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from fastapi import FastAPI, UploadFile, File |
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from fastapi.responses import JSONResponse |
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from paddleocr import PaddleOCR |
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import numpy as np |
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from PIL import Image |
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from io import BytesIO |
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import requests |
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app = FastAPI( |
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title="PaddleOCR API", |
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description="OCR via URL or File Upload", |
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version="1.0.0" |
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) |
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ocr = PaddleOCR( |
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lang="en", |
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det_model_dir=None, |
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rec_model_dir=None, |
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use_angle_cls=False |
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) |
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def run_ocr(image_bytes: bytes): |
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img = Image.open(BytesIO(image_bytes)).convert("RGB") |
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img_np = np.array(img) |
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result = ocr.predict(img_np) |
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outputs = [] |
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parsed_texts = [] |
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for res in result: |
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boxes = res.get("rec_boxes", []) |
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texts = res.get("rec_texts", []) |
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scores = res.get("rec_scores", []) |
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for box, text, score in zip(boxes, texts, scores): |
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parsed_texts.append(text) |
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outputs.append({ |
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"text": text, |
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"confidence": float(score), |
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"bounding_box": box.tolist() |
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}) |
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return { |
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"results": outputs, |
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"parsedText": parsed_texts, |
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"finalText": " ".join(parsed_texts) |
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} |
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@app.get("/ocr") |
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async def ocr_from_url(url: str): |
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try: |
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response = requests.get(url, timeout=15) |
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response.raise_for_status() |
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data = run_ocr(response.content) |
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return JSONResponse({ |
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"success": True, |
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**data |
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}) |
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except Exception as e: |
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return JSONResponse( |
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status_code=400, |
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content={ |
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"success": False, |
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"error": str(e) |
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} |
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) |
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@app.post("/ocr") |
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async def ocr_from_file(file: UploadFile = File(...)): |
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try: |
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image_bytes = await file.read() |
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data = run_ocr(image_bytes) |
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return JSONResponse({ |
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"success": True, |
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**data |
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}) |
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except Exception as e: |
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return JSONResponse( |
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status_code=400, |
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content={ |
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"success": False, |
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"error": str(e) |
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} |
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) |
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