from typing import List
from pydantic import BaseModel
from lama_cleaner.server import process
import uvicorn
from fastapi import FastAPI
app = FastAPI()
@app.on_event("startup")
async def app_start():
    image_bytes = open('image.jpg', 'rb')
    mask_bytes = open('mask.jpg', 'rb')
    # 将字节数据转换为Base64编码的字符串
    
    files = {
        "image": image_bytes,
        "mask":mask_bytes
    }
    payload = {
            "ldmSteps": 25,
            "ldmSampler": "plms",
            "zitsWireframe": True,
            "hdStrategy": "Crop",
            "hdStrategyCropMargin": 196,
            "hdStrategyCropTrigerSize": 800,
            "hdStrategyResizeLimit": 2048,
            "prompt": "",
            "negativePrompt": "",
            "croperX": 307,
            "croperY": 544,
            "croperHeight": 512,
            "croperWidth": 512,
            "useCroper": False,
            "sdMaskBlur": 5,
            "sdStrength": 0.75,
            "sdSteps": 50,
            "sdGuidanceScale": 7.5,
            "sdSampler": "uni_pc",
            "sdSeed": -1,
            "sdMatchHistograms": False,
            "sdScale": 1,
            "cv2Radius": 5,
            "cv2Flag": "INPAINT_NS",
            "paintByExampleSteps": 50,
            "paintByExampleGuidanceScale": 7.5,
            "paintByExampleSeed": -1,
            "paintByExampleMaskBlur": 5,
            "paintByExampleMatchHistograms": False,
            "p2pSteps": 50,
            "p2pImageGuidanceScale": 1.5,
            "p2pGuidanceScale": 7.5,
            "controlnet_conditioning_scale": 0.4,
            "controlnet_method": "control_v11p_sd15_canny"
        }#payload用data
    
    resp = process(files=files,payload=payload)
    print(resp)
if __name__ == '__main__':
    uvicorn.run(app, host='0.0.0.0', port=7860)