Notebooks

nbs/movie.ipynb

@@ -0,0 +1,172 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "d6299e4c-f1ba-4be4-ac89-63c05287387c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/admin/home-devforfu/realfake\n"
+     ]
+    }
+   ],
+   "source": [
+    "%cd .."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "8729a815-81b7-4667-bb97-c85456ad86e8",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from realfake.utils import list_files, write_jsonl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "82fa1fee-3ea0-415e-8a6a-8622bc55fabd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "root = Path(\"/fsx/home-devforfu/data\")\n",
+    "laion = list_files(root/\"laionimages\", [\"jpg\"])\n",
+    "movie = list_files(root/\"shotcafe\", [\"jpg\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "58d79304-bdf0-445d-b5dd-46bd2a7bf1ec",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(5133, 7526)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(laion), len(movie)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "f78ced08-3a5a-48f8-a635-6d93e82856c1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "n_test = 0.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "7a89dac3-cc8f-46cf-b60a-9118121ff69a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "tst = set(train_test_split(np.arange(len(laion)), test_size=n_test)[1])\n",
+    "metadata = [{\"path\": str(fn), \"label\": \"real\", \"valid\": i in tst} for i, fn in enumerate(laion)]\n",
+    "tst = set(train_test_split(np.arange(len(movie)), test_size=n_test)[1])\n",
+    "metadata += [{\"path\": str(fn), \"label\": \"fake\", \"valid\": i in tst} for i, fn in enumerate(movie)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "b0da02f5-eec6-4114-81fa-901aef933d72",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "False    11392\n",
+      "True      1267\n",
+      "Name: valid, dtype: int64\n",
+      "fake    7526\n",
+      "real    5133\n",
+      "Name: label, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "df = pd.DataFrame(metadata)\n",
+    "print(df.valid.value_counts())\n",
+    "print(df.label.value_counts())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "bdad7b5a-17de-424b-8bfb-d13fe197552b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "write_jsonl(\"metadata/movies.jsonl\", metadata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "428dda09-77b8-4f6c-b14e-059e9d281f9a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

nbs/movie_more.ipynb

@@ -0,0 +1,204 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "df45e4ec-e732-4cf4-8017-ce3753f4cd48",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd .."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "67eda6f2-e2e5-495a-8795-25365d46c081",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "from pathlib import Path\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from realfake.utils import list_files, write_jsonl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c6e57858-c5f1-4ef9-a69b-31e402215564",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "np.random.seed(1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5f8e03d2-039d-4aaf-b8bd-173d04b8d888",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "root = Path(\"/fsx/home-devforfu/data\")\n",
+    "laion, movie1, movie2 = [list_files(root/subdir, [\"jpg\"]) for subdir in (\"laionimages\", \"shotcafe\", \"pack1\")]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1766851a-e1f6-46af-98a1-700aa53dd240",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "len(movie2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dcb3b8ab-6012-4e78-958b-aef1bc743ef9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "n_test = 0.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "419062b0-e594-4644-87f2-180ba864587e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "tst = set(train_test_split(np.arange(len(laion)), test_size=n_test)[1])\n",
+    "metadata = [{\"path\": str(fn), \"label\": \"real\", \"valid\": i in tst} for i, fn in enumerate(laion)]\n",
+    "tst = set(train_test_split(np.arange(len(movie1)), test_size=n_test)[1])\n",
+    "metadata += [{\"path\": str(fn), \"label\": \"fake\", \"valid\": i in tst} for i, fn in enumerate(movie1)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8f6ed004-8932-4ce9-b4cb-32d0c5c47da7",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from collections import defaultdict\n",
+    "movie_to_frame = defaultdict(list)\n",
+    "for fn in movie2:\n",
+    "    movie_name = re.search(\"((?:[a-zA-Z]+|[0-9]+))\", fn.stem).group(1)\n",
+    "    movie_to_frame[movie_name].append(fn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bb06edea-419c-4e3f-b9dd-f4869e05d3a9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "trn_keys, tst_keys = train_test_split(list(set(movie_to_frame)), test_size=n_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6ac623e7-c9ae-4467-9fc7-f363adae6e57",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "metadata += [{\"path\": str(fn), \"label\": \"fake\", \"valid\": False} for key in trn_keys for fn in movie_to_frame[key]]\n",
+    "metadata += [{\"path\": str(fn), \"label\": \"fake\", \"valid\": True} for key in tst_keys for fn in movie_to_frame[key]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a70b6b30-fdbb-49cb-b10f-34547c4072bb",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame(metadata)\n",
+    "print(df.valid.value_counts())\n",
+    "print(df.label.value_counts())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "737a3a2f-428d-490f-a8a9-def76f094ce0",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "pos_weight = (1 - df.label.value_counts(normalize=True)).tolist()\n",
+    "pos_weight"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "72e03454-cec8-4b58-ba3a-f1fe7d59ee8e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "write_jsonl(\"metadata/movies_plus.jsonl\", metadata)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "41c061b1-7f8d-43d5-9b52-88c6144d0bda",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}