cosine_similarity_scores_2

.gitignore

@@ -3,4 +3,5 @@ __pycache__
 *.pickle
 *.zip
 *.json
-.DS_Store
+.DS_Store
+*.png

data/preview.ipynb

@@ -219,37 +219,7 @@
         "\n",
         "def format_name(file_name: str):\n",
         "  name_, ext_ = file_name.split('.')\n",
-        "  return f'PNG/{name_[:4]}---{name_[-4:]}.{ext_}'\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 73,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 35
-        },
-        "id": "P-LCWf2LOaOM",
-        "outputId": "6a35e807-a114-4cc9-af63-d216ea0bac13"
-      },
-      "outputs": [
-        {
-          "data": {
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "string"
-            },
-            "text/plain": [
-              "'PNG/6aa1---d46b.png'"
-            ]
-          },
-          "execution_count": 73,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
-      "source": [
-        "format_name(images[0].split('/')[-1])"
+        "  return f'PNG/{name_[:4]}---{name_[-4:]}.{ext_}'"
       ]
     },
     {
@@ -413,7 +383,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.10.13"
+      "version": "3.1.0"
     }
   },
   "nbformat": 4,

utils/get_unique_values.py

@@ -0,0 +1,13 @@
+import numpy as np
+
+def get_unique_values(start, end, count):
+  '''
+    Returns a list of unique countinous values between start and end
+    Args:
+      start: int - less than end
+      end: int - greater than start
+      count: int - number of values to return
+    Returns:
+      List[int]
+  '''
+  return np.arange(start, end, (end - start)/count)[:count]