Merge remote-tracking branch 'upstream/master'

.vscode/settings.json

@@ -1,4 +0,0 @@
-{
-    "python.pythonPath": "/home/jason/anaconda3/envs/fastaiv1/bin/python",
-    "python.linting.enabled": true
-}

ColorizeTrainingArtistic.ipynb

@@ -111,7 +111,7 @@
     "            o.save(path_gen/names[i].name)\n",
     "            i += 1\n",
     "    \n",
-    "def save_gen_images(learn_gen):\n",
+    "def save_gen_images():\n",
     "    if path_gen.exists(): shutil.rmtree(path_gen)\n",
     "    path_gen.mkdir(exist_ok=True)\n",
     "    data_gen = get_data(bs=bs, sz=sz, keep_pct=0.085)\n",
@@ -418,7 +418,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "save_gen_images(gen_name)"
+    "save_gen_images()"
    ]
   },
   {

ColorizeTrainingStable.ipynb

@@ -111,7 +111,7 @@
     "            o.save(path_gen/names[i].name)\n",
     "            i += 1\n",
     "    \n",
-    "def save_gen_images(learn_gen):\n",
+    "def save_gen_images():\n",
     "    if path_gen.exists(): shutil.rmtree(path_gen)\n",
     "    path_gen.mkdir(exist_ok=True)\n",
     "    data_gen = get_data(bs=bs, sz=sz, keep_pct=0.085)\n",
@@ -418,7 +418,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "save_gen_images(gen_name)"
+    "save_gen_images()"
    ]
   },
   {

ColorizeTrainingStableLargeBatch.ipynb

@@ -0,0 +1,779 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Stable Model Training (Large Batch/Limited GPU Memory Support)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## IMPORTANT: Training has -not- been verified by myself for this notebook ~jantic"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### NOTES:  \n",
+    "* This is \"NoGAN\" based training, described in the DeOldify readme.\n",
+    "* This model prioritizes stable and reliable renderings.  It does particularly well on portraits and landscapes.  It's not as colorful as the artistic model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.environ['CUDA_VISIBLE_DEVICES']='0' "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import fastai\n",
+    "from fastai import *\n",
+    "from fastai.vision import *\n",
+    "from fastai.callbacks.tensorboard import *\n",
+    "from fastai.vision.gan import *\n",
+    "from fasterai.generators import *\n",
+    "from fasterai.critics import *\n",
+    "from fasterai.dataset import *\n",
+    "from fasterai.loss import *\n",
+    "from fasterai.save import *\n",
+    "from PIL import Image, ImageDraw, ImageFont\n",
+    "from PIL import ImageFile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Activate Large Model Support for PyTorch\n",
+    "This will allow us to fit the model within a GPU with smaller memory capacity (e.g. GTX 1070 8Gb)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Large Model Support (LMS) is a feature provided in IBM Watson Machine Learning Community Edition (WML-CE) PyTorch V1.1.0 that allows the successful training of deep learning models that would otherwise exhaust GPU memory and abort with “out-of-memory” errors. LMS manages this oversubscription of GPU memory by temporarily swapping tensors to host memory when they are not needed. One or more elements of a deep learning model can lead to GPU memory exhaustion.\n",
+    "\n",
+    "Requires the use of IBM WML-CE (Available here: https://www.ibm.com/support/knowledgecenter/en/SS5SF7_1.6.1/welcome/welcome.html)\n",
+    "\n",
+    "Further Reading on PyTorch with Large Model Support: https://www.ibm.com/support/knowledgecenter/en/SS5SF7_1.6.1/navigation/wmlce_getstarted_pytorch.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import shutil"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set limit of GPU used before swapping to tensors to host memory\n",
+    "max_gpu_mem = 7\n",
+    "\n",
+    "def gb_to_bytes(gb):\n",
+    "    return gb*1024*1024*1024\n",
+    "\n",
+    "# Enable PyTorch LMS\n",
+    "torch.cuda.set.enabled_lms(True)\n",
+    "# Set LMS limit\n",
+    "torch.cuda.set_limit_lms(gb_to_bytes(max_gpu_mem))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Check LMS is enabled\n",
+    "torch.cuda.get_enabled_lms()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Check LMS Limit has been set\n",
+    "torch.cuda.get_limit_lms()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Path to Training Data\n",
+    "path = Path('data/imagenet/ILSVRC/Data/CLS-LOC')\n",
+    "path_hr = path\n",
+    "\n",
+    "# Path to Black and White images\n",
+    "path_bandw = Path('/training/DeOldify')\n",
+    "path_lr = path_bandw/'bandw'\n",
+    "\n",
+    "# Name of Model\n",
+    "proj_id = 'StableModel'\n",
+    "\n",
+    "# Name of Generator\n",
+    "gen_name = proj_id + '_gen'\n",
+    "pre_gen_name = gen_name + '_0'\n",
+    "\n",
+    "# Name of Critic\n",
+    "crit_name = proj_id + '_crit'\n",
+    "\n",
+    "# Name of Generated Images folder, located within the Black and White folder\n",
+    "name_gen = proj_id + '_image_gen'\n",
+    "path_gen = path/name_gen\n",
+    "\n",
+    "# Path to tensorboard data\n",
+    "TENSORBOARD_PATH = Path('data/tensorboard/' + proj_id)\n",
+    "\n",
+    "nf_factor = 2\n",
+    "pct_start = 1e-8\n",
+    "\n",
+    "# Number of workers for DataLoader\n",
+    "num_works = 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_data(bs:int, sz:int, keep_pct:float):\n",
+    "    return get_colorize_data(sz=sz, bs=bs, crappy_path=path_lr, good_path=path_hr, \n",
+    "                             random_seed=None, keep_pct=keep_pct, num_workers=num_works)\n",
+    "\n",
+    "def get_crit_data(classes, bs, sz):\n",
+    "    src = ImageList.from_folder(path, include=classes, recurse=True).random_split_by_pct(0.1, seed=42)\n",
+    "    ll = src.label_from_folder(classes=classes)\n",
+    "    data = (ll.transform(get_transforms(max_zoom=2.), size=sz)\n",
+    "           .databunch(bs=bs).normalize(imagenet_stats))\n",
+    "    return data\n",
+    "\n",
+    "def create_training_images(fn,i):\n",
+    "    dest = path_lr/fn.relative_to(path_hr)\n",
+    "    dest.parent.mkdir(parents=True, exist_ok=True)\n",
+    "    img = PIL.Image.open(fn).convert('LA').convert('RGB')\n",
+    "    img.save(dest)  \n",
+    "    \n",
+    "def save_preds(dl):\n",
+    "    i=0\n",
+    "    names = dl.dataset.items\n",
+    "    \n",
+    "    for b in dl:\n",
+    "        preds = learn_gen.pred_batch(batch=b, reconstruct=True)\n",
+    "        for o in preds:\n",
+    "            o.save(path_gen/names[i].name)\n",
+    "            i += 1\n",
+    "    \n",
+    "def save_gen_images():\n",
+    "    if path_gen.exists(): shutil.rmtree(path_gen)\n",
+    "    path_gen.mkdir(exist_ok=True)\n",
+    "    data_gen = get_data(bs=bs, sz=sz, keep_pct=0.085)\n",
+    "    save_preds(data_gen.fix_dl)\n",
+    "    PIL.Image.open(path_gen.ls()[0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create black and white training images"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Only runs if the directory isn't already created."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if not path_lr.exists():\n",
+    "    il = ImageList.from_folder(path_hr)\n",
+    "    parallel(create_training_images, il.items)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Pre-train generator"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### NOTE\n",
+    "Most of the training takes place here in pretraining for NoGAN.  The goal here is to take the generator as far as possible with conventional training, as that is much easier to control and obtain glitch-free results compared to GAN training."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 64px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bs=88 # This can be increased if using PyTorch LMS, training could be slower.\n",
+    "sz=64\n",
+    "keep_pct=1.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_gen = get_data(bs=bs, sz=sz, keep_pct=keep_pct)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen = gen_learner_wide(data=data_gen, gen_loss=FeatureLoss(), nf_factor=nf_factor)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.callback_fns.append(partial(ImageGenTensorboardWriter, base_dir=TENSORBOARD_PATH, name='GenPre'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.fit_one_cycle(1, pct_start=0.8, max_lr=slice(1e-3))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.save(pre_gen_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.unfreeze()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.fit_one_cycle(1, pct_start=pct_start,  max_lr=slice(3e-7, 3e-4))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.save(pre_gen_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 128px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bs=40 # This can be increased if using PyTorch LMS, training could be slower.\n",
+    "sz=128\n",
+    "keep_pct=1.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.data = get_data(sz=sz, bs=bs, keep_pct=keep_pct)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.unfreeze()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.fit_one_cycle(1, pct_start=pct_start, max_lr=slice(1e-7,1e-4))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.save(pre_gen_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 192px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bs=16 # This can be increased if using PyTorch LMS, training could be slower.\n",
+    "sz=192\n",
+    "keep_pct=0.50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.data = get_data(sz=sz, bs=bs, keep_pct=keep_pct)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.unfreeze()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.fit_one_cycle(1, pct_start=pct_start, max_lr=slice(5e-8,5e-5))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.save(pre_gen_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 256px"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bs=8 # This can be increased if using PyTorch LMS, training could be slower.\n",
+    "sz=256\n",
+    "keep_pct=0.50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.data = get_data(sz=sz, bs=bs, keep_pct=keep_pct)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.unfreeze()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.fit_one_cycle(1, pct_start=pct_start, max_lr=slice(5e-8,5e-5))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen.save(pre_gen_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Repeatable GAN Cycle"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### NOTE\n",
+    "Best results so far have been based on repeating the cycle below a few times (about 5-8?), until diminishing returns are hit (no improvement in image quality).  Each time you repeat the cycle, you want to increment that old_checkpoint_num by 1 so that new check points don't overwrite the old.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "old_checkpoint_num = 0\n",
+    "checkpoint_num = old_checkpoint_num + 1\n",
+    "gen_old_checkpoint_name = gen_name + '_' + str(old_checkpoint_num)\n",
+    "gen_new_checkpoint_name = gen_name + '_' + str(checkpoint_num)\n",
+    "crit_old_checkpoint_name = crit_name + '_' + str(old_checkpoint_num)\n",
+    "crit_new_checkpoint_name= crit_name + '_' + str(checkpoint_num)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Save Generated Images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bs=8\n",
+    "sz=256"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen = gen_learner_wide(data=data_gen, gen_loss=FeatureLoss(), nf_factor=nf_factor).load(gen_old_checkpoint_name, with_opt=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "save_gen_images()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Pretrain Critic"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Only need full pretraining of critic when starting from scratch.  Otherwise, just finetune!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if old_checkpoint_num == 0:\n",
+    "    bs=64\n",
+    "    sz=128\n",
+    "    learn_gen=None\n",
+    "    gc.collect()\n",
+    "    data_crit = get_crit_data([name_gen, 'test'], bs=bs, sz=sz)\n",
+    "    data_crit.show_batch(rows=3, ds_type=DatasetType.Train, imgsize=3)\n",
+    "    learn_critic = colorize_crit_learner(data=data_crit, nf=256)\n",
+    "    learn_critic.callback_fns.append(partial(LearnerTensorboardWriter, base_dir=TENSORBOARD_PATH, name='CriticPre'))\n",
+    "    learn_critic.fit_one_cycle(6, 1e-3)\n",
+    "    learn_critic.save(crit_old_checkpoint_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "bs=8\n",
+    "sz=256"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_crit = get_crit_data([name_gen, 'test'], bs=bs, sz=sz)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_crit.show_batch(rows=3, ds_type=DatasetType.Train, imgsize=3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_critic = colorize_crit_learner(data=data_crit, nf=256).load(crit_old_checkpoint_name, with_opt=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_critic.callback_fns.append(partial(LearnerTensorboardWriter, base_dir=TENSORBOARD_PATH, name='CriticPre'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_critic.fit_one_cycle(4, 1e-4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_critic.save(crit_new_checkpoint_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### GAN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_crit=None\n",
+    "learn_gen=None\n",
+    "gc.collect()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lr=2e-5\n",
+    "sz=256\n",
+    "bs=5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data_crit = get_crit_data([name_gen, 'test'], bs=bs, sz=sz)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_crit = colorize_crit_learner(data=data_crit, nf=256).load(crit_new_checkpoint_name, with_opt=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn_gen = gen_learner_wide(data=data_gen, gen_loss=FeatureLoss(), nf_factor=nf_factor).load(gen_old_checkpoint_name, with_opt=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "switcher = partial(AdaptiveGANSwitcher, critic_thresh=0.65)\n",
+    "learn = GANLearner.from_learners(learn_gen, learn_crit, weights_gen=(1.0,1.5), show_img=False, switcher=switcher,\n",
+    "                                 opt_func=partial(optim.Adam, betas=(0.,0.9)), wd=1e-3)\n",
+    "learn.callback_fns.append(partial(GANDiscriminativeLR, mult_lr=5.))\n",
+    "learn.callback_fns.append(partial(GANTensorboardWriter, base_dir=TENSORBOARD_PATH, name='GanLearner', visual_iters=100))\n",
+    "learn.callback_fns.append(partial(GANSaveCallback, learn_gen=learn_gen, filename=gen_new_checkpoint_name, save_iters=100))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Instructions:  \n",
+    "Find the checkpoint just before where glitches start to be introduced.  This is all very new so you may need to play around with just how far you go here with keep_pct."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn.data = get_data(sz=sz, bs=bs, keep_pct=0.03)\n",
+    "learn_gen.freeze_to(-1)\n",
+    "learn.fit(1,lr)"
+   ]
+  }
+ ],
+ "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": "3.7.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

ColorizeTrainingVideo.ipynb

@@ -105,7 +105,7 @@
     "            o.save(path_gen/names[i].name)\n",
     "            i += 1\n",
     "            \n",
-    "def save_gen_images(learn_gen):\n",
+    "def save_gen_images():\n",
     "    if path_gen.exists(): shutil.rmtree(path_gen)\n",
     "    path_gen.mkdir(exist_ok=True)\n",
     "    data_gen = get_data(bs=bs, sz=sz, keep_pct=0.085)\n",
@@ -262,7 +262,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "save_gen_images(gen_name)"
+    "save_gen_images()"
    ]
   },
   {

Dockerfile

@@ -2,7 +2,7 @@ From nvcr.io/nvidia/pytorch:19.04-py3
 
 RUN apt-get -y update
 
-RUN apt-get install -y python3-pip software-properties-common wget
+RUN apt-get install -y python3-pip software-properties-common wget ffmpeg
 
 RUN add-apt-repository ppa:git-core/ppa
 

Dockerfile-api

@@ -0,0 +1,46 @@
+From nvcr.io/nvidia/pytorch:19.04-py3
+
+RUN apt-get -y update
+
+RUN apt-get install -y python3-pip software-properties-common wget ffmpeg
+
+RUN add-apt-repository ppa:git-core/ppa
+
+RUN apt-get -y update
+
+RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
+
+RUN apt-get install -y git-lfs --allow-unauthenticated
+
+RUN git lfs install
+
+ENV GIT_WORK_TREE=/data
+
+RUN mkdir -p /root/.torch/models
+
+RUN mkdir -p /data/models
+
+RUN wget -O /root/.torch/models/vgg16_bn-6c64b313.pth https://download.pytorch.org/models/vgg16_bn-6c64b313.pth
+
+RUN wget -O /root/.torch/models/resnet34-333f7ec4.pth https://download.pytorch.org/models/resnet34-333f7ec4.pth
+
+RUN wget -O /root/.torch/models/resnet101-5d3b4d8f.pth https://download.pytorch.org/models/resnet101-5d3b4d8f.pth
+
+RUN wget -O /data/models/ColorizeArtistic_gen.pth https://www.dropbox.com/s/zkehq1uwahhbc2o/ColorizeArtistic_gen.pth?dl=0 
+
+RUN wget -O /data/models/ColorizeVideo_gen.pth https://www.dropbox.com/s/336vn9y4qwyg9yz/ColorizeVideo_gen.pth?dl=0
+
+ADD . /data/
+
+WORKDIR /data
+
+RUN pip install -r requirements.txt
+
+RUN pip install  Flask
+
+RUN cd /data/test_images && git lfs pull
+
+EXPOSE 5000
+
+ENTRYPOINT ["python3", "app.py"]
+

README.md

@@ -34,58 +34,58 @@ NOTE:  Click images to watch
 
 "Migrant Mother" by Dorothea Lange (1936)
 
-![MigrantMother](resource_images/10_dorothea-lange_artistic_RF25_compared_sm.jpg)
+![MigrantMother](https://i.imgur.com/Bt0vnke.jpg)
 
 
 Woman relaxing in her livingroom in Sweden (1920)
 
-![SwedenLivingRoom](resource_images/0_LivingRoom1920Sweden_artistic_RF46_compared_sm.jpg)
+![SwedenLivingRoom](https://i.imgur.com/158d0oU.jpg)
 
 
 "Toffs and Toughs" by Jimmy Sime (1937)
 
-![ClassDivide](resource_images/1_ClassDivide1930sBrittain_artistic_RF30_compared_sm.jpg)
+![ClassDivide](https://i.imgur.com/VYuav4I.jpg)
 
 
 Thanksgiving Maskers (1911)
 
-![ThanksgivingMaskers](resource_images/2_1911ThanksgivingMaskers_artistic_RF36_compared_sm.jpg)
+![ThanksgivingMaskers](https://i.imgur.com/n8qVJ5c.jpg)
 
 
 Glen Echo Madame Careta Gypsy Camp in Maryland (1925)
 
-![GypsyCamp](resource_images/3_1925GypsyCampMaryland_artistic_RF45_compared_sm.jpg)
+![GypsyCamp](https://i.imgur.com/1oYrJRI.jpg)
 
 
 "Mr. and Mrs. Lemuel Smith and their younger children in their farm house, Carroll County, Georgia." (1941)
 
-![GeorgiaFarmhouse](resource_images/4_1941GeorgiaFarmhouse_stable_RF43_compared_sm.jpg)
+![GeorgiaFarmhouse](https://i.imgur.com/I2j8ynm.jpg)
 
  
 "Building the Golden Gate Bridge" (est 1937)
 
-![GoldenGateBridge](resource_images/5_GoldenGateConstruction_stable_RF45_compared_sm.jpg)
+![GoldenGateBridge](https://i.imgur.com/6SbFjfq.jpg)
 <sub>NOTE:  What you might be wondering is while this render looks cool, are the colors accurate? The original photo certainly makes it look like the towers of the bridge could be white. We looked into this and it turns out the answer is no- the towers were already covered in red primer by this time. So that's something to keep in mind- historical accuracy remains a huge challenge!</sub>
 
 
 "Terrasse de café, Paris" (1925)
 
-![CafeParis](resource_images/6_CafeTerrace1925Paris_artistic_RF37_compared_sm.jpg)
+![CafeParis](https://i.imgur.com/WprQwP5.jpg)
 
 
 Norwegian Bride (est late 1890s)
 
-![NorwegianBride](resource_images/7_NorwegianBride1890s_artistic_RF40_compared_sm.jpg)
+![NorwegianBride](https://i.imgur.com/MmtvrZm.jpg)
 
 
 Zitkála-Šá (Lakota: Red Bird), also known as Gertrude Simmons Bonnin (1898)
 
-![NativeWoman](resource_images/8_NativeWoman1898_artistic_RF19_compared_sm.jpg)
+![NativeWoman](https://i.imgur.com/zIGM043.jpg)
 
 
 Chinese Opium Smokers (1880)
 
-![OpiumReal](resource_images/9_ChinaOpiumc1880_artistic_RF43_compared_sm.jpg)
+![OpiumReal](https://i.imgur.com/lVGq8Vq.jpg)
 
 -------------------------
 ### Stuff That Should Probably Be In A Paper
@@ -215,7 +215,7 @@ jupyter lab
 
 From there you can start running the notebooks in Jupyter Lab, via the url they provide you in the console.  
 
-#### Docker
+#### Docker for Jupyter
 
 You can build and run the docker using the following process:
 
@@ -226,18 +226,47 @@ git clone https://github.com/jantic/DeOldify.git DeOldify
 
 Building Docker
 ```console
-cd DeOldify && docker build -t deoldify .
+cd DeOldify && docker build -t deoldify_jupyter -f Dockerfile .
 ```
 
 Running Docker
 ```console
-echo "http://$(curl ifconfig.io):8888" && nvidia-docker run --ipc=host --env NOTEBOOK_PASSWORD="pass123" -p 8888:8888 -it deoldify
+echo "http://$(curl ifconfig.io):8888" && nvidia-docker run --ipc=host --env NOTEBOOK_PASSWORD="pass123" -p 8888:8888 -it deoldify_jupyter
 ```
 
+#### Docker for API
+
+You can build and run the docker using the following process:
+
+Cloning
+```console
+git clone https://github.com/jantic/DeOldify.git DeOldify
+```
+
+Building Docker
+```console
+cd DeOldify && docker build -t deoldify_api -f Dockerfile-api .
+```
+
+Running Docker
+```console
+echo "http://$(curl ifconfig.io):5000" && nvidia-docker run --ipc=host -p 5000:5000 -d deoldify_api
+```
+
+Calling the API for image processing
+```console
+curl -X POST "http://MY_SUPER_API_IP:5000/process_image" -H "accept: image/png" -H "Content-Type: application/json" -d "{\"source_url\":\"http://www.afrikanheritage.com/wp-content/uploads/2015/08/slave-family-P.jpeg\", \"render_factor\":35}" --output colorized_image.png
+```
+
+Calling the API for video processing
+```console
+curl -X POST "http://MY_SUPER_API_IP:5000/process_video" -H "accept: application/octet-stream" -H "Content-Type: application/json" -d "{\"source_url\":\"https://v.redd.it/d1ku57kvuf421/HLSPlaylist.m3u8\", \"render_factor\":35}" --output colorized_video.mp4
+```
+#### Note Regarding Docker
 If you don't have Nvidia Docker, here is the installation guide :
 https://github.com/nvidia/nvidia-docker/wiki/Installation-(version-2.0)#installing-version-20
 
-#### Note 
+#### Note GIT LFS (test images download support)
 Make sure you have Git LFS installed if you're planning on using images in the /test_images/ folder.  Otherwise, you'll just wind up getting tiny files that will have the same file names but you will run into errors trying to open them or colorize them.  If you have a fancy shmancy git client like GitHub Desktop, it will probably prompt you to install it and do it for you.  If that doesn't happen,  get it here: https://git-lfs.github.com/
 
 --------------------------
@@ -290,3 +319,7 @@ We suspect some of you are going to want access to the original DeOldify model f
 
 I'll be posting more results on Twitter. [<img src="resource_images/Twitter_Social_Icon_Rounded_Square_Color.svg" width="28">](https://twitter.com/citnaj)
 
+-------------------------
+### License
+All code in this repository is under the MIT license as specified by the LICENSE file.
+The model weights listed in this readme under the "Pretrained Weights" section are trained by ourselves and are released under the MIT license.

fasterai/dataset.py

@@ -9,7 +9,7 @@ from .augs import noisify
 def get_colorize_data(sz:int, bs:int, crappy_path:Path, good_path:Path, random_seed:int=None, 
         keep_pct:float=1.0, num_workers:int=8, xtra_tfms=[])->ImageDataBunch:
 
-    src = (ImageImageList.from_folder(crappy_path)
+    src = (ImageImageList.from_folder(crappy_path, convert_mode='RGB')
         .use_partial_data(sample_pct=keep_pct, seed=random_seed)
         .split_by_rand_pct(0.1, seed=random_seed))
 

fasterai/unet.py

@@ -68,7 +68,7 @@ class DynamicUnetDeep(SequentialEx):
         imsize = (256,256)
         sfs_szs = model_sizes(encoder, size=imsize)
         sfs_idxs = list(reversed(_get_sfs_idxs(sfs_szs)))
-        self.sfs = hook_outputs([encoder[i] for i in sfs_idxs])
+        self.sfs = hook_outputs([encoder[i] for i in sfs_idxs], detach=False)
         x = dummy_eval(encoder, imsize).detach()
 
         ni = sfs_szs[-1][1]
@@ -138,7 +138,7 @@ class DynamicUnetWide(SequentialEx):
         imsize = (256,256)
         sfs_szs = model_sizes(encoder, size=imsize)
         sfs_idxs = list(reversed(_get_sfs_idxs(sfs_szs)))
-        self.sfs = hook_outputs([encoder[i] for i in sfs_idxs])
+        self.sfs = hook_outputs([encoder[i] for i in sfs_idxs], detach=False)
         x = dummy_eval(encoder, imsize).detach()
 
         ni = sfs_szs[-1][1]

fasterai/visualize.py

@@ -104,13 +104,10 @@ class VideoColorizer():
             if re.search('.*?\.jpg', f):
                 os.remove(os.path.join(dir, f))
 
-    def _get_fps(self, source_path: Path)->float:
+    def _get_fps(self, source_path: Path)->str:
         probe = ffmpeg.probe(str(source_path))
         stream_data = next((stream for stream in probe['streams'] if stream['codec_type'] == 'video'), None)
-        avg_frame_rate = stream_data['avg_frame_rate']
-        fps_num=avg_frame_rate.split("/")[0]
-        fps_den = avg_frame_rate.rsplit("/")[1]
-        return round(float(fps_num)/float(fps_den))
+        return stream_data['avg_frame_rate']
 
     def _download_video_from_url(self, source_url, source_path:Path):
         if source_path.exists(): source_path.unlink()
@@ -143,17 +140,31 @@ class VideoColorizer():
                 color_image.save(str(colorframes_folder/img))
     
     def _build_video(self, source_path:Path)->Path:
-        result_path = self.result_folder/source_path.name
+        colorized_path = self.result_folder/(source_path.name.replace('.mp4', '_no_audio.mp4'))
         colorframes_folder = self.colorframes_root/(source_path.stem)
         colorframes_path_template = str(colorframes_folder/'%5d.jpg')
-        result_path.parent.mkdir(parents=True, exist_ok=True)
-        if result_path.exists(): result_path.unlink()
+        colorized_path.parent.mkdir(parents=True, exist_ok=True)
+        if colorized_path.exists(): colorized_path.unlink()
         fps = self._get_fps(source_path)
 
-        ffmpeg.input(str(colorframes_path_template), format='image2', vcodec='mjpeg', framerate=str(fps)) \
-            .output(str(result_path), crf=17, vcodec='libx264') \
+        ffmpeg.input(str(colorframes_path_template), format='image2', vcodec='mjpeg', framerate=fps) \
+            .output(str(colorized_path), crf=17, vcodec='libx264') \
             .run(capture_stdout=True)
-        
+
+        result_path = self.result_folder/source_path.name
+        if result_path.exists(): result_path.unlink()
+        #making copy of non-audio version in case adding back audio doesn't apply or fails.
+        shutil.copyfile(str(colorized_path), str(result_path))
+
+        # adding back sound here
+        audio_file = Path(str(source_path).replace('.mp4', '.aac'))
+        if audio_file.exists(): audio_file.unlink()
+
+        os.system('ffmpeg -y -i "' + str(source_path) + '" -vn -acodec copy "' + str(audio_file) + '"')
+
+        if audio_file.exists:
+            os.system('ffmpeg -y -i "' + str(colorized_path) + '" -i "' + str(audio_file) 
+                + '" -shortest -c:v copy -c:a aac -b:a 256k "' + str(result_path) + '"')
         print('Video created here: ' + str(result_path))
         return result_path
 

resource_images/0_LivingRoom1920Sweden_artistic_RF46.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:42fffe04df8b3bfccd67ec6749df8de948c83df762329ce556b898fb38b404bc
-size 234063

resource_images/0_LivingRoom1920Sweden_artistic_RF46_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:586bd829047a5d5e6e2749f6f1421f5f596f63d0f08842564860f6493bf2b8ce
-size 1213100

resource_images/0_LivingRoom1920Sweden_artistic_RF46_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6b2084e68ffbb7859588d82ec4019a5ec161ff8065f0a2849bcadf71555f713a
-size 612587

resource_images/10_dorothea-lange_artistic_RF25.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9b30b47ac0015d7a96763816da31e3ae9a6a0ecccb53cd8e368ad534af08fd5e
-size 111561

resource_images/10_dorothea-lange_artistic_RF25_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a96d16a66004826f2dcd1aba86865838eb7fe0360bc47bb77df9915ed8d0beea
-size 730133

resource_images/10_dorothea-lange_artistic_RF25_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:10724caceca5fbee2a7b58b241fbde999ed8e1a854c08fb3ffe6100f3c0abafb
-size 231089

resource_images/11_ParisLate1800s_artistic_RF18.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b18ab44a941e42b62f7f7f9f2ff77010aa2a9f18394e7b147f9cbc3f6bb1a1f0
-size 214554

resource_images/12_Evelyn_Nesbit_artistic_RF21.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4e094357792b896a0e0c01c178e3e223bd32c020d12e24a3e345adf8d6966d7b
-size 301809

resource_images/13_1939GypsyKids_stable_RF37.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:87c9a79f58f508b94fd086e7424cbb93b8fdbc7b4d9fffe3fb9a0224bf8866b8
-size 59249

resource_images/14_1910Racket_artistic_RF34.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:06697db894377cfd5a0914900c916849bfe95e24e7510d66dc785dda4872841c
-size 481829

resource_images/15_smoking_kid_stable_RF35.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:155c1b76661f6037f3123dca052f8ba3d6240a7067662a0deee441c586a5ebc7
-size 99133

resource_images/16_TV1930s_artistic_RF30.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cf6df05d15a42462b70e3cf2971e0def2aa36d0e59342f87118f3a7229a10c64
-size 88422

resource_images/17_Chief_artistic_RF14.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ea3163832919a0fd0165a867058b2a57f324a627191a248dee36100d1adcf881
-size 99918

resource_images/18_TitanicGym_RF31.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f481ec91030bfbc3d839899c22de876a5c5adb31f47d5c304ae7855baf046aca
-size 149643

resource_images/19_ParisLadies1910_artistic_RF38.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:35378595ed31d07ed81139f0b4744dd12c26c2e4ab6b0a848fe5489ce6f91f89
-size 52754

resource_images/1_ClassDivide1930sBrittain_artistic_RF30.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:bd75d6c245a5af8c614178409c108bdc1f754fa415c443a7db0b9413d4c9bc12
-size 483267

resource_images/1_ClassDivide1930sBrittain_artistic_RF30_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:dbf3d4a2e8696f1080c82a8b40e37e562fa271dba6467b16d43d3e286771bc92
-size 3392575

resource_images/1_ClassDivide1930sBrittain_artistic_RF30_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:832f904da55eacb7f77014b3d033639e58527fbf42b42db4e496190688bac2b2
-size 129144

resource_images/20_EasterNyc1911_artistic_RF20.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:dbdf824d5161ffacb154814b76b07818b715fc661d54e8d447e78f95236589d2
-size 116388

resource_images/21_Edinburgh1920s_stable_RF17.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c2657e927c1085b9804a01e358d46374d3a614c88953db5fd75bf89e2f8f2b78
-size 927005

resource_images/22_1850Geography_artistic_RF22.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a4b67a3eae686ef08e1f7166a609c94dd60e7fb1c40056ad86a1a2640a542d61
-size 74144

resource_images/23_1909Chicago_artistic_RF14.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:870a1294c6d24d4d9731b768dc7f9bc1ccc2b0af355ce5371a24405859ac96d3
-size 259782

resource_images/2_1911ThanksgivingMaskers_artistic_RF36.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9b860462ae64c4783ba514ccadc9c18b8e16dd1369c0d5438dc6541fbd162bbb
-size 268713

resource_images/2_1911ThanksgivingMaskers_artistic_RF36_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cb8aa25edf7f57b8861d49e9fecb0b93dc8b81def74ac31ae767335864c43e97
-size 1751927

resource_images/2_1911ThanksgivingMaskers_artistic_RF36_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:6eadfe0777a6946682878eb025a82d4d2ff663b64d5f899e65ce56cbf134893c
-size 233198

resource_images/3_1925GypsyCampMaryland_artistic_RF45.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1675907d0b034fa2dac8c9ee82d6a374906217b3788c358baa49c52bc5e740a7
-size 212866

resource_images/3_1925GypsyCampMaryland_artistic_RF45_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3aa5bf9786ac5f04a118502ac61f3b78d8e409c8547be1dfc8b06f613b0f89bc
-size 1261777

resource_images/3_1925GypsyCampMaryland_artistic_RF45_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:62131a4e5f8008b95939020e786640c02a4768252db280cd5fb2595dc8dd7908
-size 335399

resource_images/4_1941GeorgiaFarmhouse_stable_RF43.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:0195b4e9004b92d8a07b8a340daa987f662e501983dbceec30e4d0cb59d18adf
-size 1039015

resource_images/4_1941GeorgiaFarmhouse_stable_RF43_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:786d6ac07be6b3b772567d10541f47fe82843f20dd3ecfaadb4b7d78f6195080
-size 6843480

resource_images/4_1941GeorgiaFarmhouse_stable_RF43_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2e4c5dacbd36e5ab7380efd39ee65b3483f121239e222ce67f71455dbc83e371
-size 458491

resource_images/5_GoldenGateConstruction_stable_RF45.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c5aaa1bdb4bc4e17e0c31ac1b234d197701e399c883e8ec9a6db1e8f7e148c60
-size 143693

resource_images/5_GoldenGateConstruction_stable_RF45_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:062495947f732158d89e6bee3ac9592b6b718eb1b8f6e213e917948b3f750ffa
-size 723303

resource_images/5_GoldenGateConstruction_stable_RF45_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a4aa5cf6f506707ab8608d6003ed8648ea459235d3a1b0bd8a16927f075f1702
-size 137067

resource_images/6_CafeTerrace1925Paris_artistic_RF37.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f882a5f65e428f36521ce4610857a480ff174f296ee87d4162bebb585f07e0f9
-size 150918

resource_images/6_CafeTerrace1925Paris_artistic_RF37_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:86fa95b2edb857227b3b59e9f67f7e63549eccfd7d00274067c700e610a1ee22
-size 793126

resource_images/6_CafeTerrace1925Paris_artistic_RF37_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:72e4c531fe513775b54e9925d868cc3f8858468b7ae1ad3e94bfdc1305f6cd6a
-size 109076

resource_images/7_NorwegianBride1890s_artistic_RF40.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:50a7b9fad79f9a2173b6e6b876d821774b5be4e29229a2457a77b16358c7e430
-size 71152

resource_images/7_NorwegianBride1890s_artistic_RF40_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8fb7db5b2224af0ef8b64a94c713f7eb1b066f2821fdd77b42395af18655f0a2
-size 434760

resource_images/7_NorwegianBride1890s_artistic_RF40_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8a63ff755bf4258ee5e87d836694083108fa71f027ee255654519722d100c282
-size 201535

resource_images/8_NativeWoman1898_artistic_RF19.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8ed31ec5804288f5c203c9bf6a5cd7dca420ec1eaa9d5a0d9cb8ca8e322cc01c
-size 72831

resource_images/8_NativeWoman1898_artistic_RF19_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c6aa5b8085af98c7930169cfbfe41d3ef4f7ba14c74d702d627596529c006684
-size 556172

resource_images/8_NativeWoman1898_artistic_RF19_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3f954c405ee120284553da066613519ac1bde09e15469dedb47e98692d7a883e
-size 140305

resource_images/9_ChinaOpiumc1880_artistic_RF43.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f01f7432c1bdbf1f7e4a2321ca782a68de689709d5109da14e5bfb63f5253c96
-size 329321

resource_images/9_ChinaOpiumc1880_artistic_RF43_compared.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:433206e6cad12f69bc1b443e930a4f950a75c085f027b9d2ff98fd47d3aca6fc
-size 1785573

resource_images/9_ChinaOpiumc1880_artistic_RF43_compared_sm.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9c00a52c6bb87b32c6ff8c329ca23aedebe64affd3edf105fdebaebd97535ab5
-size 252142

test_images/1850Geography.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7e6a52eeb7631d400f6f40fc418eea94c72a4b28ced0c629b834de172980a87c
-size 64919

test_images/1850SchoolForGirls.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f8290997c829ddb94954f522ef41f2259b3dc454641255ae6e801792a77ee06a
-size 122321

test_images/1852GatekeepersWindsor.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:64f524b690c10961f6a2a8053583e4f67da42209d8af6b379d25c5682383a2b5
-size 232084

test_images/1860Girls.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:537317db688c01e02be4ee246a785470cd2ee211fd400789c56130a7fbb5ed76
-size 633175

test_images/1860sSamauris.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4f8cb046206642f9af8934995ad4cb790e533f89a72618f0bc4b249f93e077e3
-size 115337

test_images/1864UnionSoldier.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1bb9ed358f908064af87c158c809a945cc33139d7742f0e7ed35790283ab0464
-size 82395

test_images/1867MusicianConstantinople.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:4b1f4b4d0299ea53d71c9a9d016f1ffa4d86fd1a067c41702025263271db0490
-size 129194

test_images/1870Girl.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e8147cd46316671aa95a3488b0fefa59944a42fdce89e3914f80f33d4c411061
-size 97908

test_images/1870sSphinx.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:0f02b0b7cff589a8db6e2207bb90817a17da31179345fcec5736238a59952326
-size 141240

test_images/1874Mexico.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f5a7c895b2aa3ff059d7b1893e21346bc2156b7df7faf3728683959b368805f1
-size 687715

test_images/1875Olds.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:65392fcfc059dba92fef4f8581ea8d98804c554e32779ef5dc37f075dda37e69
-size 8054415

test_images/1880Paris.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c9e26125901020faac2cdbf4111ae30597d2f83135d3928155f56ac8232aa08f
-size 180959

test_images/1880sBrooklynBridge.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3fc70f36ff3792596788e94e4807c889d6a2c2b6ae34aa216ffa7b2859a3aad9
-size 58452

test_images/1886Hoop.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a7d3dc903293dcd3dc78fcc4ac80fa847ff10f0e39fe71bf15515be71390901b
-size 147130

test_images/1886ProspectPark.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:97483a0fb76a72fa356d63bbf08b3b1a2f35d8899c8f0066371205de4cc7f176
-size 157593

test_images/1888Slum.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e3db6d5a85acc5f298c6e77cfb25176a83925a1f965c33568c68d87ee9fac4f3
-size 69849

test_images/1890BostonHospital.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:bb78baa1340c7ed9eaecb48576e7c92c092b8d5ef8ce12b0c20ba1fcb64f6081
-size 121767

test_images/1890CliffHouseSF.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c2e55c8621a8fc3bd5cdf2d02de55e6b8768f13a3e4003ab207d0e31531fa2d4
-size 48377

test_images/1890Surfer.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b5d509d9fd45ed968b8686689394595d20e91027b120ddbb76643dc5bf0b3a46
-size 297061

test_images/1890sChineseImmigrants.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1149eed69b918bebfcf88218a459b564a477ce04c30d032eeac64142328b9a1e
-size 252364

test_images/1890sMedStudents.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:165f6e8d2cb96dc79dc1558d2ab46a9bd7ab91d1dfbf5cdbf0e306250e85b60e
-size 135206

test_images/1890sPingPong.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:75e2f83e533267cb28919729976ec14a007144ab1afacc874132c6f7028cc03e
-size 227379

test_images/1890sShoeShopOhio.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:77caaf2090de13c3487919ae3ac16d2369f8f4908b2ff23c82d69f6063aa0d93
-size 69692

test_images/1890sTouristsEgypt.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:fb973a9b9b3213a5aba498e6dddd262c86f6d24d8b24f84298b67d31c75b5f21
-size 932481

test_images/1892WaterLillies.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3f670bcb39e3f0e6d1a57d9bad1c0aac7abd3b9ea21db69c8e81d76e4bd30f94
-size 156605

test_images/1895BikeMaidens.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:490be08a3eab33c71a65b0a64bc3a28598c71728a6d9f0432a901d7311c415a1
-size 108972

test_images/1896NewsBoyGirl.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:c625df6e3432fa9b03154fb7d2a5617b17f5690502036a950f2d30c6d9ac6525
-size 40430

test_images/1897BlindmansBluff.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:11ab23fdf71bfc195796b079cdf91e92cce6c0b345c252412cf48489b27964dc
-size 67498

test_images/1897VancouverAmberlamps.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:02a6f4ea0f4214e2a5c2917a311d514cd7290fa9a28c37525fc98f4e79e9a8a4
-size 877517

test_images/1899NycBlizzard.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ab047e2fea66a2609b7a08fcc9c38237e02628ec9632cb560343f985f118c4d2
-size 521801

test_images/1899SodaFountain.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e5a1312df88d948d7c1122dc3652202b3d84f48cb956c45b9cac81e59fbe9acd
-size 375719

test_images/1900NJThanksgiving.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9ffa8824cb450eeb96f32cf002436d42a75a01e5cca98c2ca8c35d39f6b71bc6
-size 957904

test_images/1900ParkDog.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5fd53faaafcb2941109489c56e4e45a7aa6bffc2308fab6194f81d1b516233c4
-size 153711

test_images/1900sDaytonaBeach.png

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ba0cf7906beacfaf1bace6aa695b6ee186d09075d8ad8c34721cb595d572a9a5
-size 319993

test_images/1900sLadiesTeaParty.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a101f258edfe04aaa56a2007dd544bd72e36c60dfb90a98403ace46907510bcd
-size 470435

test_images/1900sSaloon.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3ea9a8d01750b5730b24f9916d2a86f3d78c8c26b2f1b9085c7b70c480a1deeb
-size 1057399

test_images/1901Electrophone.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8c19aa375635b93daf6ebe787b544365a9912fcde66df465d415e8e847d131fa
-size 127896

test_images/1902FrenchYellowBellies.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:afde50ed276a92432bda5f3ef00b4cad09d4455ea7c9a6b176d32074c33bd97f
-size 94042

test_images/1904ChineseMan.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:db671e85d756c98203d99d975eff8c04cacac424d30e511bf792e3fe3d61b4dc
-size 80472

test_images/1907Cowboys.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3b1af96471aea4c33b3cfe4749491e470f27e6e9c79f509a8730ff995e61490f
-size 128624

test_images/1908FamilyPhoto.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:53dc11d50820988f2b7fc4884416090ec13c372c1bf3f9905a20d15d677d109c
-size 80163

test_images/1908RookeriesLondon.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:f6edc02efd49d34994b510e70ac00d0d5eb5b307b2203121dab6aa0da9e7e800
-size 173888

test_images/1909Chicago.jpg

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:85fe2a66fdd36e7b70151bf278f74d0135cbcebb7ed63c1ff6aca6e6a69e3fa0
-size 273400