This is a continuation of previous article to reduce the number of objects detected and catalogued from aerial drone images for optimum performance. One technique to do so is to lookup the vector store for a similar image and skip it unless the timestamp exceeds the time range for the current flight.

Sample:

import requests

import json

import sys

import os

import numpy as np

# Add the parent folder to the module search path

sys.path.insert(0, os.path.abspath(".."))

from visionprocessor.vectorizer import vectorize_image

# Azure AI Search configurations

search_endpoint = os.getenv("AZURE_SEARCH_SERVICE_ENDPOINT")

index_name = os.getenv("AZURE_SEARCH_INDEX_NAME")

search_api_key = os.getenv("AZURE_SEARCH_ADMIN_KEY")

vision_api_key = os.getenv("AZURE_AI_VISION_API_KEY")

# Query string for red cars

query_text = "Find red cars in drone images"

blob_url = "<BLOB_SAS_URL>"

vector = vectorize_image(blob_url, vision_api_key, "eastus")

vector = np.pad(vector, (0, 1536 - len(vector)), mode='constant')

# print(f"len={len(vector)}")

# Vector search payload

body = {

        "count": True,

        "select": "id,description,vector",

        "vectorQueries": [

            {

                "vector": vector.tolist(),

                "k": 5,

                "fields": "vector",

                "kind": "vector",

                "exhaustive": True

            }

        ]

    }

# Headers for Azure Search API

headers = {

    "Content-Type": "application/json",

    "api-key": search_api_key

}

# Send search request to Azure AI Search

response = requests.post(

    f"{search_endpoint}/indexes/{index_name}/docs/search?api-version=2024-07-01",

    headers=headers,

    data=json.dumps(body)

)

# Parse response

search_results = response.json()

print(len(search_results))

print(search_results)

ids = ",".join([item["id"] for item in search_results.get("value", [])]).strip(",")

print(ids)

# output:

# RedCar3: 015644,015643,012669,008812,011600

# RedCar4: 014076,014075,014077,014074,014543

# Count occurrences of "red car" in descriptions

red_car_count = sum(1 for item in search_results.get("value", []) if "red car" in item["description"].lower())

print(f"Total red cars found in drone images: {red_car_count}")

Reference: previous article: https://1drv.ms/w/c/d609fb70e39b65c8/EVdJ7oJaqFFAvkx9udkFX1UBC0KcZkrPJU6k5yTdwcZlNg?e=LR1SYf