paddle ocr suport

backend/ocr-server/server.py

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+import os
+import base64
+import logging
+from io import BytesIO
+
+import numpy as np
+from fastapi import FastAPI, UploadFile, File
+from fastapi.responses import JSONResponse
+from paddleocr import PaddleOCR
+from pydantic import BaseModel
+from PIL import Image
+
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("paddleocr-server")
+
+OCR_LANG = os.getenv("OCR_LANG", "fr")
+
+print(f"[INIT] Initializing PaddleOCR (lang={OCR_LANG})...", flush=True)
+ocr_engine = PaddleOCR(
+    use_doc_orientation_classify=False,
+    use_doc_unwarping=False,
+    use_textline_orientation=False,
+    lang=OCR_LANG,
+)
+print("[INIT] PaddleOCR ready.", flush=True)
+
+app = FastAPI()
+
+
+class OCRRequest(BaseModel):
+    image: str
+
+
+@app.get("/health")
+def health():
+    return {"status": "healthy", "service": "PaddleOCR Server"}
+
+
+@app.post("/ocr")
+def ocr_json(req: OCRRequest):
+    print(f"[OCR] Request received, image field length: {len(req.image)}", flush=True)
+    try:
+        img_bytes = base64.b64decode(req.image)
+    except Exception as e:
+        print(f"[OCR] Base64 decode failed: {e}", flush=True)
+        return JSONResponse(
+            status_code=400,
+            content={"errorCode": 1, "message": "invalid base64 image"},
+        )
+    print(f"[OCR] Decoded {len(img_bytes)} bytes, header: {img_bytes[:32].hex()}", flush=True)
+    return run_ocr(img_bytes)
+
+
+@app.post("/ocr/upload")
+def ocr_upload(file: UploadFile = File(...)):
+    img_bytes = file.file.read()
+    print(f"[OCR] Upload received, {len(img_bytes)} bytes, header: {img_bytes[:32].hex()}", flush=True)
+    return run_ocr(img_bytes)
+
+
+def run_ocr(img_bytes: bytes):
+    try:
+        image = Image.open(BytesIO(img_bytes))
+        if image.mode != "RGB":
+            image = image.convert("RGB")
+        img_array = np.array(image)
+        print(f"[OCR] Image decoded: {img_array.shape}", flush=True)
+    except Exception as e:
+        print(f"[OCR] Image decode FAILED: {e}", flush=True)
+        return JSONResponse(
+            status_code=400,
+            content={"errorCode": 1, "message": f"failed to decode image: {e}"},
+        )
+
+    try:
+        result = list(ocr_engine.predict(img_array))
+
+        pages = []
+        for r in result:
+            raw = r._to_json()
+            data = raw.get("res", raw)
+            pages.append({
+                "rec_texts": data.get("rec_texts", []),
+                "rec_scores": [float(s) for s in data.get("rec_scores", [])],
+                "rec_boxes": data.get("rec_boxes", []),
+                "rec_polys": data.get("rec_polys", []),
+            })
+
+        return {"errorCode": 0, "result": {"ocrResults": pages}}
+
+    except Exception as e:
+        logger.exception("OCR failed")
+        return JSONResponse(
+            status_code=500,
+            content={"errorCode": 2, "message": str(e)},
+        )