feat: 简单的接口

.gitignore

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+.vscode
+.idea
+venv
+*.jpg
+*.jpeg
+.DS_Store

main.py

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+import cv2
+import numpy as np
+
+def detect_circles(image_path):
+    # 读取图像
+    img = cv2.imread(image_path, cv2.IMREAD_COLOR)
+    
+    # 将图像转换为灰度图
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    
+    # 使用高斯模糊处理图像
+    blurred = cv2.GaussianBlur(gray, (9, 9), 2)
+    
+    # 使用霍夫圆检测法检测圆圈
+    circles = cv2.HoughCircles(blurred, cv2.HOUGH_GRADIENT, dp=1.2, minDist=30,
+                               param1=80, param2=38, minRadius=15, maxRadius=60)
+    
+    # 确认至少检测到一个圆圈
+    if circles is not None:
+        circles = np.round(circles[0, :]).astype("int")
+        
+        print(f"检测到 {len(circles)} 个圆圈")
+        for i, (x, y, r) in enumerate(circles, start=1): # 从1开始计数
+            # 在图像中绘制圆圈
+            cv2.circle(img, (x, y), r, (0, 255, 0), 4)
+            # 在图像中绘制圆心
+            cv2.circle(img, (x, y), 2, (0, 128, 255), 3)
+            # 在图像中绘制圆圈编号
+            cv2.putText(img, f'{i}', (x - 10, y + 10), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
+
+        # 显示结果图像并处理退出事件
+        while True:
+            cv2.imshow("detected circles", img)
+            key = cv2.waitKey(1) & 0xFF
+            if key == 27:  # ESC键的ASCII码是27
+                break
+                
+        cv2.destroyAllWindows()
+    else:
+        print("没有检测到圆圈")
+
+# 调用函数并传递图像路径
+detect_circles("image2.jpg")

requirements.txt

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+annotated-types==0.7.0
+anyio==4.4.0
+certifi==2024.6.2
+click==8.1.7
+dnspython==2.6.1
+email_validator==2.1.1
+exceptiongroup==1.2.1
+fastapi==0.111.0
+fastapi-cli==0.0.4
+h11==0.14.0
+httpcore==1.0.5
+httptools==0.6.1
+httpx==0.27.0
+idna==3.7
+Jinja2==3.1.4
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+mdurl==0.1.2
+numpy==1.26.4
+opencv-python==4.10.0.82
+orjson==3.10.3
+pillow==10.3.0
+pydantic==2.7.3
+pydantic_core==2.18.4
+Pygments==2.18.0
+python-dotenv==1.0.1
+python-multipart==0.0.9
+PyYAML==6.0.1
+rich==13.7.1
+shellingham==1.5.4
+sniffio==1.3.1
+starlette==0.37.2
+typer==0.12.3
+typing_extensions==4.12.1
+ujson==5.10.0
+uvicorn==0.30.1
+uvloop==0.19.0
+watchfiles==0.22.0
+websockets==12.0

svc.py

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