image preprocesssion function

Author: LinkWoong

LinkGAN/preprocess.py

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+import tensorflow as tf
+import numpy as np
+import io
+import os
+os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
+import cv2
+from Essential import *
+from keras.models import load_model
+import pandas as pd 
+
+def preprocess(image_path, mod_path, content_to_sketch):
+
+	mod = load_model(mod_path)
+	pd.set_option('display.expand_frame_repr', False)
+
+	images = load_image(image_path)
+	new_path = image_path + '/temp'
+
+	for i in range(len(images)):
+
+		temp = resize(images[i])
+		if not os.path.exists(new_path):
+			os.makedirs(new_path)
+		name = new_path + '/resized_' + str(i) + '.jpeg'
+		print name
+
+		cv2.imwrite(name, temp)
+
+	if content_to_sketch:
+		images = load_image(new_path)
+
+		for i in range(len(images)):
+
+			width = float(images[i].shape[1])
+			height = float(images[i].shape[0])
+			depth = float(images[i].shape[2])
+
+			print images[i].shape
+
+			images[i] = images[i].transpose((2, 0, 1))
+
+			light_map = np.zeros(images[i].shape, dtype=np.float)
+
+			for j in range(3):
+				light_map[j] = light_map_single(images[i][j])
+
+			light_map = normalize_pic(light_map)
+			light_map = resize_img_512_3d(light_map)
+
+			line_mat = mod.predict(light_map, batch_size=1)
+			line_mat = line_mat.transpose((3, 1, 2, 0))[0]
+
+			line_mat = line_mat[0:int(height), 0:int(width), :]
+			show_active_img_and_save('sketches', line_mat, './' + str(i) + '.jpeg')
+			line_mat = np.amax(line_mat, 2)
+
+			show_active_img_and_save_denoise_filter2('sketches', line_mat, new_path + '/sketch/sketched_' + str(i) + '.jpeg')
+			show_active_img_and_save_denoise_filter('sketches', line_mat, './' + str(i) + '.jpeg')
+
+			sketch_path = new_path + '/sketch'
+			content_path = new_path
+
+			return content_path, sketch_path