from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt



def lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
				'''simple docstring'''







				__UpperCamelCase					:Union[str, Any]        =		cva.getAffineTransform(__snake_case  ,      __snake_case     )
				return cva.warpAffine(__snake_case  ,      __snake_case  ,      (rows, cols)     )


if __name__ == "__main__":
				# read original image
				__lowercase										= cva.imread(
				    str(Path(__file__).resolve().parent.parent / '''image_data''' / '''lena.jpg''')
				)
				# turn image in gray scale value
				__lowercase										= cva.cvtColor(image, cva.COLOR_BGR2GRAY)
				# get image shape
				__lowercase										= gray_img.shape

				# set different points to rotate image
				__lowercase										= np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
				__lowercase										= np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
				__lowercase										= np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
				__lowercase										= np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

				# add all rotated images in a list
				__lowercase										= [
				    gray_img,
				    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
				    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
				    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
				]

				# plot different image rotations
				__lowercase										= plt.figure(1)
				__lowercase										= ["""Original""", """Rotation 1""", """Rotation 2""", """Rotation 3"""]
				for i, image in enumerate(images):
								plt.subplot(2, 2, i + 1), plt.imshow(image, '''gray''')
								plt.title(titles[i])
								plt.axis('''off''')
								plt.subplots_adjust(left=0.0, bottom=0.0_5, right=1.0, top=0.9_5)
				plt.show()






from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
    if not (is_transformers_available() and is_torch_available()):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
    from .notes_encoder import SpectrogramNotesEncoder
    from .continous_encoder import SpectrogramContEncoder
    from .pipeline_spectrogram_diffusion import (
        SpectrogramContEncoder,
        SpectrogramDiffusionPipeline,
        TaFilmDecoder,
    )

try:
    if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
    from .midi_utils import MidiProcessor





