Notebook for matching scenes with StashDB UUIDs with TPDB

pandas/README.md

@@ -44,3 +44,30 @@ After opening this repository in Visual Studio Code, remember to set correct ker
 Now you can start experimenting with Stash and Pandas by looking at hello_world.ipynb.
 
 ![Example notebook with Data Wrangler](images/hello_world_data_wrangler.png)
+
+# Notebooks
+
+## Hello World
+
+A handful of samples to get you going.
+
+## Scene Matching
+
+Tailored to a workflow where scenes have been matched to StashDB first and you want to match to TPDB without using TPDB's data directly.
+
+Process is as follows:
+
+1. Set TPDB_API_KEY value in .env file to your TPDB API key
+2. Run initial cells to create Stash app connection and create utility functions
+3. Run studio summary to figure out which networks have most scenes missing TPDB. Open `df_scenes_grouped_by_studio` in Data Wrangler.
+4. Iterate following process
+   1. Find studio with name
+   1. Get 100 scenes at a time from Stash app
+   1. Get TPDB matches with phash and get the best match in a single table
+   1. Open `df_matched_scenes` in Data Wrangler
+   1. Manually verify with Data Wrangler UI that scenes match as you expected
+   1. Save TPDB UUIDs to your Stash app with one of the last cells. There are multiple examples based on if you are comfortable saving TPDB UUIDs only to those scenes which match all identifiers or if you want something more specific.
+
+![Studios with most missing scenes](images/scene_matching_studio_summary.png)
+
+![Matched scenes under review](images/scene_matching_manual_review.png)