str          =						f'''{anno[0]} {anno[1]} {anno[2]} {anno[3]} {anno[4]}'''
               annos_list.append(snake_case__  )
          with open(f'''/{file_root}.txt'''	,"""w"""  ) as outfile:
               outfile.write("""\n""".join(line for line in annos_list  )  )






def   UpperCamelCase  (       snake_case__     :   str	,snake_case__     :   str  ):




     '''simple docstring'''






     __snake_case			:List[str]          =						[]
     __snake_case			:Dict          =						[]
     for label_file in glob.glob(os.path.join(snake_case__	,"""*.txt"""  )  ):
          __snake_case			:Tuple          =						label_file.split(os.sep  )[-1].rsplit("""."""	,1  )[0]
          with open(snake_case__  ) as in_file:
               __snake_case			:Optional[int]          =						in_file.readlines()
          __snake_case			:Any          =						os.path.join(snake_case__	,f'''{label_name}.jpg'''  )

          __snake_case			:List[str]          =						[]
          for obj_list in obj_lists:
               __snake_case			:int          =						obj_list.rstrip("""\n"""  ).split(""" """  )
               boxes.append(
                   [
                       int(obj[0]  ),
                       float(obj[1]  ),
                       float(obj[2]  ),
                       float(obj[3]  ),
                       float(obj[4]  ),
                   ]  )
          if not boxes:
               continue
          img_paths.append(snake_case__  )
          labels.append(snake_case__  )
     return img_paths, labels






def   UpperCamelCase  (       snake_case__     :   list	,snake_case__     :   list	,snake_case__     :   int = 1  ):




     '''simple docstring'''






     __snake_case			:Dict          =						[]
     __snake_case			:Any          =						[]
     __snake_case			:int          =						[]
     for idx in range(len(snake_case__  )  ):
          __snake_case			:Optional[int]          =						[]
          __snake_case			:List[str]          =						img_list[idx]
          path_list.append(snake_case__  )
          __snake_case			:Union[str, Any]          =						anno_list[idx]
          __snake_case			:List[Any]          =						cva.imread(snake_case__  )
          if flip_type == 1:
               __snake_case			:Optional[Any]          =						cva.flip(snake_case__	,snake_case__  )
               for bbox in img_annos:
                    __snake_case			:Union[str, Any]          =						1 - bbox[1]
                    new_annos.append([bbox[0], x_center_new, bbox[2], bbox[3], bbox[4]]  )
          elif flip_type == 0:
               __snake_case			:Union[str, Any]          =						cva.flip(snake_case__	,snake_case__  )
               for bbox in img_annos:
                    __snake_case			:Optional[Any]          =						1 - bbox[2]
                    new_annos.append([bbox[0], bbox[1], y_center_new, bbox[3], bbox[4]]  )
          new_annos_lists.append(snake_case__  )
          new_imgs_list.append(snake_case__  )
     return new_imgs_list, new_annos_lists, path_list






def   UpperCamelCase  (       snake_case__     :   int = 32  ):




     '''simple docstring'''






     assert number_char > 1, "The number of character should greater than 1"
     __snake_case			:Optional[Any]          =						ascii_lowercase + digits
     return "".join(random.choice(snake_case__  ) for _ in range(snake_case__  )  )


if __name__ == "__main__":
     main()
     print("""DONE ✅""")


