70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
from fastapi import FastAPI, UploadFile, HTTPException
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from pydantic import BaseModel
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from PIL import Image
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import io
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import base64
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import cv2
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import numpy as np
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def opencv_image_to_bytes(opencv_image):
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"""将 OpenCV 图像对象转换为 bytes 对象"""
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# 使用 cv2.imencode() 将图像编码为 numpy 数组
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ret, buffer = cv2.imencode('.jpg', opencv_image)
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# 将 numpy 数组转换为 bytes
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img_bytes = buffer.tobytes()
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return img_bytes
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def handleImageByCV2(bs: bytes) -> {int, bytes}:
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# 读取图像
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img = cv2.imdecode(np.frombuffer(bs, np.uint8), cv2.IMREAD_COLOR)
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# 将图像转换为灰度图
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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# 使用高斯模糊处理图像
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blurred = cv2.GaussianBlur(gray, (9, 9), 2)
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# 使用霍夫圆检测法检测圆圈
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circles = cv2.HoughCircles(blurred, cv2.HOUGH_GRADIENT, dp=1.2, minDist=30,
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param1=80, param2=38, minRadius=15, maxRadius=60)
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# 确认至少检测到一个圆圈
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if circles is not None:
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circles = np.round(circles[0, :]).astype("int")
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print(f"检测到 {len(circles)} 个圆圈")
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for i, (x, y, r) in enumerate(circles, start=1): # 从1开始计数
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# 在图像中绘制圆圈
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cv2.circle(img, (x, y), r, (0, 255, 0), 4)
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# 在图像中绘制圆心
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cv2.circle(img, (x, y), 2, (0, 128, 255), 3)
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# 在图像中绘制圆圈编号
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cv2.putText(img, f'{i}', (x - 10, y + 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
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return len(circles), opencv_image_to_bytes(img)
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else:
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return 0, opencv_image_to_bytes(img)
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app = FastAPI()
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class ImageResponse(BaseModel):
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image_base64: str
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circle_count: int
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@app.post("/upload_image", response_model=ImageResponse)
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async def upload_image(image_file: UploadFile):
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if not(image_file.filename.endswith('.jpg') or image_file.filename.endswith('.jpeg')):
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raise HTTPException(status_code=400, detail="Only jpg or jpeg files are supported")
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image_bytes = await image_file.read()
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count, new_bytes = handleImageByCV2(image_bytes)
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img_base64 = base64.b64encode(new_bytes).decode('utf-8')
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return ImageResponse(image_base64=img_base64, circle_count=count)
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if __name__ == '__main__':
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000) |