File size: 7,810 Bytes
31a913a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jantic/DeOldify/blob/master/ImageColorizerColabStable.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **<font color='blue'> Stable Colorizer </font>**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "663IVxfrpIAb"
   },
   "source": [
    "#β—’ DeOldify - Colorize your own photos!\n",
    "\n",
    "####**Credits:**\n",
    "\n",
    "Special thanks to:\n",
    "\n",
    "Matt Robinson and MarΓ­a Benavente for pioneering the DeOldify image colab notebook.  \n",
    "\n",
    "Dana Kelley for doing things, breaking stuff & having an opinion on everything."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ZjPqTBNoohK9"
   },
   "source": [
    "\n",
    "\n",
    "---\n",
    "\n",
    "\n",
    "#β—’ Verify Correct Runtime Settings\n",
    "\n",
    "**<font color='#FF000'> IMPORTANT </font>**\n",
    "\n",
    "In the \"Runtime\" menu for the notebook window, select \"Change runtime type.\" Ensure that the following are selected:\n",
    "* Runtime Type = Python 3\n",
    "* Hardware Accelerator = GPU \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "gaEJBGDlptEo"
   },
   "source": [
    "#β—’ Git clone and install DeOldify"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-T-svuHytJ-8"
   },
   "outputs": [],
   "source": [
    "!git clone https://github.com/jantic/DeOldify.git DeOldify "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cd DeOldify"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "BDFjbNxaadNK"
   },
   "source": [
    "#β—’ Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "00_GcC_trpdE"
   },
   "outputs": [],
   "source": [
    "#NOTE:  This must be the first call in order to work properly!\n",
    "from deoldify import device\n",
    "from deoldify.device_id import DeviceId\n",
    "#choices:  CPU, GPU0...GPU7\n",
    "device.set(device=DeviceId.GPU0)\n",
    "\n",
    "import torch\n",
    "\n",
    "if not torch.cuda.is_available():\n",
    "    print('GPU not available.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "Lsx7xCXNSVt6"
   },
   "outputs": [],
   "source": [
    "!pip install -r requirements-colab.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "MsJa69CMwj3l"
   },
   "outputs": [],
   "source": [
    "import fastai\n",
    "from deoldify.visualize import *\n",
    "\n",
    "torch.backends.cudnn.benchmark = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!mkdir 'models'\n",
    "!wget https://www.dropbox.com/s/usf7uifrctqw9rl/ColorizeStable_gen.pth?dl=0 -O ./models/ColorizeStable_gen.pth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "tzHVnegp21hC"
   },
   "outputs": [],
   "source": [
    "colorizer = get_image_colorizer(artistic=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "BDFjbNxaadNJ"
   },
   "source": [
    "#β—’ Instructions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### source_url\n",
    "Type in a url to a direct link of an image.  Usually that means they'll end in .png, .jpg, etc. NOTE: If you want to use your own image, upload it first to a site like Imgur. \n",
    "\n",
    "### render_factor\n",
    "The default value of 35 has been carefully chosen and should work -ok- for most scenarios (but probably won't be the -best-). This determines resolution at which the color portion of the image is rendered. Lower resolution will render faster, and colors also tend to look more vibrant. Older and lower quality images in particular will generally benefit by lowering the render factor. Higher render factors are often better for higher quality images, but the colors may get slightly washed out. \n",
    "\n",
    "### watermarked\n",
    "Selected by default, this places a watermark icon of a palette at the bottom left corner of the image.  This is intended to be a standard way to convey to others viewing the image that it is colorized by AI. We want to help promote this as a standard, especially as the technology continues to improve and the distinction between real and fake becomes harder to discern. This palette watermark practice was initiated and lead by the company MyHeritage in the MyHeritage In Color feature (which uses a newer version of DeOldify than what you're using here).\n",
    "\n",
    "#### How to Download a Copy\n",
    "Simply right click on the displayed image and click \"Save image as...\"!\n",
    "\n",
    "## Pro Tips\n",
    "\n",
    "You can evaluate how well the image is rendered at each render_factor by using the code at the bottom (that cell under \"See how well render_factor values perform on a frame here\"). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "sUQrbSYipiJn"
   },
   "source": [
    "#β—’ Colorize!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "source_url = '' #@param {type:\"string\"}\n",
    "render_factor = 35  #@param {type: \"slider\", min: 7, max: 40}\n",
    "watermarked = True #@param {type:\"boolean\"}\n",
    "\n",
    "if source_url is not None and source_url !='':\n",
    "    image_path = colorizer.plot_transformed_image_from_url(url=source_url, render_factor=render_factor, compare=True, watermarked=watermarked)\n",
    "    show_image_in_notebook(image_path)\n",
    "else:\n",
    "    print('Provide an image url and try again.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## See how well render_factor values perform on the image here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(10,40,2):\n",
    "    colorizer.plot_transformed_image('test_images/image.png', render_factor=i, display_render_factor=True, figsize=(8,8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "X7Ycv_Y9xAHp"
   },
   "source": [
    "---\n",
    "#βš™ Recommended image sources \n",
    "* [/r/TheWayWeWere](https://www.reddit.com/r/TheWayWeWere/)"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "ImageColorizerColabStable.ipynb",
   "provenance": [],
   "toc_visible": true,
   "version": "0.3.2"
  },
  "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"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}