Training an AI to detect military vehicles, such as tanks and IFVs, requires a lot of high-quality images. The challenge isn’t just collecting these images, but also doing it efficiently. That’s where using a custom Google search engine with an API comes in. I’ve set up a process that helps me gather the images I need to train my AI without spending too much time or effort.
Setting Up Your Own Google Custom Search Engine
First, you need to create a custom search engine on Google. This allows you to narrow down your search results to specific websites or topics, making it easier to find the images you're looking for.
Here’s a simple guide to setting it up:
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Go to Google Custom Search and click on "Create a custom search engine."
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Enter your desired topics or websites that relate to military vehicles. For example, you could use websites like military news sites or image repositories.
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Once set up, Google gives you a unique API key to use in your script. Keep this key safe, as it’s your access to Google’s search engine.
Using the Google API to Pull Images
Now that you have your custom search engine, it’s time to automate the process of pulling images. With a simple Python script, you can use the Google Custom Search API to download images.
Here’s a basic script you can use:
import requests import os import re API_KEY = "API_KEY_HERE" CX = "Search_Engine_Key" def sanitize_folder_name(name): # Remove any characters that are not allowed in filenames or directories return re.sub(r'[<>:"/\\|?*]', '', name) def search_images(query, num_images=100): print(f"Searching for: {query}") search_url = "https://www.googleapis.com/customsearch/v1" image_urls = [] # Calculate how many requests we need to make (10 results per request) for start_index in range(1, num_images+1, 10): params = { "q": query, "cx": CX, "key": API_KEY, "searchType": "image", "num": 10, "start": start_index, # Start from the next index } response = requests.get(search_url, params=params) print(f"Status code: {response.status_code}") try: data = response.json() except Exception as e: print("Error parsing JSON:", e) print("Raw response:", response.text) return # Extract image links inside the function items = data.get("items", []) image_urls.extend(