Dockerignore

.dockerignore

@@ -0,0 +1,2 @@
+training-runs
+datasets

ThisPlaceDoesExist.ipynb

@@ -1,8 +1,22 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "c08a9c8e-bcce-4b45-94ad-b422ad60bea9",
+   "metadata": {},
+   "source": [
+    "# This Place Does Exists - Utilities for Stylegan3\n",
+    "\n",
+    "This notebook contains utility functions for working with the models created by StyleGAN3. \n",
+    "\n",
+    "## Usage\n",
+    "\n",
+    "Include it in any notebook using `%run ThisPlaceDoesExist.ipynb`. After which everything from this notebook becomes available. Including a `runs` variable which is a list containing all the `Run` objects."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 1,
    "id": "f4ee99c4-9c28-4fe4-9408-e130a0d446d3",
    "metadata": {},
    "outputs": [],
@@ -52,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 4,
    "id": "4c428611-8d75-4f9a-ae5a-7960e7b01470",
    "metadata": {},
    "outputs": [],
@@ -68,16 +82,6 @@
     "See [Snapshot_images.ipynb](Snapshot_images.ipynb) for examples of each run/snapshot."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "9a5c4a18-0389-4d36-989e-7a120db590ab",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# snapshot = runs[3].snapshots[70]"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "c3aa8404-aeb0-4f63-b4b4-c278f0cf3766",
@@ -90,7 +94,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 5,
    "id": "c180db45-9bf1-4f0a-ab55-62b476a5897c",
    "metadata": {},
    "outputs": [],
@@ -115,22 +119,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "id": "22c74f41-65e7-461a-9094-f0b3d8738c82",
    "metadata": {},
-   "outputs": [
+   "outputs": [],
-    {
-     "ename": "NameError",
-     "evalue": "name 'runs' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[0;32m/tmp/ipykernel_1/862876608.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# def is_main():\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mplot\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_runs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mruns\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbbox_to_anchor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mloc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"lower left\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'runs' is not defined"
-     ]
-    }
-   ],
    "source": [
     "def is_main():\n",
     "    plot = plot_runs(runs)\n",
@@ -449,11 +441,11 @@
     "    runnr = snapshot.run.as_nr\n",
     "    # !!python pbaylies_projector.py --network $snapshot_pkl --outdir out/projections/$runnr-$imagenr --target-image $image_filename --use-clip=False\n",
     "    \n",
-    "    if replace_if_exists or not os.path.exists(f\"out/projections/{runnr}/{image_name}/proj.png\"):\n",
+    "    if replace_if_exists or not os.path.exists(f\"out/projections/{snapshot.id}/{image_name}/proj.png\"):\n",
     "        process = subprocess.Popen([\n",
     "            \"python\", \"pbaylies_projector.py\",\n",
     "            \"--network\" , snapshot.pkl_path,\n",
-    "            \"--outdir\", f\"out/projections/{runnr}/{image_name}\",\n",
+    "            \"--outdir\", f\"out/projections/{snapshot.id}/{image_name}\",\n",
     "            \"--target-image\", image_filename,\n",
     "            \"--use-clip\", \"False\",\n",
     "            \"--num-steps\", str(steps),\n",
@@ -469,10 +461,10 @@
     "        loss, dist = (None, None)\n",
     "\n",
     "    return {\n",
-    "        \"img\": f\"out/projections/{runnr}-{imagenr}/proj.png\",\n",
+    "        \"img\": f\"out/projections/{snapshot.id}/{image_name}/proj.png\",\n",
-    "        \"src_img\": f\"out/projections/{runnr}-{imagenr}/target.png\",\n",
+    "        \"src_img\": f\"out/projections/{snapshot.id}/{image_name}/target.png\",\n",
     "        \"src\": image_filename,\n",
-    "        \"npz\": f\"out/projections/{runnr}-{imagenr}/projected_w.npz\",\n",
+    "        \"npz\": f\"out/projections/{snapshot.id}/{image_name}/projected_w.npz\",\n",
     "        \"loss\": loss,\n",
     "        \"dist\": dist\n",
     "    }\n",
@@ -568,43 +560,6 @@
     "    # output.release()\n",
     "    writer.close()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "id": "6ff4c6db-b48f-4ff4-b08c-e85138f0f307",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "id": "d0661104-72a7-4320-980a-1a702388659f",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e2aa2c98-cf1e-465a-9455-fe4a02f145ad",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

dataset_tool.py

@@ -90,7 +90,7 @@ def open_image_folder(source_dir, *, max_images: Optional[int]):
             arch_fname = os.path.relpath(fname, source_dir)
             arch_fname = arch_fname.replace('\\', '/')
             img = np.array(PIL.Image.open(fname))
-            yield dict(img=img, label=labels.get(arch_fname))
+            yield dict(img=img, label=labels.get(arch_fname), filename=fname)
             if idx >= max_idx-1:
                 break
     return max_idx, iterate_images()
@@ -119,7 +119,7 @@ def open_image_zip(source, *, max_images: Optional[int]):
                 with z.open(fname, 'r') as file:
                     img = PIL.Image.open(file) # type: ignore
                     img = np.array(img)
-                yield dict(img=img, label=labels.get(fname))
+                yield dict(img=img, label=labels.get(fname), filename=fname)
                 if idx >= max_idx-1:
                     break
     return max_idx, iterate_images()

runs.py

@@ -1,13 +1,14 @@
 import os
 import datetime
 import json
-from typing import List
+from typing import List, Optional
 from PIL import Image
 from enum import Enum
 import logging
 import numpy as np
 import dnnlib
 import legacy
+from dataset_tool import open_dataset
 
 logger = logging.getLogger('runs')
 
@@ -131,6 +132,13 @@ class Run():
     def dataset_is_conditional(self):
         return bool(self.training_options["training_set_kwargs"]["use_labels"])
     
+    def dataset_iterator(self, max_images: Optional[int] = None):
+        max_images, iterator = open_dataset(
+            self.training_options["training_set_kwargs"]["path"],
+            max_images=max_images
+        )
+        return iterator
+            
     @property
     def resolution(self):
         return self.training_options["training_set_kwargs"]["resolution"]

templates/runs.j2

@@ -17,6 +17,11 @@
     <section id='cover'>
         <h1 class="title">This Place Does Exist</h1>
         <h2>Stylegan 3 Snapshots</h2>
+        <div class='authors'>Ward Goes & Ruben van de Ven</div>
+    </section>
+    
+    <section id="introduction">
+    {{introduction}}
     </section>
 
     <section id="toc">