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import warnings
warnings.filterwarnings("ignore", message=".*pin_memory.*")
import os
import io
import easyocr
import numpy as np
from fastapi import FastAPI, UploadFile, File
from fastapi.responses import JSONResponse
from PIL import Image
from pdf2image import convert_from_bytes
from concurrent.futures import ThreadPoolExecutor
# =========================
# EasyOCR config
# =========================
MODEL_DIR = "/app/.EasyOCR"
USER_NET_DIR = os.path.join(MODEL_DIR, "user_network")
os.makedirs(MODEL_DIR, exist_ok=True)
os.makedirs(USER_NET_DIR, exist_ok=True)
# ✅ preload reader
reader = easyocr.Reader(
['en', 'hi'],
model_storage_directory=MODEL_DIR,
user_network_directory=USER_NET_DIR,
download_enabled=False
)
# =========================
# FastAPI app
# =========================
app = FastAPI()
@app.get("/")
async def root():
return {"message": "OCR API is running on Hugging Face 🚀"}
def run_ocr_on_image(image: Image.Image) -> str:
"""Convert PIL → numpy, run OCR, return plain text"""
image_np = np.array(image)
results = reader.readtext(image_np)
# ✅ only text, join all detections
extracted_text = " ".join([str(text) for _, text, _ in results])
return extracted_text.strip()
@app.post("/ocr")
async def ocr(file: UploadFile = File(...)):
try:
contents = await file.read()
if file.filename.lower().endswith(".pdf"):
# ✅ Convert PDF → images
pages = convert_from_bytes(contents)
# ✅ Run OCR in parallel
text_results = []
with ThreadPoolExecutor() as executor:
page_texts = list(executor.map(run_ocr_on_image, pages))
for i, text in enumerate(page_texts, start=1):
text_results.append({
"page": i,
"text": text
})
return JSONResponse(content={"pdf_results": text_results})
else:
# ✅ Single image case
image = Image.open(io.BytesIO(contents))
text = run_ocr_on_image(image)
return JSONResponse(content={"text": text})
except Exception as e:
return JSONResponse(content={"error": str(e)}, status_code=500)
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