
'''simple docstring'''



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    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_						)     ->     List[str]:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				1.5
   _SCREAMING_SNAKE_CASE      =				int(factor * num_class_images						)
   _SCREAMING_SNAKE_CASE      =				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:
      _SCREAMING_SNAKE_CASE      =				client.query(text=SCREAMING_SNAKE_CASE_						)
      if len(SCREAMING_SNAKE_CASE_						) >= factor * num_class_images or num_images > 1e4:
         break
      else:
         _SCREAMING_SNAKE_CASE      =				int(factor * num_images						)
         _SCREAMING_SNAKE_CASE      =				ClipClient(
             url="""https://knn.laion.ai/knn-service"""    ,      indice_name="""laion_400m"""    ,      num_images=SCREAMING_SNAKE_CASE_    ,      aesthetic_weight=0.1    ,      )

   _SCREAMING_SNAKE_CASE      =				0
   _SCREAMING_SNAKE_CASE      =				0
   _SCREAMING_SNAKE_CASE      =				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:
         _SCREAMING_SNAKE_CASE      =				class_images[count]
         count += 1
         try:
            _SCREAMING_SNAKE_CASE      =				requests.get(images["""url"""]						)
            if img.status_code == 2_00:
               _SCREAMING_SNAKE_CASE      =				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    lowerCAmelCase_	(				)     ->     Dict:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				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=2_00    ,      type=SCREAMING_SNAKE_CASE_						)
   return parser.parse_args()


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








'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCamelCase__      :		str       							=  {
    "configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
    "tokenization_canine": ["CanineTokenizer"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase__      :		List[Any]       							=  [
         "CANINE_PRETRAINED_MODEL_ARCHIVE_LIST",
         "CanineForMultipleChoice",
         "CanineForQuestionAnswering",
         "CanineForSequenceClassification",
         "CanineForTokenClassification",
         "CanineLayer",
         "CanineModel",
         "CaninePreTrainedModel",
         "load_tf_weights_in_canine",
     ]


if TYPE_CHECKING:
     from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
     from .tokenization_canine import CanineTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_canine import (
              CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
              CanineForMultipleChoice,
              CanineForQuestionAnswering,
              CanineForSequenceClassification,
              CanineForTokenClassification,
              CanineLayer,
              CanineModel,
              CaninePreTrainedModel,
              load_tf_weights_in_canine,
          )


else:
     import sys

     UpperCamelCase__      :		str       							=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






