dierk
3ef43019be
- index_images_indb.py: new script indexing via VECTOR_EMBEDDING(CLIP_IMG) using a two-step INSERT+UPDATE to work around ORA-24816 - index_images_oracle.py / index_images.py: add timing output - Presentation: schema names VECTORS_USER/VECTOR in diagram and comparison, ONNX expansion, HNSW index note on slide 11, indexing times updated from 3-run benchmark (avg: PG 12.1s, Ora 12.1s, InDB 13.6s) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
import os
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import time
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from dotenv import load_dotenv
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from db_oracle import get_connection_indb
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load_dotenv()
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PHOTOS_DIR = os.getenv("PHOTOS_DIR")
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def main():
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conn = get_connection_indb()
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cur = conn.cursor()
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cur.execute("SELECT COUNT(*) FROM VECTOR.FOTO_VEKTOR")
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print(f"Rows before: {cur.fetchone()[0]}")
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files = [f for f in os.listdir(PHOTOS_DIR) if f.lower().endswith((".jpg", ".jpeg"))]
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print(f"Found {len(files)} photos in {PHOTOS_DIR}")
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start = time.time()
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for i, filename in enumerate(files, 1):
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filepath = os.path.join(PHOTOS_DIR, filename)
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cur.execute("SELECT 1 FROM VECTOR.FOTO_VEKTOR WHERE filename = :1", (filename,))
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if cur.fetchone():
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print(f"[{i}/{len(files)}] Skipping {filename} (already indexed)")
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continue
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with open(filepath, "rb") as f:
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blob_data = f.read()
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# ORA-24816: Oracle cannot bind the same BLOB as both column value and
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# VECTOR_EMBEDDING() input in one statement. Insert the BLOB first, then
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# let Oracle compute the embedding from the stored data in a second step.
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cur.execute(
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"INSERT INTO VECTOR.FOTO_VEKTOR (filename, foto) VALUES (:1, :2)",
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(filename, blob_data),
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)
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cur.execute(
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"""UPDATE VECTOR.FOTO_VEKTOR
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SET foto_vek = VECTOR_EMBEDDING(CLIP_IMG USING foto AS data)
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WHERE filename = :1""",
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(filename,),
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)
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conn.commit()
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print(f"[{i}/{len(files)}] Indexed {filename}")
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elapsed = time.time() - start
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print(f"Done in {elapsed:.1f} seconds.")
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if __name__ == "__main__":
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main()
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