labelmeWithAI/labelme/utils/image.py

import base64
import io

import numpy as np
import PIL.Image


def img_b64_to_arr(img_b64):
    f = io.BytesIO()
    f.write(base64.b64decode(img_b64))
    img_arr = np.array(PIL.Image.open(f))
    return img_arr


def img_arr_to_b64(img_arr):
    img_pil = PIL.Image.fromarray(img_arr)
    f = io.BytesIO()
    img_pil.save(f, format='PNG')
    img_bin = f.getvalue()
    if hasattr(base64, 'encodebytes'):
        img_b64 = base64.encodebytes(img_bin)
    else:
        img_b64 = base64.encodestring(img_bin)
    return img_b64


def img_data_to_png_data(img_data):
    with io.BytesIO() as f:
        f.write(img_data)
        img = PIL.Image.open(f)

        with io.BytesIO() as f:
            img.save(f, 'PNG')
            f.seek(0)
            return f.read()


def apply_exif_orientation(image):
    try:
        exif = image._getexif()
    except AttributeError:
        exif = None

    if exif is None:
        return image

    exif = {
        PIL.ExifTags.TAGS[k]: v
        for k, v in exif.items()
        if k in PIL.ExifTags.TAGS
    }

    orientation = exif.get('Orientation', None)

    if orientation == 1:
        # do nothing
        return image
    elif orientation == 2:
        # left-to-right mirror
        return PIL.ImageOps.mirror(image)
    elif orientation == 3:
        # rotate 180
        return image.transpose(PIL.Image.ROTATE_180)
    elif orientation == 4:
        # top-to-bottom mirror
        return PIL.ImageOps.flip(image)
    elif orientation == 5:
        # top-to-left mirror
        return PIL.ImageOps.mirror(image.transpose(PIL.Image.ROTATE_270))
    elif orientation == 6:
        # rotate 270
        return image.transpose(PIL.Image.ROTATE_270)
    elif orientation == 7:
        # top-to-right mirror
        return PIL.ImageOps.mirror(image.transpose(PIL.Image.ROTATE_90))
    elif orientation == 8:
        # rotate 90
        return image.transpose(PIL.Image.ROTATE_90)
    else:
        return image