AI与电影服装设计：机器学习服装的NFT化

// SPDX-License-Identifier: MIT
pragma solidity ^0.8.0;

import "@openzeppelin/contracts/token/ERC721/ERC721.sol";
import "@openzeppelin/contracts/access/Ownable.sol";

contract CostumeDesignNFT is ERC721, Ownable {
    struct Costume {
        uint256 id;
        string name;
        string movieTitle;
        string character;
        string era;
        string aiModel;
        bytes32 designHash;
        address designer;
        uint256 timestamp;
        uint256 royaltyRate;
        uint256 usageCount;
        bool isRegistered;
    }
    
    struct License {
        uint256 licenseId;
        uint256 costumeId;
        address licensee;
        string projectName;
        uint256 fee;
        uint256 duration;
        bool isActive;
    }
    
    mapping(uint256 => Costume) public costumes;
    mapping(uint256 => License[]) public licenses;
    mapping(address => uint256[]) public designerCostumes;
    
    uint256 public costumeCount;
    uint256 public licenseCount;
    uint256 public constant MAX_ROYALTY = 1500; // 15%
    
    event CostumeRegistered(uint256 indexed id, string name, string movieTitle);
    event CostumeLicensed(uint256 indexed costumeId, address indexed licensee, uint256 fee);
    
    constructor() ERC721("CostumeDesign", "CSTD") {}
    
    function registerCostume(
        string memory _name,
        string memory _movieTitle,
        string memory _character,
        string memory _era,
        string memory _aiModel,
        bytes32 _designHash,
        uint256 _royaltyRate
    ) external returns (uint256) {
        require(_royaltyRate <= MAX_ROYALTY, "Royalty too high");
        
        costumeCount++;
        costumes[costumeCount] = Costume({
            id: costumeCount,
            name: _name,
            movieTitle: _movieTitle,
            character: _character,
            era: _era,
            aiModel: _aiModel,
            designHash: _designHash,
            designer: msg.sender,
            timestamp: block.timestamp,
            royaltyRate: _royaltyRate,
            usageCount: 0,
            isRegistered: true
        });
        
        designerCostumes[msg.sender].push(costumeCount);
        _safeMint(msg.sender, costumeCount);
        
        emit CostumeRegistered(costumeCount, _name, _movieTitle);
        return costumeCount;
    }
    
    function licenseCostume(
        uint256 _costumeId,
        string memory _projectName,
        uint256 _fee,
        uint256 _durationDays
    ) external payable {
        require(msg.value >= _fee, "Insufficient fee");
        require(costumes[_costumeId].isRegistered, "Costume not registered");
        
        licenseCount++;
        licenses[_costumeId].push(License({
            licenseId: licenseCount,
            costumeId: _costumeId,
            licensee: msg.sender,
            projectName: _projectName,
            fee: _fee,
            duration: _durationDays * 1 days,
            isActive: true
        }));
        
        costumes[_costumeId].usageCount++;
        payable(costumes[_costumeId].designer).transfer(_fee);
        
        emit CostumeLicensed(_costumeId, msg.sender, _fee);
    }
    
    function getCostumeInfo(uint256 _costumeId)
        external view returns (Costume memory)
    {
        return costumes[_costumeId];
    }
    
    function getDesignerCostumes(address _designer)
        external view returns (uint256[] memory)
    {
        return designerCostumes[_designer];
    }
}

import numpy as np
import pandas as pd
from typing import Dict, List
import matplotlib.pyplot as plt

class CostumeAnalyzer:
    def __init__(self):
        self.costumes = []
        
    def generate_synthetic_data(self, n: int = 50):
        np.random.seed(42)
        eras = ['古代', '中世纪', '维多利亚', '现代', '未来']
        models = ['DALL-E', 'Midjourney', 'StableDiffusion', 'Custom']
        
        for i in range(n):
            costume = {
                'id': i + 1,
                'era': np.random.choice(eras),
                'ai_model': np.random.choice(models),
                'royalty_rate': np.random.uniform(0.01, 0.15),
                'usage_count': np.random.randint(0, 15),
                'total_revenue': np.random.exponential(8000),
                'complexity': np.random.uniform(1, 10)
            }
            self.costumes.append(costume)
    
    def analyze_economy(self) -> Dict:
        df = pd.DataFrame(self.costumes)
        return {
            'total_designs': len(self.costumes),
            'total_revenue': df['total_revenue'].sum(),
            'avg_revenue': df['total_revenue'].mean(),
            'avg_royalty': df['royalty_rate'].mean(),
            'best_era': df.groupby('era')['total_revenue'].sum().idxmax()
        }
    
    def generate_report(self) -> str:
        eff = self.analyze_economy()
        report = f"""
=== AI服装设计经济分析 ===

总设计数: {eff['total_designs']}
总收入: ${eff['total_revenue']:,.2f}
平均收入: ${eff['avg_revenue']:,.2f}
平均版税率: {eff['avg_royalty']:.1%}
最赚钱时代: {eff['best_era']}
"""
        return report


if __name__ == "__main__":
    analyzer = CostumeAnalyzer()
    analyzer.generate_synthetic_data(50)
    report = analyzer.generate_report()
    print(report)

class CostumeManager {
    constructor(providerUrl, contractAddress) {
        this.web3 = new Web3(providerUrl);
        this.contract = new this.web3.eth.Contract([], contractAddress);
    }
    
    async registerCostume(name, movieTitle, character, era, aiModel, designHash, royaltyRate) {
        return await this.contract.methods
            .registerCostume(name, movieTitle, character, era, aiModel, designHash, royaltyRate)
            .send({ from: this.userAccount });
    }
    
    async licenseCostume(costumeId, projectName, fee, durationDays) {
        const feeWei = this.web3.utils.toWei(fee.toString(), 'ether');
        return await this.contract.methods
            .licenseCostume(costumeId, projectName, feeWei, durationDays)
            .send({ from: this.userAccount, value: feeWei });
    }
}

const manager = new CostumeManager('https://mainnet.infura.io/v3/YOUR_ID', '0x...');