

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


_UpperCAmelCase		:   Optional[Any]										=       {
    """configuration_blip""": [
        """BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlipConfig""",
        """BlipTextConfig""",
        """BlipVisionConfig""",
    ],
    """processing_blip""": ["""BlipProcessor"""],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:   Optional[Any]										=       ["""BlipImageProcessor"""]


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:   int										=       [
					    """BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """BlipModel""",
					    """BlipPreTrainedModel""",
					    """BlipForConditionalGeneration""",
					    """BlipForQuestionAnswering""",
					    """BlipVisionModel""",
					    """BlipTextModel""",
					    """BlipForImageTextRetrieval""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase		:   Optional[Any]										=       [
					    """TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFBlipModel""",
					    """TFBlipPreTrainedModel""",
					    """TFBlipForConditionalGeneration""",
					    """TFBlipForQuestionAnswering""",
					    """TFBlipVisionModel""",
					    """TFBlipTextModel""",
					    """TFBlipForImageTextRetrieval""",
					]

if TYPE_CHECKING:
					from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
					from .processing_blip import BlipProcessor

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_blip import BlipImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_blip import (
										    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BlipForConditionalGeneration,
										    BlipForImageTextRetrieval,
										    BlipForQuestionAnswering,
										    BlipModel,
										    BlipPreTrainedModel,
										    BlipTextModel,
										    BlipVisionModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_blip import (
										    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFBlipForConditionalGeneration,
										    TFBlipForImageTextRetrieval,
										    TFBlipForQuestionAnswering,
										    TFBlipModel,
										    TFBlipPreTrainedModel,
										    TFBlipTextModel,
										    TFBlipVisionModel,
										)

else:
					import sys

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







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	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    1.5
							snake_case_							=    int(factor * num_class_images      )
							snake_case_							=    ClipClient(
							    url='https://knn.laion.ai/knn-service'   ,							indice_name='laion_400m'   ,							num_images=UpperCamelCase__   ,							aesthetic_weight=0.1      )

							os.makedirs(F'''{class_data_dir}/images'''   ,							exist_ok=UpperCamelCase__      )
							if len(list(Path(F'''{class_data_dir}/images'''      ).iterdir()      )      ) >= num_class_images:
														return

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

							snake_case_							=    0
							snake_case_							=    0
							snake_case_							=    tqdm(desc='downloading real regularization images'   ,							total=UpperCamelCase__      )

							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:
																					snake_case_							=    class_images[count]
																					count += 1
																					try:
																												snake_case_							=    requests.get(images['url']      )
																												if img.status_code == 200:
																																			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	( ):







							'''simple docstring'''






							snake_case_							=    argparse.ArgumentParser(''   ,							add_help=UpperCamelCase__      )
							parser.add_argument('--class_prompt'   ,							help='text prompt to retrieve images'   ,							required=UpperCamelCase__   ,							type=UpperCamelCase__      )
							parser.add_argument('--class_data_dir'   ,							help='path to save images'   ,							required=UpperCamelCase__   ,							type=UpperCamelCase__      )
							parser.add_argument('--num_class_images'   ,							help='number of images to download'   ,							default=200   ,							type=UpperCamelCase__      )
							return parser.parse_args()


if __name__ == "__main__":
					_UpperCAmelCase		:   Optional[int]										=       parse_args()
					retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)




