改进 响应

main.py

@@ -1,13 +1,18 @@
 import asyncio
 import os
+import pprint
 from typing import Optional
 
 import aiohttp  # 用于异步 HTTP 请求
 import easyocr
 import torch
+import uvicorn
 from fastapi import FastAPI, UploadFile, File, Query
 from fastapi.responses import JSONResponse
 
+import response
+from response import OCRResponse
+
 MODEL_DIR = "./models"
 USE_GPU = os.environ.get('USE_GPU', 'false') == 'true'
 NNPACK = os.environ.get('NNPACK', 'false') == 'true'
@@ -83,51 +88,70 @@ async def process_ocr(reader, image_data):
 
         # 成功处理后返回数据
         return {
-            "status": "success",
+            "status": bool,
-            "message": "OCR 处理成功",
             "data": output
         }, 200
     except Exception as e:
         # 处理失败，返回错误信息
         return {
-            "status": "error",
+            "status": bool,
-            "message": "OCR 处理失败",
             "error": str(e),
             "data": None
         }, 500
 
 
 @app.post("/ocr")
-async def ocr_image(lang_1: Optional[str] = None, lang_2: Optional[str] = None, image: UploadFile = File(...)):
+async def ocr_image(lang_1: Optional[str] = None, lang_2: Optional[str] = None, image: UploadFile = File(...)) \
+        -> OCRResponse:
     # 获取 OCR 读取器并捕获可能的错误
     reader, error = await get_reader(lang_1, lang_2)
 
     if error:
-        return JSONResponse(status_code=500, content={
+        return OCRResponse(
-            "status": "error",
+            success=False,
-            "message": "OCR 处理失败",
+            message="OCR 处理失败",
-            "error": error,
+            data=None,
-            "data": None
+            error=error
-        })
+        )
 
     try:
         # 获取图片的二进制数据
         image_data = await image.read()
     except Exception as e:
-        return JSONResponse(status_code=500, content={
+        return OCRResponse(
-            "status": "error",
+            success=False,
-            "message": "无法读取图片文件",
+            message="无法读取图片文件",
-            "error": str(e),
+            data=None,
-            "data": None
+            error=error
-        })
+        )
 
     # 调用通用的 OCR 处理函数
-    response_data, status_code = await process_ocr(reader, image_data)
+    ocr_data, status_code = await process_ocr(reader, image_data)
-    return JSONResponse(status_code=status_code, content=response_data)
+    full_text = ""
+    ocr_data_list = list()
+    for entry in ocr_data["data"]:
+        full_text += entry["text"]
+        r = response.OCRData(
+            text=entry["text"],
+            bbox=entry["bbox"],
+            confidence=entry["confidence"]
+        )
+
+        ocr_data_list.append(r)
+    # 返回 OCR 处理结果
+    pprint.pprint(ocr_data)
+
+    return OCRResponse(
+        success=True,
+        data=ocr_data_list,
+        error=None,
+        message=None,
+    )
 
 
 @app.get("/ocr")
-async def ocr_image_from_url(lang_1: Optional[str] = None, lang_2: Optional[str] = None, url: str = Query(...)):
+async def ocr_image_from_url(lang_1: Optional[str] = None, lang_2: Optional[str] = None,
+                             url: str = Query(...)) -> OCRResponse:
     # 使用 aiohttp 进行异步 HTTP 请求
     async with aiohttp.ClientSession() as session:
         try:
@@ -136,25 +160,34 @@ async def ocr_image_from_url(lang_1: Optional[str] = None, lang_2: Optional[str]
                     raise Exception(f"无法获取图片, HTTP 状态码: {response.status}")
                 # 读取图片数据
                 image_data = await response.read()
+
         except Exception as e:
-            return JSONResponse(status_code=500, content={
+            return OCRResponse(
-                "status": "error",
+                success=False,
-                "message": "无法从 URL 获取图片",
+                message="无法从 URL 获取图片",
-                "error": str(e),
+                data=None,
-                "data": None
+                error=str(e),
-            })
+            )
 
     # 获取 OCR 读取器并捕获可能的错误
     reader, error = await get_reader(lang_1, lang_2)
 
     if error:
-        return JSONResponse(status_code=500, content={
+        return OCRResponse(
-            "status": "error",
+            success=False,
-            "message": "OCR 处理失败",
+            message="OCR 处理失败",
-            "error": error,
+            data=None,
-            "data": None
+            error=error,
-        })
+        )
 
     # 调用通用的 OCR 处理函数
-    response_data, status_code = await process_ocr(reader, image_data)
+    ocr_data, status_code = await process_ocr(reader, image_data)
-    return JSONResponse(status_code=status_code, content=response_data)
+
+    return OCRResponse(
+        success=True,
+        data=ocr_data,
+    )
+
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=8000)

response.py

@@ -0,0 +1,15 @@
+from pydantic import BaseModel
+from typing import List, Optional
+
+
+class OCRData(BaseModel):
+    text: str
+    bbox: List[List[int]]  # 这里使用 List[List[int]] 来表示多个坐标点
+    confidence: float
+
+
+class OCRResponse(BaseModel):
+    success: bool
+    error: Optional[str]
+    message: Optional[str]
+    data: Optional[List[OCRData]] = []