convertor.py

import pandas as pd
import numpy as np
from skimage import color 
from PIL import Image


def skimage_rgb2lab(rgb):
    return color.rgb2lab(rgb.reshape(1,1,3))


def rgb2df(img):
    h, w, _ = img.shape
    x_l, y_l = np.meshgrid(np.arange(h), np.arange(w), indexing='ij')
    r, g, b = img[:,:,0], img[:,:,1], img[:,:,2]
    df = pd.DataFrame({
        "x_l": x_l.ravel(),
        "y_l": y_l.ravel(),
        "r": r.ravel(),
        "g": g.ravel(),
        "b": b.ravel(),
    })
    return df

def mask2df(mask):
    h, w = mask.shape
    x_l, y_l = np.meshgrid(np.arange(h), np.arange(w), indexing='ij')
    flg = mask.astype(int)
    df = pd.DataFrame({
        "x_l_m": x_l.ravel(),
        "y_l_m": y_l.ravel(),
        "m_flg": flg.ravel(),
    })
    return df


def rgba2df(img):
    h, w, _ = img.shape
    x_l, y_l = np.meshgrid(np.arange(h), np.arange(w), indexing='ij')
    r, g, b, a = img[:,:,0], img[:,:,1], img[:,:,2], img[:,:,3]
    df = pd.DataFrame({
        "x_l": x_l.ravel(),
        "y_l": y_l.ravel(),
        "r": r.ravel(),
        "g": g.ravel(),
        "b": b.ravel(),
        "a": a.ravel()
    })
    return df

def hsv2df(img):
    x_l, y_l = np.meshgrid(np.arange(img.shape[0]), np.arange(img.shape[1]), indexing='ij')
    h, s, v = np.transpose(img, (2, 0, 1))
    df = pd.DataFrame({'x_l': x_l.flatten(), 'y_l': y_l.flatten(), 'h': h.flatten(), 's': s.flatten(), 'v': v.flatten()})
    return df

def df2rgba(img_df):
    r_img = img_df.pivot_table(index="x_l", columns="y_l",values= "r").reset_index(drop=True).values
    g_img = img_df.pivot_table(index="x_l", columns="y_l",values= "g").reset_index(drop=True).values
    b_img = img_df.pivot_table(index="x_l", columns="y_l",values= "b").reset_index(drop=True).values
    a_img = img_df.pivot_table(index="x_l", columns="y_l",values= "a").reset_index(drop=True).values
    df_img = np.stack([r_img, g_img, b_img, a_img], 2).astype(np.uint8)
    return df_img

def df2bgra(img_df):
    r_img = img_df.pivot_table(index="x_l", columns="y_l",values= "r").reset_index(drop=True).values
    g_img = img_df.pivot_table(index="x_l", columns="y_l",values= "g").reset_index(drop=True).values
    b_img = img_df.pivot_table(index="x_l", columns="y_l",values= "b").reset_index(drop=True).values
    a_img = img_df.pivot_table(index="x_l", columns="y_l",values= "a").reset_index(drop=True).values
    df_img = np.stack([b_img, g_img, r_img, a_img], 2).astype(np.uint8)
    return df_img

def df2rgb(img_df):
    r_img = img_df.pivot_table(index="x_l", columns="y_l",values= "r").reset_index(drop=True).values
    g_img = img_df.pivot_table(index="x_l", columns="y_l",values= "g").reset_index(drop=True).values
    b_img = img_df.pivot_table(index="x_l", columns="y_l",values= "b").reset_index(drop=True).values
    df_img = np.stack([r_img, g_img, b_img], 2).astype(np.uint8)
    return df_img

def pil2cv(image):
    new_image = np.array(image, dtype=np.uint8)
    if new_image.ndim == 2:
        pass
    elif new_image.shape[2] == 3:
        new_image = new_image[:, :, ::-1]
    elif new_image.shape[2] == 4:
        new_image = new_image[:, :, [2, 1, 0, 3]]
    return new_image

def cv2pil(image):
    new_image = image.copy()
    if new_image.ndim == 2:
        pass
    elif new_image.shape[2] == 3:
        new_image = new_image[:, :, ::-1]
    elif new_image.shape[2] == 4:
        new_image = new_image[:, :, [2, 1, 0, 3]]
    new_image = Image.fromarray(new_image)
    return new_image