import torch
import onnx
import onnxruntime as rt
from torchvision import transforms as T
from PIL import Image
from tokenizer_base import Tokenizer
import gradio as gr

model_file = "captcha.onnx"
img_size = (32, 128)
charset = r"0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~"

tokenizer_base = Tokenizer(charset)

def get_transform(img_size):
    transforms = [
        T.Resize(img_size, T.InterpolationMode.BICUBIC),
        T.ToTensor(),
        T.Normalize(0.5, 0.5)
    ]
    return T.Compose(transforms)

def to_numpy(tensor):
    return tensor.detach().cpu().numpy() if tensor.requires_grad else tensor.cpu().numpy()

def initialize_model(model_file):
    transform = get_transform(img_size)
    onnx_model = onnx.load(model_file)
    onnx.checker.check_model(onnx_model)
    ort_session = rt.InferenceSession(model_file)
    return transform, ort_session

# Core OCR function
def get_text(img_org):
    x = transform(img_org.convert('RGB')).unsqueeze(0)
    ort_inputs = {ort_session.get_inputs()[0].name: to_numpy(x)}
    logits = ort_session.run(None, ort_inputs)[0]
    probs = torch.tensor(logits).softmax(-1)
    preds, _ = tokenizer_base.decode(probs)
    return preds[0]

# Load model
transform, ort_session = initialize_model(model_file=model_file)

# ✅ Use gr.Interface (not Blocks) to support external API call
iface = gr.Interface(
    fn=get_text,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="Text Captcha Solver",
    description="API & UI nhận diện Captcha sử dụng mô hình ONNX"
)

iface.launch(enable_queue=True)  # <-- BẮT BUỘC để gọi được từ WinForms