Introduction to OpenAI

Vision

Practical Vision Applications

In this guide, we explore five high-impact use cases for vision models such as OpenAI’s CLIP and DALL·E. From retail automation to autonomous navigation, these applications showcase how computer vision drives efficiency and innovation.

Application AreaKey Benefit
Image Classification for E-commerceAutomatic tagging, improved search, seamless catalog uploads
Object Detection & Security SystemsReal-time intrusion alerts and crowd monitoring
Medical Image AnalysisRapid detection of fractures, tumors, and other abnormalities
Visual Search in RetailImage-based product discovery and style recommendations
Autonomous VehiclesObject, lane, and obstacle detection for self-driving cars

1. Image Classification for E-commerce

Automated image classification helps online retailers tag thousands of products by style, material, or color—boosting search relevance and reducing manual effort.

  • Automatically label new inventory
  • Enhance on-site search filters
  • Maintain consistent metadata across catalogs

Best Practice

Use high‐quality, well-lit images to improve classification accuracy. Crop tightly around the product to reduce background noise.

The image outlines the benefits of image classification for e-commerce, highlighting automatic product classification, improved searchability, automatic labeling, and usefulness for large catalogs.

Example: Identify the contents of a product image via URL using OpenAI’s Vision API.

from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": [
            {"type": "text", "text": "What’s in this image?"},
            {"type": "image_url", "image_url": {
                "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
            }}
        ]}
    ],
    max_tokens=300,
)

print(response.choices[0].message.content)

The model accurately describes a scenic outdoor boardwalk framed by trees, greenery, blue sky, and clouds.


2. Object Detection and Security Systems

Real-time object detection enables smart surveillance solutions that identify people, vehicles, and unauthorized access in critical areas.

  • Intrusion detection in restricted zones
  • Automated alerts for security teams
  • Crowd density monitoring and flow analysis

Performance Tip

Deploy inference on edge devices to minimize latency and avoid sending raw video feeds over the network.

The image is an infographic about object detection in security systems, highlighting its core applications and examples like real-time intrusion detection and identifying unauthorized entry.

A typical workflow: the camera detects a person in a no-entry zone and instantly notifies on-duty personnel.


3. Medical Image Analysis

Vision models support radiologists by quickly flagging anomalies in X-rays, CT scans, and MRIs—helping to detect fractures, tumors, and infections with high sensitivity.

The image is a slide titled "Medical Image Analysis," highlighting its applications in diagnosing diseases, analyzing X-rays, CT scans, MRIs, and identifying abnormalities.

Warning

This tool is for preliminary assessment only. Always consult a licensed medical professional for diagnosis and treatment.

Example: Detecting a Forearm Fracture

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": [
            {"type": "text", "text": "Examine this medical image. Explain what the injury is."},
            {"type": "image_url", "image_url": {
                "url": "https://media02.stockfood.com/largepreviews/MzU50Dg1NTQx/11609211-Broken-arm-X-ray.jpg"
            }}
        ]}
    ],
    max_tokens=300,
)

print(response.choices[0].message.content)

The model pinpoints a fractured radius and ulna, illustrating its potential for faster preliminary diagnoses.


4. Visual Search in Retail

Visual search transforms online shopping by letting users upload photos to find matching or similar products—driving higher engagement and conversion rates.

  • Snap-and-search for apparel, accessories, or home decor
  • Instantly retrieve visually similar catalog items
  • Personalize recommendations based on style features

The image is a slide titled "Visual Search in Retail," highlighting its role in enhancing the shopping experience by allowing customers to upload images for matching.

A shopper uploads a photo of a pair of sneakers, and the system returns available styles with comparable color, design, and brand.


5. Autonomous Vehicles

Self-driving cars rely on computer vision for perception tasks crucial to safe navigation:

  • Real-time object detection (vehicles, pedestrians, traffic signals)
  • Lane and road edge detection
  • Dynamic obstacle avoidance

Example: Road Scene Description

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": [
            {"type": "text", "text": "You are an autonomous vehicle. Describe what you detect in front of you."}
        ]},
        {"role": "user", "content": [
            {"type": "image_url", "image_url": {
                "url": "https://media.istockphoto.com/id/636690722/photo/driving-at-sunset-view-from-the-driver-angle-car-focusinside.jpg?s=612x612&w=0&k=20&c=B-D5L7GVi93AhjfoLngbxHB8AEBjXPk_ZQ8tZEmSBo="
            }}
        ]}
    ],
    max_tokens=300,
)

print(response.choices[0].message.content)

The model identifies traffic lights, nearby cars, lane markings, road conditions, and potential pedestrians—demonstrating robust scene understanding.


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