





import getopt
import json
import os

# import numpy as np
import sys
from collections import OrderedDict

import datasets
import numpy as np
import torch
from modeling_frcnn import GeneralizedRCNN
from processing_image import Preprocess

from utils import Config
_UpperCamelCase       = False
_UpperCamelCase       = Config.from_pretrained('''unc-nlp/frcnn-vg-finetuned''')
_UpperCamelCase       = datasets.Features(
    OrderedDict(
        {
            '''attr_ids''': datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value('''float32''')),
            '''attr_probs''': datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value('''float32''')),
            '''boxes''': datasets.ArrayaD((CONFIG.MAX_DETECTIONS, 4), dtype='''float32'''),
            '''img_id''': datasets.Value('''int32'''),
            '''obj_ids''': datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value('''float32''')),
            '''obj_probs''': datasets.Sequence(length=CONFIG.MAX_DETECTIONS, feature=datasets.Value('''float32''')),
            '''roi_features''': datasets.ArrayaD((CONFIG.MAX_DETECTIONS, 2048), dtype='''float32'''),
            '''sizes''': datasets.Sequence(length=2, feature=datasets.Value('''float32''')),
            '''preds_per_image''': datasets.Value(dtype='''int32'''),
        }
    )
)




class 				_lowerCamelCase :



      """simple docstring"""






      def __init__( self				,						UpperCAmelCase=sys.argv[1:]   )       ->   List[Any]:






        '''simple docstring'''






        __snake_case   :				Tuple        =       None
        __snake_case   :				Union[str, Any]        =       None
        __snake_case   :				List[Any]        =       None
        __snake_case   :				Optional[Any]        =       1
        __snake_case    ,   __snake_case   :				Optional[int]        =       getopt.getopt(UpperCAmelCase				,						"i:o:b:s"				,						["inputdir=", "outfile=", "batch_size=", "subset_list="]   )
        for opt, arg in opts:
          if opt in ("-i", "--inputdir"):
            __snake_case   :				Tuple        =       arg
          elif opt in ("-o", "--outfile"):
            __snake_case   :				List[Any]        =       arg
          elif opt in ("-b", "--batch_size"):
            __snake_case   :				Optional[int]        =       int(UpperCAmelCase   )
          elif opt in ("-s", "--subset_list"):
            __snake_case   :				Tuple        =       arg

        assert inputdir is not None  # and os.path.isdir(inputdir), f"{inputdir}"
        assert outputfile is not None and not os.path.isfile(UpperCAmelCase   ), F"""{outputfile}"""
        if subset_list is not None:
          with open(os.path.realpath(UpperCAmelCase   )   ) as f:
            __snake_case   :				Any        =       {self._vqa_file_split()[0] for x in tryload(UpperCAmelCase   )}
        else:
          __snake_case   :				int        =       None

        __snake_case   :				Tuple        =       CONFIG
        if torch.cuda.is_available():
          __snake_case   :				Union[str, Any]        =       "cuda"
        __snake_case   :				Tuple        =       os.path.realpath(UpperCAmelCase   )
        __snake_case   :				Dict        =       os.path.realpath(UpperCAmelCase   )
        __snake_case   :				Union[str, Any]        =       Preprocess(self.config   )
        __snake_case   :				Any        =       GeneralizedRCNN.from_pretrained("unc-nlp/frcnn-vg-finetuned"				,						config=self.config   )
        __snake_case   :				Tuple        =       batch_size if batch_size != 0 else 1
        __snake_case   :				Optional[Any]        =       DEFAULT_SCHEMA







      def 						UpperCAmelCase		( self				,						UpperCAmelCase   )       ->   Tuple:






        '''simple docstring'''






        __snake_case   :				Dict        =       int(file.split("."   )[0].split("_"   )[-1]   )
        __snake_case   :				str        =       os.path.join(self.inputdir				,						UpperCAmelCase   )
        return (img_id, filepath)







      @property
      def 						UpperCAmelCase		( self   )       ->   int:






        '''simple docstring'''






        __snake_case   :				Optional[int]        =       []
        for i, file in enumerate(os.listdir(self.inputdir   )   ):
          if self.subset_list is not None and i not in self.subset_list:
            continue
          batch.append(self._vqa_file_split(UpperCAmelCase   )   )
          if len(UpperCAmelCase   ) == self.batch:
            __snake_case   :				Dict        =       batch
            __snake_case   :				Dict        =       []
            yield list(map(UpperCAmelCase				,						zip(*UpperCAmelCase   )   )   )

        for i in range(1   ):
          yield list(map(UpperCAmelCase				,						zip(*UpperCAmelCase   )   )   )







      def __call__( self   )       ->   Optional[int]:






        '''simple docstring'''






        if not TEST:
          __snake_case   :				Any        =       datasets.ArrowWriter(features=self.schema				,						path=self.outputfile   )
        # do file generator
        for i, (img_ids, filepaths) in enumerate(self.file_generator   ):
          __snake_case    ,   __snake_case    ,   __snake_case   :				Optional[int]        =       self.preprocess(UpperCAmelCase   )
          __snake_case   :				str        =       self.model(
              UpperCAmelCase				,						UpperCAmelCase				,						scales_yx=UpperCAmelCase				,						padding="max_detections"				,						max_detections=self.config.MAX_DETECTIONS				,						pad_value=0				,						return_tensors="np"				,						location="cpu"				,						)
          __snake_case   :				Dict        =       output_dict.pop("normalized_boxes"   )
          if not TEST:
            __snake_case   :				Dict        =       np.array(UpperCAmelCase   )
            __snake_case   :				Any        =       self.schema.encode_batch(UpperCAmelCase   )
            writer.write_batch(UpperCAmelCase   )
          if TEST:
            break
          # finalizer the writer
        if not TEST:
          __snake_case    ,   __snake_case   :				Optional[Any]        =       writer.finalize()
          print(F"""Success! You wrote {num_examples} entry(s) and {num_bytes >> 20} mb"""   )







def       lowerCAmelCase__(	lowercase       :    int				) ->    Union[str, Any]:
  try:
    __snake_case   :				Optional[Any]        =       json.load(lowercase				)
    try:
      __snake_case   :				Any        =       list(data.keys()				)
    except Exception:
      __snake_case   :				List[str]        =       [d["img_id"] for d in data]
  except Exception:
    try:
      __snake_case   :				str        =       eval(stream.read()				)
    except Exception:
      __snake_case   :				Dict        =       stream.read().split("\n"				)
  return data


if __name__ == "__main__":
     _UpperCamelCase       = Extract(sys.argv[1:])
     extract()
     if not TEST:
          _UpperCamelCase       = datasets.Dataset.from_file(extract.outputfile)
          # wala!
          # print(np.array(dataset[0:2]["roi_features"]).shape)








import subprocess
from argparse import ArgumentParser
from typing import List, Union

from huggingface_hub.hf_api import HfFolder, create_repo, whoami
from requests.exceptions import HTTPError

from . import BaseTransformersCLICommand




class 				_lowerCamelCase (    a    ):



      """simple docstring"""






      @staticmethod
      def 						UpperCAmelCase		( UpperCAmelCase   )       ->   Any:






        '''simple docstring'''






        __snake_case   :				Dict        =       parser.add_parser("login"				,						help="Log in using the same credentials as on huggingface.co"   )
        login_parser.set_defaults(func=lambda UpperCAmelCase   : LoginCommand(UpperCAmelCase   )   )
        __snake_case   :				int        =       parser.add_parser("whoami"				,						help="Find out which huggingface.co account you are logged in as."   )
        whoami_parser.set_defaults(func=lambda UpperCAmelCase   : WhoamiCommand(UpperCAmelCase   )   )
        __snake_case   :				int        =       parser.add_parser("logout"				,						help="Log out"   )
        logout_parser.set_defaults(func=lambda UpperCAmelCase   : LogoutCommand(UpperCAmelCase   )   )

        # new system: git-based repo system
        __snake_case   :				Union[str, Any]        =       parser.add_parser(
            "repo"				,						help="Deprecated: use `huggingface-cli` instead. Commands to interact with your huggingface.co repos."				,						)
        __snake_case   :				List[str]        =       repo_parser.add_subparsers(
            help="Deprecated: use `huggingface-cli` instead. huggingface.co repos related commands"   )
        __snake_case   :				int        =       repo_subparsers.add_parser(
            "create"				,						help="Deprecated: use `huggingface-cli` instead. Create a new repo on huggingface.co"   )
        repo_create_parser.add_argument(
            "name"				,						type=UpperCAmelCase				,						help="Name for your model's repo. Will be namespaced under your username to build the model id."				,						)
        repo_create_parser.add_argument("--organization"				,						type=UpperCAmelCase				,						help="Optional: organization namespace."   )
        repo_create_parser.add_argument("-y"				,						"--yes"				,						action="store_true"				,						help="Optional: answer Yes to the prompt"   )
        repo_create_parser.set_defaults(func=lambda UpperCAmelCase   : RepoCreateCommand(UpperCAmelCase   )   )




class 				_lowerCamelCase :



      """simple docstring"""






      UpperCAmelCase_						:      Tuple       ="\u001b[1m"
      UpperCAmelCase_						:      int       ="\u001b[31m"
      UpperCAmelCase_						:      Optional[Any]       ="\u001b[90m"
      UpperCAmelCase_						:      Optional[Any]       ="\u001b[0m"







      @classmethod
      def 						UpperCAmelCase		( cls				,						UpperCAmelCase   )       ->   Union[str, Any]:






        '''simple docstring'''






        return F"""{cls._bold}{s}{cls._reset}"""







      @classmethod
      def 						UpperCAmelCase		( cls				,						UpperCAmelCase   )       ->   Optional[int]:






        '''simple docstring'''






        return F"""{cls._bold}{cls._red}{s}{cls._reset}"""







      @classmethod
      def 						UpperCAmelCase		( cls				,						UpperCAmelCase   )       ->   List[str]:






        '''simple docstring'''






        return F"""{cls._gray}{s}{cls._reset}"""







def       lowerCAmelCase__(	lowercase       :    List[List[Union[str, int]]]   ,     lowercase       :    List[str]				) ->    str:
  __snake_case   :				Dict        =       [max(len(str(lowercase				)				) for x in col				) for col in zip(*lowercase   ,     lowercase				)]
  __snake_case   :				str        =       ("{{:{}}} " * len(lowercase				)).format(*lowercase				)
  __snake_case   :				Tuple        =       []
  lines.append(row_format.format(*lowercase				)				)
  lines.append(row_format.format(*["-" * w for w in col_widths]				)				)
  for row in rows:
    lines.append(row_format.format(*lowercase				)				)
  return "\n".join(lowercase				)




class 				_lowerCamelCase :



      """simple docstring"""






      def __init__( self				,						UpperCAmelCase   )       ->   Dict:






        '''simple docstring'''






        __snake_case   :				List[str]        =       args




class 				_lowerCamelCase (    a    ):



      """simple docstring"""






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






        '''simple docstring'''






        print(
            ANSI.red(
                "ERROR! `huggingface-cli login` uses an outdated login mechanism "
                "that is not compatible with the Hugging Face Hub backend anymore. "
                "Please use `huggingface-cli login instead."   )   )




class 				_lowerCamelCase (    a    ):



      """simple docstring"""






      def 						UpperCAmelCase		( self   )       ->   str:






        '''simple docstring'''






        print(
            ANSI.red(
                "WARNING! `transformers-cli whoami` is deprecated and will be removed in v5. Please use "
                "`huggingface-cli whoami` instead."   )   )
        __snake_case   :				Optional[Any]        =       HfFolder.get_token()
        if token is None:
          print("Not logged in"   )
          exit()
        try:
          __snake_case    ,   __snake_case   :				Tuple        =       whoami(UpperCAmelCase   )
          print(UpperCAmelCase   )
          if orgs:
            print(ANSI.bold("orgs: "   )				,						",".join(UpperCAmelCase   )   )
        except HTTPError as e:
          print(UpperCAmelCase   )
          print(ANSI.red(e.response.text   )   )
          exit(1   )




class 				_lowerCamelCase (    a    ):



      """simple docstring"""






      def 						UpperCAmelCase		( self   )       ->   List[str]:






        '''simple docstring'''






        print(
            ANSI.red(
                "ERROR! `transformers-cli logout` uses an outdated logout mechanism "
                "that is not compatible with the Hugging Face Hub backend anymore. "
                "Please use `huggingface-cli logout instead."   )   )




class 				_lowerCamelCase (    a    ):



      """simple docstring"""






      def 						UpperCAmelCase		( self   )       ->   Tuple:






        '''simple docstring'''






        print(
            ANSI.red(
                "WARNING! Managing repositories through transformers-cli is deprecated. "
                "Please use `huggingface-cli` instead."   )   )
        __snake_case   :				Dict        =       HfFolder.get_token()
        if token is None:
          print("Not logged in"   )
          exit(1   )
        try:
          __snake_case   :				Optional[int]        =       subprocess.check_output(["git", "--version"]   ).decode("utf-8"   )
          print(ANSI.gray(stdout.strip()   )   )
        except FileNotFoundError:
          print("Looks like you do not have git installed, please install."   )

        try:
          __snake_case   :				Union[str, Any]        =       subprocess.check_output(["git-lfs", "--version"]   ).decode("utf-8"   )
          print(ANSI.gray(stdout.strip()   )   )
        except FileNotFoundError:
          print(
              ANSI.red(
                  "Looks like you do not have git-lfs installed, please install."
                  " You can install from https://git-lfs.github.com/."
                  " Then run `git lfs install` (you only have to do this once)."   )   )
        print(""   )

        __snake_case    ,   __snake_case   :				Any        =       whoami(UpperCAmelCase   )
        __snake_case   :				List[str]        =       self.args.organization if self.args.organization is not None else user
        __snake_case   :				Any        =       F"""{namespace}/{self.args.name}"""
        print(F"""You are about to create {ANSI.bold(UpperCAmelCase   )}"""   )

        if not self.args.yes:
          __snake_case   :				Optional[int]        =       input("Proceed? [Y/n] "   ).lower()
          if not (choice == "" or choice == "y" or choice == "yes"):
            print("Abort"   )
            exit()
        try:
          __snake_case   :				List[str]        =       create_repo(UpperCAmelCase				,						name=self.args.name				,						organization=self.args.organization   )
        except HTTPError as e:
          print(UpperCAmelCase   )
          print(ANSI.red(e.response.text   )   )
          exit(1   )
        print("\nYour repo now lives at:"   )
        print(F"""  {ANSI.bold(UpperCAmelCase   )}"""   )
        print("\nYou can clone it locally with the command below, and commit/push as usual."   )
        print(F"""\n  git clone {url}"""   )
        print(""   )

