53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
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# import sys
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# from fastapi import FastAPI
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# from fastapi.staticfiles import StaticFiles
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# version = f"{sys.version_info.major}.{sys.version_info.minor}"
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# app = FastAPI()
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# # 将 /root/app 目录挂载为静态文件
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# app.mount("/files", StaticFiles(directory="/root/app"), name="files")
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# @app.get("/")
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# async def read_root():
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# message = f"Hello world! From FastAPI running on Uvicorn with Gunicorn. Using Python {version}"
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# return {"message": message}
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# from PIL import Image
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# import pandas as pd
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# # 读取图片
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# 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
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# image = Image.open(image_path)
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# # 获取图片的RGB数据
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# pixels = list(image.getdata())
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# # 创建一个DataFrame来统计每种颜色的出现次数
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# color_counts = pd.Series(pixels).value_counts()
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# # 将颜色统计结果转换为DataFrame
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# color_summary = color_counts.reset_index()
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# color_summary.columns = ['RGB', 'Count']
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# # 打印结果
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# print(color_summary)
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# # 可选：将结果保存到CSV文件
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# color_summary.to_csv('color_summary.csv', index=False)
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import pickle
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# 指定文件路径
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file_path = '/home/xiazj/ai-station-code/tmp/sam/c768f709-b123-48fb-b98b-addf0bbb8a04/model_params.pickle'
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# 读取 pickle 文件
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with open(file_path, 'rb') as file:
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data,api = pickle.load(file)
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# 打印数据
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print(data)
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print(api)
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