from ipfml import processing, metrics from PIL import Image from skimage import color import numpy as np def get_svd_data(data_type, block): """ Method which returns the data type expected """ if data_type == 'lab': block_file_path = '/tmp/lab_img.png' block.save(block_file_path) data = processing.get_LAB_L_SVD_s(Image.open(block_file_path)) if data_type == 'mscn_revisited': img_mscn_revisited = processing.rgb_to_mscn(block) # save tmp as img img_output = Image.fromarray(img_mscn_revisited.astype('uint8'), 'L') mscn_revisited_file_path = '/tmp/mscn_revisited_img.png' img_output.save(mscn_revisited_file_path) img_block = Image.open(mscn_revisited_file_path) # extract from temp image data = metrics.get_SVD_s(img_block) if data_type == 'mscn': img_gray = np.array(color.rgb2gray(np.asarray(block))*255, 'uint8') img_mscn = processing.calculate_mscn_coefficients(img_gray, 7) img_mscn_norm = processing.normalize_2D_arr(img_mscn) img_mscn_gray = np.array(img_mscn_norm*255, 'uint8') data = metrics.get_SVD_s(img_mscn_gray) if data_type == 'low_bits_6': low_bits_6 = processing.rgb_to_LAB_L_low_bits(block, 6) data = metrics.get_SVD_s(low_bits_6) if data_type == 'low_bits_5': low_bits_5 = processing.rgb_to_LAB_L_low_bits(block, 5) data = metrics.get_SVD_s(low_bits_5) if data_type == 'low_bits_4': low_bits_4 = processing.rgb_to_LAB_L_low_bits(block, 4) data = metrics.get_SVD_s(low_bits_4) if data_type == 'low_bits_3': low_bits_3 = processing.rgb_to_LAB_L_low_bits(block, 3) data = metrics.get_SVD_s(low_bits_3) if data_type == 'low_bits_2': low_bits_2 = processing.rgb_to_LAB_L_low_bits(block, 2) data = metrics.get_SVD_s(low_bits_2) if data_type == 'low_bits_4_shifted_2': data = metrics.get_SVD_s(processing.rgb_to_LAB_L_bits(block, (3, 6))) return data