{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
},
"colab": {
"name": "kl_py_kep_stilus_atalakitas.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
""
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "U9poSqZZf01Z",
"colab_type": "text"
},
"source": [
"![TF](https://1.bp.blogspot.com/-eb-_3Aqu5bA/XnertoOpPgI/AAAAAAAAa6Y/8TPaJ8vjn2cN_so7xLeqPZDqX3pQjVARgCLcBGAsYHQ/s200/tf.jpg)\n",
"\n",
"\n",
"# Neural style transfer picures\n",
"\n",
"----\n",
"\n",
"\n",
"A Deep Dream mellett a mély tanulás-vezérelt képmódosításban egy másik jelentős fejlemény, amely 2015 nyarán történt, az idegrendszer\n",
"stílusátadás.\n",
"A neurális stílusátvivő algoritmus sok finomításon mentek keresztül, és sok változata jött létre.\n",
"\n",
"A neurális stílusátvitel abból áll, hogy a referenciakép \"stílusát\" alkalmazzák egy célképre, miközben megőrzi a cél \"tartalmát\".\n",
"\n",
"---\n",
"\n",
"Minta kép stilus átvitelre:\n",
"\n",
"![style transfer](https://1.bp.blogspot.com/-4pVLfMFY1eE/Xne0fcLF0QI/AAAAAAAAa6k/ijKMpn7aUUYJJERkXyPmHmFKDAcwMXNZgCLcBGAsYHQ/s400/silus_atvitel.jpg)\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "mwMP8sLHf01S",
"colab_type": "code",
"colab": {},
"outputId": "fdced301-fca1-41ac-cb5f-667c1a5055f6"
},
"source": [
"import keras\n",
"keras.__version__"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"Using TensorFlow backend.\n"
],
"name": "stderr"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"'2.3.1'"
]
},
"metadata": {
"tags": []
},
"execution_count": 2
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "nDqX3xm4f01a",
"colab_type": "text"
},
"source": [
"\n",
"---\n",
"\n",
"A \"stílus\" alatt lényegében a textúrák, a színek és a képi minták szerepelnek, különféle térbeli skálákban, míg a \"tartalom\" a kép magasabb szintű makrostruktúrája. \n",
"\n",
"Például a kék-sárga kör alakú ecsetvonásokat a fenti példában \"stílusnak\" tekintik a Van Gogh Csillagos éjszaka felhasználásával, míg a Tuebingen fényképén szereplő épületek \"tartalomnak\" tekinthetők.\n",
"\n",
"A stílusátvitel gondolatának, amely szorosan összekapcsolódik a textúragenerációval, hosszú ideje volt a képfeldolgozó közösségben, mielőtt 2015-ben kifejlesztette a neurális stílusátadást.\n",
"\n",
" Mint azonban kiderült, a stílus mély, tanuláson alapuló megvalósítása Az átadás olyan páratlan eredményeket hozott, amelyek összehasonlíthatatlanok voltak abban, amit korábban el lehet érni a klasszikus számítógépes látástechnikákkal, és elképesztő reneszánst váltott ki a számítógépes látás kreatív alkalmazásaiban.\n",
"\n",
" ---\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "I7ygaroof01b",
"colab_type": "text"
},
"source": [
"```\n",
"loss = distance(style(reference_image) - style(generated_image)) +\n",
" distance(content(original_image) - content(generated_image))\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "jb7MKYUgf01c",
"colab_type": "text"
},
"source": [
"---\n",
"\n",
"Ennek a veszteségnek a minimalizálása azt eredményezi, hogy a \"stílus (létrehozott kép)\" közel áll a \"stílus (referencia_kép)\", míg a \"tartalom (létrehozott kép)\" közel kell lennie a \"tartalomhoz (létrehozott kép)\", ezáltal elérheti a stílusátadást, ahogyan azt meghatároztuk.\n",
"\n",
"Gatys és munkatársainak egyik alapvető megfigyelése az, hogy a mély konvolúciós neurális hálózatok pontosan lehetőséget kínálnak a matematikai meghatározásra\n",
"a \"stílus\" és a \"tartalom\" funkciókat.\n",
"\n",
"A stílusátvitel megvalósításának kulcseleme ugyanaz az ötlet, amely központi jelentőségű az összes mélyreható tanulási algoritmusban: meghatározunk egy veszteségfüggvényt annak meghatározására, hogy mit akarunk elérni, és minimalizáljuk ezt a veszteséget.\n",
"\n",
" Tudjuk, mit akarunk elérni: őrizzük meg az eredeti kép \"tartalmát\", miközben elfogadjuk a referenciakép \"stílusát\". \n",
" \n",
" Ha képesek lennénk matematikailag meghatározni a tartalmat és a stílust, akkor a minimalizálás megfelelő veszteségfüggvénye a következő:\n",
" \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "tekxeyCDf01d",
"colab_type": "text"
},
"source": [
"## A tartalom elvesztése\n",
"\n",
"Mint már tudjuk, a hálózat korábbi rétegeiből származó aktiválások helyi információkat tartalmaznak a képről, míg a magasabb rétegekből származó aktiválások egyre inkább globális és elvont információkat tartalmaznak. \n",
"\n",
"Másképpen megfogalmazva a convnet különféle rétegeinek aktiválása a kép tartalmának lebontását teszi lehetővé különböző térbeli skálán. \n",
"\n",
"Ezért elvárjuk, hogy egy kép globálisabb és elvontabb \"tartalmát\" a convnet felső rétegének ábrázolása megragadja.\n",
"\n",
"A tartalomvesztés megfelelő jelöltje tehát egy előre kiképzett konvnet mérlegelése, és veszteségként meghatározza az L2 normát a felső képen kiszámított felső réteg aktiválása és a generált képen kiszámított ugyanazon réteg aktiválása között. \n",
" Ez garantálná, hogy a convnet felső rétegéből látható, hogy a létrehozott kép \"hasonlít\" az eredeti célképhez. Feltételezve, hogy a convnet felső rétegei valójában a bemenő képek „tartalma”, akkor ez a képtartalom megőrzésének módja."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6cl_DvoDf01e",
"colab_type": "text"
},
"source": [
"## A stílusvesztés\n",
"\n",
"Míg a tartalomvesztés csak egyetlen magasabb szintű réteget von maga után.\n",
"A papír a convnet több rétegét használja ki: a stílus-referenciakép megjelenését arra törekszünk, hogy az összes convnet által kivont térbeli skálán, és ne csak egyetlen skálán szerepeljen.\n",
"\n",
"A stílus elvesztése érdekében a Gatys et al. A papír kihasználja a réteg aktiválásának \"Gram-mátrixát\", azaz az adott réteg jellemzőinek térképei közötti belső terméket. Ez a belső termék úgy értelmezhető, hogy egy réteg jellemzői közötti összefüggések térképét ábrázolja. \n",
"\n",
"Ezek a tulajdonságkorrelációk rögzítik egy adott térbeli skála mintázatainak statisztikáit, amelyek empirikusan megfelelnek az ezen a skálán található textúrák megjelenésének.\n",
"\n",
"Ezért a stílusvesztés célja a hasonló belső összefüggések megőrzése a különböző rétegek aktiválása során, a stílus referenciaképen és a létrehozott képen. \n",
"\n",
"Ez viszont garantálja, hogy a különféle térbeli skálákban található textúrák hasonlóak lesznek a stílus-referenciaképen és a létrehozott képen\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "v0OzuZxtf01f",
"colab_type": "text"
},
"source": [
"## Röviden\n",
"\n",
" egy előre képzett konvnet segítségével meghatározhatjuk a veszteséget, amely:\n",
"\n",
"A tartalom megőrzése hasonló magas szintű rétegek aktiválásának fenntartásával a céltartalom-kép és a létrehozott kép között. \n",
"\n",
"A konvnetnek \"látnia\" kell a célképet és a létrehozott képet, mint \"ugyanazokat a dolgokat tartalmazza\".\n",
"\n",
"A stílus megőrzése érdekében hasonló korrelációkat kell fenntartani az aktiválások során mind az alacsony, mind a magas szintű rétegekre. Valójában a tulajdonságkorrelációk rögzítik a textúrákat: a létrehozott és a stílus referenciaképnek ugyanazon textúráknak kell lennie különböző térbeli skálákban.\n",
"\n",
"\n",
"Most vessünk egy pillantást az eredeti 2015 idegi stílusú átviteli algoritmus Keras megvalósítására. Mint láthatja, sok hasonlóságot mutat az előző szakaszban kifejlesztett Deep Dream megvalósítással."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "y8rkRUbZf01g",
"colab_type": "text"
},
"source": [
"\n",
"\n",
"## Neurális stílusátvitel Kerasban\n",
"\n",
"A neurális stílusátvitel bármilyen előre képzett konvnet segítségével megvalósítható. Itt a VGG19 hálózatot fogjuk használni, amelyet Gatys és társai használtak a cikkükben. A VGG19 az 5. fejezetben bemutatott VGG16 hálózat egyszerű változata, három további konvolúciós réteggel.\n",
"\n",
"Ez az általános folyamatunk:\n",
"\n",
"Állítson be egy hálózatot, amely kiszámítja a VGG19 réteg aktiválásait a stílus referenciakép, a célkép és a generált kép számára egyidejűleg.\n",
"A fenti három képen kiszámított réteg aktiválásokkal határozhatja meg a fent leírt veszteségfüggvényt, amelyet minimalizálunk a stílusátvitel elérése érdekében.\n",
"\n",
"Állítson be egy gradiens leszállási folyamatot ennek a veszteség funkciónak a minimalizálása érdekében.\n",
"\n",
"Kezdjük azzal, hogy meghatározzuk a figyelembe vett két kép elérési útját: a stílus referenciaképet és a cél képet. Annak biztosítása érdekében, hogy az összes feldolgozott kép hasonló méretű legyen (széles körben eltérő méretek megnehezítik a stílusátvitelt), később átméretezzük mindegyik megosztott 400px magasságot."
]
},
{
"cell_type": "code",
"metadata": {
"id": "G0w87xLBf01h",
"colab_type": "code",
"colab": {}
},
"source": [
"from keras.preprocessing.image import load_img, img_to_array\n",
"\n",
"# This is the path to the image you want to transform.\n",
"target_image_path = 'Tubingen.jpg'\n",
"# This is the path to the style image.\n",
"style_reference_image_path = 'transfer_style_reference.jpg'\n",
"\n",
"# Dimensions of the generated picture.\n",
"width, height = load_img(target_image_path).size\n",
"img_height = 400\n",
"img_width = int(width * img_height / height)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true,
"id": "yFLt6Rf9f01j",
"colab_type": "text"
},
"source": [
"Szükségünk lesz néhány kiegészítő funkcióra a VGG19 konvnetbe be- és kimenő képek betöltéséhez, előfeldolgozásához és utófeldolgozásához:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "pwZP1fM-f01k",
"colab_type": "code",
"colab": {}
},
"source": [
"import numpy as np\n",
"from keras.applications import vgg19\n",
"\n",
"def preprocess_image(image_path):\n",
" img = load_img(image_path, target_size=(img_height, img_width))\n",
" img = img_to_array(img)\n",
" img = np.expand_dims(img, axis=0)\n",
" img = vgg19.preprocess_input(img)\n",
" return img\n",
"\n",
"def deprocess_image(x):\n",
" # Remove zero-center by mean pixel\n",
" x[:, :, 0] += 103.939\n",
" x[:, :, 1] += 116.779\n",
" x[:, :, 2] += 123.68\n",
" # 'BGR'->'RGB'\n",
" x = x[:, :, ::-1]\n",
" x = np.clip(x, 0, 255).astype('uint8')\n",
" return x"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "PCKg-ijrf01o",
"colab_type": "text"
},
"source": [
"\n",
"Állítsuk be a VGG19 hálózatot. Bemenetként három képből álló köteget vesz fel: a stílus referenciaképet, a célképet és egy helyőrzőt, amely a létrehozott képet tartalmazza. A helyőrző egyszerűen szimbolikus tenzor, amelynek értékét a Numpy tömbök külsőleg biztosítják. A stílushivatkozás és a célkép statikus, tehát a K.constant felhasználásával definiálhatók, míg a létrehozott kép helyőrzőjében szereplő értékek idővel megváltoznak.\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "tnudHyHyf01p",
"colab_type": "code",
"colab": {},
"outputId": "ed700c0b-7ac8-4196-f211-76b05e32f134"
},
"source": [
"from keras import backend as K\n",
"\n",
"target_image = K.constant(preprocess_image(target_image_path))\n",
"style_reference_image = K.constant(preprocess_image(style_reference_image_path))\n",
"\n",
"# This placeholder will contain our generated image\n",
"combination_image = K.placeholder((1, img_height, img_width, 3))\n",
"\n",
"# We combine the 3 images into a single batch\n",
"input_tensor = K.concatenate([target_image,\n",
" style_reference_image,\n",
" combination_image], axis=0)\n",
"\n",
"# We build the VGG19 network with our batch of 3 images as input.\n",
"# The model will be loaded with pre-trained ImageNet weights.\n",
"model = vgg19.VGG19(input_tensor=input_tensor,\n",
" weights='imagenet',\n",
" include_top=False)\n",
"print('Model loaded.')"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"Model loaded.\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "gxpCy-qUf01s",
"colab_type": "text"
},
"source": [
"\n",
"Definiáljuk a tartalomvesztést, amelynek célja annak biztosítása, hogy a VGG19 konvnet felső rétegének hasonló képe legyen a célkép és a létrehozott kép szempontjából:\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "pckBT1Hlf01s",
"colab_type": "code",
"colab": {}
},
"source": [
"def content_loss(base, combination):\n",
" return K.sum(K.square(combination - base))"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "mHUTXs5Yf01v",
"colab_type": "text"
},
"source": [
"\n",
"Ez stílusvesztés. Mely hív egy segédfunkciót a bemeneti mátrix Gram mátrixának kiszámításához, vagyis az eredeti jellemző mátrixban található korrelációk térképét.\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "psWlSuCQf01w",
"colab_type": "code",
"colab": {}
},
"source": [
"def gram_matrix(x):\n",
" features = K.batch_flatten(K.permute_dimensions(x, (2, 0, 1)))\n",
" gram = K.dot(features, K.transpose(features))\n",
" return gram\n",
"\n",
"\n",
"def style_loss(style, combination):\n",
" S = gram_matrix(style)\n",
" C = gram_matrix(combination)\n",
" channels = 3\n",
" size = img_height * img_width\n",
" return K.sum(K.square(S - C)) / (4. * (channels ** 2) * (size ** 2))"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "tBn13tgzf01y",
"colab_type": "text"
},
"source": [
"\n",
"\n",
"\n",
"E két veszteségkomponenshez hozzáadunk egy harmadik, a \"teljes variációs veszteséget\". Ennek célja a generált kép térbeli folytonosságának ösztönzése, ezáltal elkerülve a túlságosan pixelesített eredményeket. Ezt úgy lehet értelmezni, mint egy rendezési veszteséget.\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "ew_IEoa3f01z",
"colab_type": "code",
"colab": {}
},
"source": [
"def total_variation_loss(x):\n",
" a = K.square(\n",
" x[:, :img_height - 1, :img_width - 1, :] - x[:, 1:, :img_width - 1, :])\n",
" b = K.square(\n",
" x[:, :img_height - 1, :img_width - 1, :] - x[:, :img_height - 1, 1:, :])\n",
" return K.sum(K.pow(a + b, 1.25))"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "JxZ4hL-Zf011",
"colab_type": "text"
},
"source": [
"\n",
"A minimalizált veszteség e három veszteség súlyozott átlaga. A tartalomvesztés kiszámításához csak egy felső réteget, a block5_conv2 réteget használjuk fel, míg a stílusvesztéshez a rétegek listáját használjuk, mint az alacsony és a magas szintű rétegeket is. \n",
"\n",
"Összeadjuk a teljes variációs veszteséget a végén.\n",
"\n",
"Attól függően, hogy milyen stílus-referenciaképet és tartalmi képet használ, akkor valószínűleg be szeretné állítani a tartalom-súly együtthatót, a tartalom veszteség hozzájárulását a teljes veszteséghez. A magasabb tartalmi súly azt jelenti, hogy a céltartalom jobban felismerhető lesz a létrehozott képen.\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "Zk5zGH4uf012",
"colab_type": "code",
"colab": {}
},
"source": [
"# Dict mapping layer names to activation tensors\n",
"outputs_dict = dict([(layer.name, layer.output) for layer in model.layers])\n",
"# Name of layer used for content loss\n",
"content_layer = 'block5_conv2'\n",
"# Name of layers used for style loss\n",
"style_layers = ['block1_conv1',\n",
" 'block2_conv1',\n",
" 'block3_conv1',\n",
" 'block4_conv1',\n",
" 'block5_conv1']\n",
"# Weights in the weighted average of the loss components\n",
"total_variation_weight = 1e-4\n",
"style_weight = 1.\n",
"content_weight = 0.025\n",
"\n",
"# Define the loss by adding all components to a `loss` variable\n",
"loss = K.variable(0.)\n",
"layer_features = outputs_dict[content_layer]\n",
"target_image_features = layer_features[0, :, :, :]\n",
"combination_features = layer_features[2, :, :, :]\n",
"loss = loss + (content_weight * content_loss(target_image_features, combination_features))\n",
"for layer_name in style_layers:\n",
" layer_features = outputs_dict[layer_name]\n",
" style_reference_features = layer_features[1, :, :, :]\n",
" combination_features = layer_features[2, :, :, :]\n",
" sl = style_loss(style_reference_features, combination_features)\n",
" loss += (style_weight / len(style_layers)) * sl\n",
"loss += total_variation_weight * total_variation_loss(combination_image)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "SYedqASKf014",
"colab_type": "text"
},
"source": [
"\n",
"Végül beállítottuk a gradiens leszállási folyamatot. Az eredeti Gatys-al. papír, az optimalizálást az L-BFGS algoritmussal hajtjuk végre, ezért ezt is itt fogjuk használni. \n",
"\n",
"Ez lényeges különbség az előző szakaszban szereplő Deep Dream példához képest. \n",
"\n",
"Az L-BFGS algoritmusok a SciPy-vel vannak csomagolva. A SciPy implementációnak azonban két enyhe korlátozása van:\n",
"\n",
"Meg kell adni a veszteségfüggvény és a gradiensek értékét, mint két különálló funkciót.\n",
"\n",
"Csak lapos vektorokra alkalmazható, míg 3D-s képtömbünk van.\n",
"\n",
"Nagyon nem lenne hatékony a veszteségfüggvény és a színátmenetek értékének független kiszámítása, mivel sok redundáns számításhoz vezetne a kettő között. \n",
"\n",
"Szinte kétszer lassabbak lennénk, mint amennyire csak tudnánk, ha közösen számolnánk őket. Ennek elkerüléséhez felállítottuk az értékelõ nevû Python osztályt, amely kiszámítja mind a veszteség értékét, mind a színátmenetek értékét, visszaadja a veszteség értékét, amikor elsõ alkalommal hívják, és tárolja a következõ hívás színátmeneteit.\n",
"\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "-z-r_n9zf015",
"colab_type": "code",
"colab": {}
},
"source": [
"# Get the gradients of the generated image wrt the loss\n",
"grads = K.gradients(loss, combination_image)[0]\n",
"\n",
"# Function to fetch the values of the current loss and the current gradients\n",
"fetch_loss_and_grads = K.function([combination_image], [loss, grads])\n",
"\n",
"\n",
"class Evaluator(object):\n",
"\n",
" def __init__(self):\n",
" self.loss_value = None\n",
" self.grads_values = None\n",
"\n",
" def loss(self, x):\n",
" assert self.loss_value is None\n",
" x = x.reshape((1, img_height, img_width, 3))\n",
" outs = fetch_loss_and_grads([x])\n",
" loss_value = outs[0]\n",
" grad_values = outs[1].flatten().astype('float64')\n",
" self.loss_value = loss_value\n",
" self.grad_values = grad_values\n",
" return self.loss_value\n",
"\n",
" def grads(self, x):\n",
" assert self.loss_value is not None\n",
" grad_values = np.copy(self.grad_values)\n",
" self.loss_value = None\n",
" self.grad_values = None\n",
" return grad_values\n",
"\n",
"evaluator = Evaluator()"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "o3pXO_I8f017",
"colab_type": "text"
},
"source": [
"\n",
"Végül futtathatjuk a gradiens-emelkedési folyamatot a SciPy L-BFGS algoritmusának felhasználásával, az algoritmus minden egyes iterációjánál mentve az aktuálisan generált képet (itt egyetlen iteráció képviseli a gradiens-emelkedés 20 lépését):\n"
]
},
{
"cell_type": "code",
"metadata": {
"id": "JzqKIwnIf018",
"colab_type": "code",
"colab": {},
"outputId": "717efe39-b348-47b9-df2a-0bf0684b6c31"
},
"source": [
"from scipy.optimize import fmin_l_bfgs_b\n",
"## from scipy.misc import imsave // megszünt\n",
"import imageio\n",
"import time\n",
"\n",
"result_prefix = 'style_transfer_result'\n",
"iterations = 20\n",
"\n",
"# Run scipy-based optimization (L-BFGS) over the pixels of the generated image\n",
"# so as to minimize the neural style loss.\n",
"# This is our initial state: the target image.\n",
"# Note that `scipy.optimize.fmin_l_bfgs_b` can only process flat vectors.\n",
"x = preprocess_image(target_image_path)\n",
"x = x.flatten()\n",
"for i in range(iterations):\n",
" print('Start of iteration', i)\n",
" start_time = time.time()\n",
" x, min_val, info = fmin_l_bfgs_b(evaluator.loss, x, fprime=evaluator.grads, maxfun=20)\n",
" print('Current loss value:', min_val)\n",
" # Save current generated image\n",
" img = x.copy().reshape((img_height, img_width, 3))\n",
" img = deprocess_image(img)\n",
" fname = result_prefix + '_at_iteration_%d.png' % i\n",
"# imsave(fname, img)\n",
" imageio.imwrite(fname, img)\n",
" end_time = time.time()\n",
" print('Image saved as', fname)\n",
" print('Iteration %d completed in %ds' % (i, end_time - start_time))"
],
"execution_count": 0,
"outputs": [
{
"output_type": "stream",
"text": [
"Start of iteration 0\n",
"Current loss value: 1639755600.0\n",
"Image saved as style_transfer_result_at_iteration_0.png\n",
"Iteration 0 completed in 249s\n",
"Start of iteration 1\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "xxc0pqOdf02A",
"colab_type": "code",
"colab": {}
},
"source": [
"import imageio\n",
"##imageio.imwrite('filename.jpg', array)"
],
"execution_count": 0,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "mBgMMPRAf02D",
"colab_type": "text"
},
"source": [
"Ezt kapjuk:"
]
},
{
"cell_type": "code",
"metadata": {
"id": "lgM4UWaef02D",
"colab_type": "code",
"colab": {},
"outputId": "d6655224-e0ef-4422-b5c4-8c1e9a2cf074"
},
"source": [
"from matplotlib import pyplot as plt\n",
"\n",
"# Content image\n",
"plt.imshow(load_img(target_image_path, target_size=(img_height, img_width)))\n",
"plt.figure()\n",
"\n",
"# Style image\n",
"plt.imshow(load_img(style_reference_image_path, target_size=(img_height, img_width)))\n",
"plt.figure()\n",
"\n",
"# Generate image\n",
"plt.imshow(img)\n",
"plt.show()"
],
"execution_count": 0,
"outputs": [
{
"output_type": "error",
"ename": "NameError",
"evalue": "name 'img' is not defined",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 11\u001b[0m \u001b[1;31m# Generate image\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mimg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 13\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mNameError\u001b[0m: name 'img' is not defined"
]
},
{
"output_type": "display_data",
"data": {
"image/png": "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\n",
"text/plain": [
"