# import sys

# from fastapi import FastAPI
# from fastapi.staticfiles import StaticFiles
# version = f"{sys.version_info.major}.{sys.version_info.minor}"

# app = FastAPI()

# # 将 /root/app 目录挂载为静态文件
# app.mount("/files", StaticFiles(directory="/root/app"), name="files")

# @app.get("/")
# async def read_root():
#     message = f"Hello world! From FastAPI running on Uvicorn with Gunicorn. Using Python {version}"
#     return {"message": message}


# from PIL import Image
# import pandas as pd

# # 读取图片
# image_path = '/home/xiazj/ai-station-code/tmp/dimaoshibie/d94afe94-2fae-4ce5-9ee4-94ac1d699337/merge_binary_dimao2.jpg'  # 替换成你的图片路径
# image = Image.open(image_path)

# # 获取图片的RGB数据
# pixels = list(image.getdata())

# # 创建一个DataFrame来统计每种颜色的出现次数
# color_counts = pd.Series(pixels).value_counts()

# # 将颜色统计结果转换为DataFrame
# color_summary = color_counts.reset_index()
# color_summary.columns = ['RGB', 'Count']

# # 打印结果
# print(color_summary)

# # 可选：将结果保存到CSV文件
# color_summary.to_csv('color_summary.csv', index=False)

import pickle

# 指定文件路径
file_path = '/home/xiazj/ai-station-code/tmp/sam/c768f709-b123-48fb-b98b-addf0bbb8a04/model_params.pickle'

# 读取 pickle 文件
with open(file_path, 'rb') as file:
    data,api = pickle.load(file)

# 打印数据
print(data)
print(api)