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| import numpy as np | |
| import pandas as pd | |
| from PIL import Image | |
| def rgb2df(img): | |
| """ | |
| Convert an RGB image to a DataFrame. | |
| Args: | |
| img (np.ndarray): RGB image. | |
| Returns: | |
| df (pd.DataFrame): DataFrame containing the image data. | |
| """ | |
| 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 df2rgba(img_df): | |
| """ | |
| Convert a DataFrame to an RGB image. | |
| Args: | |
| img_df (pd.DataFrame): DataFrame containing image data. | |
| Returns: | |
| img (np.ndarray): RGB image. | |
| """ | |
| 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 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 |