
'''simple docstring'''




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

import cva
import numpy as np

# Parrameters
lowercase			:				Optional[int]    		=			(7_20, 12_80)  # Height, Width
lowercase			:				List[str]    		=			(0.4, 0.6)  # if height or width lower than this scale, drop it.
lowercase			:				List[Any]    		=			1 / 1_00
lowercase			:				Optional[Any]    		=			''
lowercase			:				Dict    		=			''
lowercase			:				str    		=			''
lowercase			:				str    		=			2_50







def 		lowerCAmelCase_				(   ):




    '''simple docstring'''



    A,  A       :   Dict					=						get_dataset(snake_case__		,				snake_case__						)
    for index in range(snake_case__						):
        A       :   Tuple					=						random.sample(range(len(snake_case__						)						)		,				4						)
        A,  A,  A       :   List[str]					=						update_image_and_anno(
            snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				filter_scale=snake_case__		,				)

        # Get random string code: '7b7ad245cdff75241935e4dd860f3bad'
        A       :   Union[str, Any]					=						random_chars(32						)
        A       :   Any					=						path.split(os.sep						)[-1].rsplit('''.'''		,				1						)[0]
        A       :   Union[str, Any]					=						F'{OUTPUT_DIR}/{file_name}_MOSAIC_{letter_code}'
        cva.imwrite(F'{file_root}.jpg'		,				snake_case__		,				[cva.IMWRITE_JPEG_QUALITY, 85]						)
        print(F'Succeeded {index+1}/{NUMBER_IMAGES} with {file_name}'						)
        A       :   Dict					=						[]
        for anno in new_annos:
            A       :   Optional[int]					=						anno[3] - anno[1]
            A       :   int					=						anno[4] - anno[2]
            A       :   str					=						anno[1] + width / 2
            A       :   List[str]					=						anno[2] + height / 2
            A       :   Dict					=						F'{anno[0]} {x_center} {y_center} {width} {height}'
            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 		lowerCAmelCase_				(   snake_case__		,				snake_case__						):




    '''simple docstring'''



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

        A       :   Tuple					=						[]
        for obj_list in obj_lists:
            A       :   List[Any]					=						obj_list.rstrip('''\n'''						).split(''' '''						)
            A       :   str					=						float(obj[1]						) - float(obj[3]						) / 2
            A       :   List[Any]					=						float(obj[2]						) - float(obj[4]						) / 2
            A       :   int					=						float(obj[1]						) + float(obj[3]						) / 2
            A       :   Optional[Any]					=						float(obj[2]						) + float(obj[4]						) / 2

            boxes.append([int(obj[0]						), xmin, ymin, xmax, ymax]						)
        if not boxes:
            continue
        img_paths.append(snake_case__						)
        labels.append(snake_case__						)
    return img_paths, labels







def 		lowerCAmelCase_				(   snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__		,				snake_case__ = 0.0		,				):




    '''simple docstring'''



    A       :   List[str]					=						np.zeros([output_size[0], output_size[1], 3]		,				dtype=np.uinta						)
    A       :   List[Any]					=						scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
    A       :   Optional[Any]					=						scale_range[0] + random.random() * (scale_range[1] - scale_range[0])
    A       :   Optional[Any]					=						int(scale_x * output_size[1]						)
    A       :   Union[str, Any]					=						int(scale_y * output_size[0]						)

    A       :   Union[str, Any]					=						[]
    A       :   Union[str, Any]					=						[]
    for i, index in enumerate(snake_case__						):
        A       :   List[Any]					=						all_img_list[index]
        path_list.append(snake_case__						)
        A       :   Tuple					=						all_annos[index]
        A       :   Optional[Any]					=						cva.imread(snake_case__						)
        if i == 0:  # top-left
            A       :   Optional[Any]					=						cva.resize(snake_case__		,				(divid_point_x, divid_point_y)						)
            A       :   Optional[Any]					=						img
            for bbox in img_annos:
                A       :   Union[str, Any]					=						bbox[1] * scale_x
                A       :   Optional[Any]					=						bbox[2] * scale_y
                A       :   int					=						bbox[3] * scale_x
                A       :   Optional[int]					=						bbox[4] * scale_y
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]						)
        elif i == 1:  # top-right
            A       :   Any					=						cva.resize(snake_case__		,				(output_size[1] - divid_point_x, divid_point_y)						)
            A       :   Optional[Any]					=						img
            for bbox in img_annos:
                A       :   Optional[Any]					=						scale_x + bbox[1] * (1 - scale_x)
                A       :   Tuple					=						bbox[2] * scale_y
                A       :   Any					=						scale_x + bbox[3] * (1 - scale_x)
                A       :   List[str]					=						bbox[4] * scale_y
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]						)
        elif i == 2:  # bottom-left
            A       :   Optional[Any]					=						cva.resize(snake_case__		,				(divid_point_x, output_size[0] - divid_point_y)						)
            A       :   Any					=						img
            for bbox in img_annos:
                A       :   Optional[Any]					=						bbox[1] * scale_x
                A       :   List[str]					=						scale_y + bbox[2] * (1 - scale_y)
                A       :   Optional[Any]					=						bbox[3] * scale_x
                A       :   Any					=						scale_y + bbox[4] * (1 - scale_y)
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]						)
        else:  # bottom-right
            A       :   List[str]					=						cva.resize(
                snake_case__		,				(output_size[1] - divid_point_x, output_size[0] - divid_point_y)						)
            A       :   str					=						img
            for bbox in img_annos:
                A       :   Dict					=						scale_x + bbox[1] * (1 - scale_x)
                A       :   int					=						scale_y + bbox[2] * (1 - scale_y)
                A       :   List[Any]					=						scale_x + bbox[3] * (1 - scale_x)
                A       :   Any					=						scale_y + bbox[4] * (1 - scale_y)
                new_anno.append([bbox[0], xmin, ymin, xmax, ymax]						)

    # Remove bounding box small than scale of filter
    if filter_scale > 0:
        A       :   List[str]					=						[
            anno
            for anno in new_anno
            if filter_scale < (anno[3] - anno[1]) and filter_scale < (anno[4] - anno[2])
        ]

    return output_img, new_anno, path_list[0]







def 		lowerCAmelCase_				(   snake_case__						):




    '''simple docstring'''



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


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






"""simple docstring"""




import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links


def   __magic_name__	(      __snake_case				:       Union[str, Any]     , __snake_case				:       List[str]=7  ) ->				str:
       lowercase    :				int       		=							None
       if token is not None:
              lowercase    :				Any       		=							{"Accept": "application/vnd.github+json", "Authorization": f"""Bearer {token}"""}

       # The id of a workflow (not of a workflow run)
       lowercase    :				int       		=							"636036"

       lowercase    :				Dict       		=							f"""https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"""
       # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
       url += f"""?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"""

       lowercase    :				int       		=							requests.get(__snake_case     , headers=__snake_case  ).json()

       return result["workflow_runs"]


def   __magic_name__	(      __snake_case				:       Dict  ) ->				Tuple:
       lowercase    :				Tuple       		=							get_daily_ci_runs(__snake_case  )
       lowercase    :				Union[str, Any]       		=							None
       for workflow_run in workflow_runs:
              if workflow_run["status"] == "completed":
                     lowercase    :				List[Any]       		=							workflow_run["id"]
                     break

       return workflow_run_id


def   __magic_name__	(      __snake_case				:       Optional[int]     , __snake_case				:       Optional[Any]     , __snake_case				:       Union[str, Any]  ) ->				int:
       lowercase    :				Dict       		=							get_last_daily_ci_runs(__snake_case  )
       if workflow_run_id is not None:
              lowercase    :				Dict       		=							get_artifacts_links(worflow_run_id=__snake_case     , token=__snake_case  )
              for artifact_name in artifact_names:
                     if artifact_name in artifacts_links:
                            lowercase    :				Optional[int]       		=							artifacts_links[artifact_name]
                            download_artifact(
                                artifact_name=__snake_case     , artifact_url=__snake_case     , output_dir=__snake_case     , token=__snake_case  )


def   __magic_name__	(      __snake_case				:       List[Any]     , __snake_case				:       Optional[int]     , __snake_case				:       Tuple  ) ->				Optional[int]:
       get_last_daily_ci_artifacts(__snake_case     , __snake_case     , __snake_case  )

       lowercase    :				str       		=							{}
       for artifact_name in artifact_names:
              lowercase    :				Optional[Any]       		=							os.path.join(__snake_case     , f"""{artifact_name}.zip"""  )
              if os.path.isfile(__snake_case  ):
                     lowercase    :				List[Any]       		=							{}
                     with zipfile.ZipFile(__snake_case  ) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(__snake_case  ):
                                          # read the file
                                          with z.open(__snake_case  ) as f:
                                                 lowercase    :				str       		=							f.read().decode("UTF-8"  )

       return results


