app.py

import gradio as gr
import easyocr
import numpy as np
from PIL import Image
import torch
import spaces

load_dotenv()  # load .env file

HF_TOKEN = os.getenv("ocr_sec")
client = Client("theoracle/easyocr-api", hf_token=HF_TOKEN)

# Create dummy tensor to confirm GPU availability
zero = torch.Tensor([0]).cuda()
print("Torch is using:", zero.device)  # Should be 'cuda:0'

# Declare reader outside the function (only once)
reader = easyocr.Reader(['en'], gpu=True)

@spaces.GPU  # Ensures this function runs on GPU
def extract_text(image):
    result = reader.readtext(np.array(image), detail=0)
    text = "\n".join(result)
    print("OCR complete. Text:", text)
    return text

iface = gr.Interface(
    fn=extract_text,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="GPU OCR with EasyOCR",
    description="Upload an image. OCR runs on GPU using EasyOCR + Hugging Face Spaces."
)

iface.launch()