check visison extract model

extract/test.ipynb

@@ -0,0 +1,139 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "a314a8ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.        , 0.        ],\n",
+       "       [0.26726124, 0.56694671]])"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics.pairwise import cosine_similarity\n",
+    "import numpy as np\n",
+    "X = [[0, 0, 0], [1, 2, 3]]\n",
+    "Y = [[1, 0, 0], [1, 1, 0]]\n",
+    "cosine_similarity(X, Y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "4b560c4f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sims = cosine_similarity(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d8d5d17a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "a1098a5a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(3, 3)\n",
+      "(array([0, 0, 1]), array([1, 2, 2]))\n",
+      "(3,)\n",
+      "mean sim: -0.3333333333333334 std: 0.47140452079103173\n"
+     ]
+    }
+   ],
+   "source": [
+    "# X = np.array([\n",
+    "#     [0, 0, 0], \n",
+    "#     [-1, 100, -1000],\n",
+    "#     [-1, -2, -4]\n",
+    "#     ]\n",
+    "#              )\n",
+    "\n",
+    "X = np.array([\n",
+    "    [0, 0, 0], \n",
+    "    [1,1,1],\n",
+    "    [-1, -1, -1]\n",
+    "    ]\n",
+    "             )\n",
+    "print(X.shape)\n",
+    "sims = cosine_similarity(X)\n",
+    "\n",
+    "triu_idxs = np.triu_indices_from(sims, k=1)\n",
+    "print(triu_idxs)\n",
+    "dist_vals = sims[triu_idxs]\n",
+    "print(dist_vals.shape)\n",
+    "print(\"mean sim:\", dist_vals.mean(), \"std:\", dist_vals.std())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "2dacad18",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.])"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dist_vals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "76d25e07",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}