

import argparse
import os
from io import BytesIO
from pathlib import Path

import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    List[str]	,     SCREAMING_SNAKE_CASE_		:    Any	,     SCREAMING_SNAKE_CASE_		:    List[Any]			):



     '''simple docstring'''





     lowercase__    :   int      =       1.5
     lowercase__    :   Optional[int]      =       int(factor * num_class_images			)
     lowercase__    :   List[Any]      =       ClipClient(
         url='https://knn.laion.ai/knn-service'	,     indice_name='laion_400m'	,     num_images=SCREAMING_SNAKE_CASE_	,     aesthetic_weight=0.1			)

     os.makedirs(f"""{class_data_dir}/images"""	,     exist_ok=SCREAMING_SNAKE_CASE_			)
     if len(list(Path(f"""{class_data_dir}/images"""			).iterdir()			)			) >= num_class_images:
          return

     while True:
          lowercase__    :   Dict      =       client.query(text=SCREAMING_SNAKE_CASE_			)
          if len(SCREAMING_SNAKE_CASE_			) >= factor * num_class_images or num_images > 1E4:
               break
          else:
               lowercase__    :   Optional[int]      =       int(factor * num_images			)
               lowercase__    :   str      =       ClipClient(
                   url='https://knn.laion.ai/knn-service'	,     indice_name='laion_400m'	,     num_images=SCREAMING_SNAKE_CASE_	,     aesthetic_weight=0.1	,     )

     lowercase__    :   Tuple      =       0
     lowercase__    :   List[str]      =       0
     lowercase__    :   List[str]      =       tqdm(desc='downloading real regularization images'	,     total=SCREAMING_SNAKE_CASE_			)

     with open(f"""{class_data_dir}/caption.txt"""	,     'w'			) as fa, open(f"""{class_data_dir}/urls.txt"""	,     'w'			) as fa, open(
         f"""{class_data_dir}/images.txt"""	,     'w'			) as fa:
          while total < num_class_images:
               lowercase__    :   str      =       class_images[count]
               count += 1
               try:
                    lowercase__    :   Tuple      =       requests.get(images['url']			)
                    if img.status_code == 200:
                         lowercase__    :   str      =       Image.open(BytesIO(img.content			)			)
                         with open(f"""{class_data_dir}/images/{total}.jpg"""	,     'wb'			) as f:
                              f.write(img.content			)
                         fa.write(images['caption'] + '\n'			)
                         fa.write(images['url'] + '\n'			)
                         fa.write(f"""{class_data_dir}/images/{total}.jpg""" + '\n'			)
                         total += 1
                         pbar.update(1			)
                    else:
                         continue
               except Exception:
                    continue
     return

def 	snake_case__			(    ):



     '''simple docstring'''





     lowercase__    :   Optional[int]      =       argparse.ArgumentParser(''	,     add_help=SCREAMING_SNAKE_CASE_			)
     parser.add_argument('--class_prompt'	,     help='text prompt to retrieve images'	,     required=SCREAMING_SNAKE_CASE_	,     type=SCREAMING_SNAKE_CASE_			)
     parser.add_argument('--class_data_dir'	,     help='path to save images'	,     required=SCREAMING_SNAKE_CASE_	,     type=SCREAMING_SNAKE_CASE_			)
     parser.add_argument('--num_class_images'	,     help='number of images to download'	,     default=200	,     type=SCREAMING_SNAKE_CASE_			)
     return parser.parse_args()


if __name__ == "__main__":
       snake_case_			  = parse_args()
       retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case_			  = {
    '''configuration_instructblip''': [
        '''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''InstructBlipConfig''',
        '''InstructBlipQFormerConfig''',
        '''InstructBlipVisionConfig''',
    ],
    '''processing_instructblip''': ['''InstructBlipProcessor'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       snake_case_			  = [
           '''INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''InstructBlipQFormerModel''',
           '''InstructBlipPreTrainedModel''',
           '''InstructBlipForConditionalGeneration''',
           '''InstructBlipVisionModel''',
       ]

if TYPE_CHECKING:
       from .configuration_instructblip import (
           INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           InstructBlipConfig,
           InstructBlipQFormerConfig,
           InstructBlipVisionConfig,
       )
       from .processing_instructblip import InstructBlipProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_instructblip import (
                  INSTRUCTBLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  InstructBlipForConditionalGeneration,
                  InstructBlipPreTrainedModel,
                  InstructBlipQFormerModel,
                  InstructBlipVisionModel,
              )

else:
       import sys

       snake_case_			  = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

