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APIYI provides powerful image understanding capabilities, supporting deep analysis and understanding of images using various advanced AI models. Through a unified OpenAI API format, you can easily implement image recognition, scene description, OCR text recognition, and other functions.
🔍 Intelligent Visual Analysis Supports various visual tasks including object recognition, scene understanding, text extraction, sentiment analysis, and more, enabling AI to truly “understand” images.

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🌟 Core Features

  • 🎯 Multi-Model Support: Top vision models like GPT-4o, Gemini 2.5 Pro, Claude, etc.
  • 📸 Flexible Input: Supports URL links and Base64 encoded images
  • 🌏 Chinese Optimization: Perfect support for Chinese scene understanding and text recognition
  • ⚡ Fast Response: High-performance inference with second-level results
  • 💰 Cost Control: Multiple model options to meet different budget requirements

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📋 Supported Vision Models

Model NameModel IDFeaturesRecommended Scenarios
GPT-4o ⭐gpt-4oStrong comprehensive abilities, accurate recognitionGeneral image understanding
GPT-4.1 Minigpt-4.1-miniLightweight and fast, low costBatch processing
Gemini 2.5 Pro ⭐gemini-2.5-proUltra-long context, rich detailsComplex scene analysis
Gemini 2.5 Flashgemini-2.5-flashExtremely fast, high cost-performanceReal-time applications
Claude 3.5 Sonnetclaude-3-5-sonnetDeep understanding, accurate descriptionsProfessional analysis

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🚀 Quick Start

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1. Basic Example - Image URL

import requests

url = "https://api.apiyi.com/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "model": "gpt-4o",
    "messages": [
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Please describe this image in detail"
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://example.com/image.jpg"
                    }
                }
            ]
        }
    ]
}

response = requests.post(url, headers=headers, json=payload)
result = response.json()
print(result['choices'][0]['message']['content'])

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2. Local Image Example - Base64 Encoding

import base64
import requests

def image_to_base64(image_path):
    """Convert local image to base64 encoding"""
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

# Read local image
base64_image = image_to_base64("path/to/your/image.jpg")

url = "https://api.apiyi.com/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "model": "gemini-2.5-pro",
    "messages": [
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Analyze all text content in this image"
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": f"data:image/jpeg;base64,{base64_image}"
                    }
                }
            ]
        }
    ]
}

response = requests.post(url, headers=headers, json=payload)
print(response.json()['choices'][0]['message']['content'])

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3. Advanced Example - Multi-Image Comparison

import requests

url = "https://api.apiyi.com/v1/chat/completions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "model": "gpt-4o",
    "messages": [
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Please compare the differences between these two images:"},
                {
                    "type": "image_url",
                    "image_url": {"url": "https://example.com/image1.jpg"}
                },
                {
                    "type": "image_url",
                    "image_url": {"url": "https://example.com/image2.jpg"}
                }
            ]
        }
    ],
    "max_tokens": 1000
}

response = requests.post(url, headers=headers, json=payload)
print(response.json()['choices'][0]['message']['content'])

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🎯 Common Use Cases

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1. Product Recognition and Analysis

prompt = """
Please analyze this product image, including:
1. Product type and brand
2. Main features and selling points
3. Suitable target audience
4. Suggested marketing copy
"""

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2. Document OCR Recognition

prompt = """
Please extract all text content from the image and organize it in the original format.
If there are tables, please present them in Markdown table format.
"""

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3. Medical Imaging Assistance

prompt = """
This is a medical imaging picture, please:
1. Describe basic image information (such as imaging type, body part, etc.)
2. Label visible anatomical structures
3. Note: For reference only, not for diagnostic purposes
"""

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4. Security Surveillance Analysis

prompt = """
Analyze the surveillance footage to identify:
1. Number of people and their positions in the scene
2. Any abnormal behavior
3. Environmental safety hazards
4. Timestamp information (if visible)
"""

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💡 Best Practices

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Image Preprocessing Recommendations

  1. Format Support: Mainstream formats like JPEG, PNG, GIF, WebP
  2. Size Limit: Recommended single image under 20MB
  3. Resolution: Higher resolution images achieve better recognition
  4. Compression: Moderate compression to improve transfer speed

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Prompt Optimization

# ❌ Not Recommended: Vague prompt
prompt = "What is this"

# ✅ Recommended: Specific and clear prompt
prompt = """
Please analyze this image from the following aspects:
1. Main Objects: Identify main objects or people in the image
2. Scene Environment: Describe the shooting location and environmental features
3. Color Composition: Analyze color scheme and composition characteristics
4. Emotional Atmosphere: Emotions or atmosphere conveyed by the image
5. Possible Uses: What scenarios this image is suitable for
"""

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Error Handling

import requests
from requests.exceptions import RequestException

def analyze_image_with_retry(image_url, prompt, max_retries=3):
    """Image analysis function with retry mechanism"""
    for attempt in range(max_retries):
        try:
            response = requests.post(
                "https://api.apiyi.com/v1/chat/completions",
                headers={
                    "Authorization": f"Bearer {API_KEY}",
                    "Content-Type": "application/json"
                },
                json={
                    "model": "gpt-4o",
                    "messages": [{
                        "role": "user",
                        "content": [
                            {"type": "text", "text": prompt},
                            {"type": "image_url", "image_url": {"url": image_url}}
                        ]
                    }]
                },
                timeout=30
            )

            if response.status_code == 200:
                return response.json()
            elif response.status_code == 429:
                print(f"Rate limited, waiting to retry... (attempt {attempt + 1}/{max_retries})")
                time.sleep(2 ** attempt)  # Exponential backoff
            else:
                print(f"Error: {response.status_code} - {response.text}")

        except RequestException as e:
            print(f"Request exception: {e}")

    return None

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🔧 Advanced Features

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1. Streaming Output

For lengthy analyses, streaming output provides better user experience: 
payload = {
    "model": "gpt-4o",
    "messages": [...],
    "stream": True
}

response = requests.post(url, headers=headers, json=payload, stream=True)
for line in response.iter_lines():
    if line:
        print(line.decode('utf-8'))

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2. Multi-turn Conversation

Maintain context for in-depth analysis: 
messages = [
    {
        "role": "user",
        "content": [
            {"type": "text", "text": "What animal is this?"},
            {"type": "image_url", "image_url": {"url": "animal.jpg"}}
        ]
    },
    {
        "role": "assistant",
        "content": "This is a Golden Retriever."
    },
    {
        "role": "user",
        "content": [{"type": "text", "text": "How old does it look? How is its health condition?"}]
    }
]

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3. Combined with Function Calling

tools = [
    {
        "type": "function",
        "function": {
            "name": "save_image_analysis",
            "description": "Save image analysis results to database",
            "parameters": {
                "type": "object",
                "properties": {
                    "objects": {"type": "array", "items": {"type": "string"}},
                    "scene": {"type": "string"},
                    "text_content": {"type": "string"}
                }
            }
        }
    }
]

payload = {
    "model": "gpt-4o",
    "messages": messages,
    "tools": tools,
    "tool_choice": "auto"
}

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📊 Performance Comparison

ModelResponse SpeedRecognition AccuracyChinese SupportPrice
GPT-4o⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐$$
Gemini 2.5 Pro⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐$$
Gemini 2.5 Flash⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐$
GPT-4.1 Mini⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐$

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🚨 Important Notes

  1. Privacy Protection: Do not upload images containing sensitive information
  2. Compliant Usage: Follow relevant laws and regulations, do not use for illegal purposes
  3. Result Verification: AI analysis results are for reference only, important decisions require manual review
  4. Cost Control: Choose models reasonably to avoid unnecessary expenses
💡 Pro Tip: Recommend testing with GPT-4.1 Mini or Gemini 2.5 Flash first, then use advanced models for production deployment after confirming effectiveness.