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