获取API密钥

OpenClaw API 是一个用于AI小龙虾图像识别、数据分析等功能的API接口，以下是基本使用方法：

准备工作

注册与认证

- 在控制台创建应用，获取API Key和Secret

API基础配置

Python 示例

import requests
import base64
import json
class OpenClawAPI:
    def __init__(self, api_key, api_secret):
        self.api_key = api_key
        self.api_secret = api_secret
        self.base_url = "https://api.openclaw.ai/v1"
        self.headers = {
            "Content-Type": "application/json",
            "Authorization": f"Bearer {api_key}"
        }
    def _make_request(self, endpoint, method="POST", data=None):
        url = f"{self.base_url}/{endpoint}"
        response = requests.request(
            method=method,
            url=url,
            headers=self.headers,
            json=data
        )
        return response.json()

核心功能调用

1 图像识别（小龙虾检测）

def detect_crayfish(self, image_path):
    """
    检测图片中的小龙虾
    """
    # 方式1：使用Base64编码
    with open(image_path, "rb") as image_file:
        image_base64 = base64.b64encode(image_file.read()).decode()
    data = {
        "image": image_base64,
        "model": "crayfish-detection-v2",
        "confidence_threshold": 0.5
    }
    return self._make_request("detection", data=data)

2 尺寸测量

def measure_size(self, image_path, reference_object_size=10):
    """
    测量小龙虾尺寸（需提供参照物尺寸，单位：cm）
    """
    with open(image_path, "rb") as f:
        image_data = base64.b64encode(f.read()).decode()
    data = {
        "image": image_data,
        "reference_size": reference_object_size,
        "unit": "cm"
    }
    return self._make_request("measurement", data=data)

3 健康状况分析

def health_analysis(self, image_path):
    """
    分析小龙虾健康状况
    """
    data = {
        "image": self._encode_image(image_path),
        "analysis_type": "health",
        "features": ["shell_color", "activity", "limb_integrity"]
    }
    return self._make_request("analysis/health", data=data)

批量处理示例

def batch_process(self, image_paths):
    """
    批量处理多张图片
    """
    results = []
    for img_path in image_paths:
        result = self.detect_crayfish(img_path)
        if result.get("success"):
            results.append({
                "filename": img_path,
                "count": result["data"]["count"],
                "sizes": result["data"]["sizes"]
            })
    return results

错误处理

def safe_detection(self, image_path):
    try:
        response = self.detect_crayfish(image_path)
        if response.get("code") == 200:
            return {
                "success": True,
                "data": response["data"]
            }
        else:
            return {
                "success": False,
                "error": response.get("message", "Unknown error")
            }
    except requests.exceptions.RequestException as e:
        return {
            "success": False,
            "error": f"Network error: {str(e)}"
        }

使用示例

# 初始化客户端
api = OpenClawAPI(
    api_key="your_api_key_here",
    api_secret="your_api_secret_here"
)
# 单张图片检测
result = api.detect_crayfish("crayfish.jpg")
print(f"检测到 {result['count']} 只小龙虾")
# 尺寸测量
measurement = api.measure_size(
    image_path="crayfish_with_scale.jpg",
    reference_object_size=5  # 参照物实际尺寸5cm
)
print(f"小龙虾长度：{measurement['length_cm']} cm")
# 批量处理
images = ["farm1.jpg", "farm2.jpg", "farm3.jpg"]
batch_results = api.batch_process(images)

异步调用（可选）

import aiohttp
import asyncio
async def async_detect(image_paths):
    async with aiohttp.ClientSession() as session:
        tasks = []
        for img_path in image_paths:
            task = self._async_detect_single(session, img_path)
            tasks.append(task)
        results = await asyncio.gather(*tasks)
        return results

参数说明

注意事项

1. API限制：注意查看API调用频率限制和配额
2. 图片要求：建议图片大小<10MB，格式为JPG/PNG
3. 认证安全：妥善保管API密钥，不要在客户端暴露
4. 网络要求：确保网络稳定，建议设置超时时间

获取帮助

• 官方文档：https://docs.openclaw.ai
• API状态：https://status.openclaw.ai
• 技术支持：support@openclaw.ai

请根据实际API文档调整具体参数和端点地址。

标签： API 密钥