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Change metric to use CS for search. Also order by distance. #28

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Change metric to use CS for search. Also order by distance. #28

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35 changes: 20 additions & 15 deletions notebooks/QuickStart.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -85,15 +85,7 @@
"execution_count": null,
"id": "3cd0d138",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Enter JSON string: "
]
}
],
"outputs": [],
"source": [
"! adb config create --active --from-json"
]
Expand Down Expand Up @@ -307,23 +299,28 @@
"outputs": [],
"source": [
"from aperturedb.CommonLibrary import create_connector, execute_query\n",
"from aperturedb.NotebookHelpers import display\n",
"from aperturedb.NotebookHelpers import display as nbd\n",
"from IPython.display import display\n",
"import clip\n",
"import torch\n",
"\n",
"device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
"model, preprocess = clip.load(\"ViT-B/16\", device=device)\n",
"\n",
"search_tokens = clip.tokenize([f\"a photo of bread\"]).to(device)\n",
"search_tokens = clip.tokenize([f\"a photo of bread on plate\"]).to(device)\n",
"search_embeddings = model.encode_text(search_tokens)\n",
"\n",
"query = [{\n",
" \"FindDescriptor\": {\n",
" \"set\": \"ViT-B/16\", # Name of descriptor set to use\n",
" \"k_neighbors\": 5, # How many results to return\n",
" \"k_neighbors\": 10, # How many results to return\n",
" \"distances\": True, # Also return distances (as _distance property)\n",
" \"blobs\": False, # Don't return vectors of matching descriptors\n",
" \"_ref\": 1 # forward reference\n",
" \"_ref\": 1, # forward reference,\n",
" \"metric\": \"CS\",\n",
" \"results\": {\n",
" \"list\": [\"_uniqueid\"]\n",
" }\n",
" }\n",
"}, {\n",
" \"FindImage\": {\n",
Expand All @@ -332,7 +329,8 @@
" \"ref\": 1 # backward reference\n",
" },\n",
" \"results\": {\n",
" \"all_properties\": True # Return all properties\n",
" \"list\": [\"_uniqueid\"], # Return all properties\n",
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@bovlb bovlb Jul 16, 2025

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Suggested change
" \"list\": [\"_uniqueid\"], # Return all properties\n",
" \"list\": [\"_uniqueid\"], # Return only unique ids\n",

" \"group_by_source\": True\n",
" }\n",
" }\n",
"}]\n",
Expand All @@ -351,7 +349,14 @@
"\n",
"# Check if the query was successful\n",
"if result == 0:\n",
" display(blobs)\n"
" #Here we reorder the images based on the distances before displaying them\n",
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@bovlb bovlb Jul 16, 2025

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Suggested change
" #Here we reorder the images based on the distances before displaying them\n",
" # Here we reorder the images based on the distances before displaying them\n",

" # based on decreasing distance from the input vector.\n",
" descriptors = response[0][\"FindDescriptor\"][\"entities\"]\n",
" images = response[1][\"FindImage\"][\"entities\"]\n",
" for d in descriptors:\n",
" bi = images[d[\"_uniqueid\"]][0][\"_blob_index\"]\n",
" display(d[\"_distance\"], bi)\n",
" nbd([blobs[bi]])\n"
]
},
{
Expand Down