use crate::types::Session;
use ddddocr_core::DetOutput;
use ddddocr_core::error::{Result, TensorError};
use ddddocr_core::traits::{DetEngine, InferenceEngine};
use ndarray::Ix3;
use ort::inputs;
use ort::value::TensorRef;
// use tract_onnx::prelude::{tvec, IntoTensor, Tensor};

#[derive(Debug)]
pub struct DetRuntime {
    pub session: Session,
}

impl DetRuntime {
    pub fn new(session: Session) -> Self {
        Self { session }
    }
}

impl InferenceEngine for DetRuntime {
    type Output = DetOutput; // 明确绑定 OCR 小枚举
    fn inference(&self, input_array: ndarray::Array4<f32>) -> Result<Self::Output, TensorError> {
        // tract 的 run 会返回一个 Vec<TValue>，我们通常只需要第一个输出
        // let result = self.ocr.run(tvec!(tensor.into()))?;
        let mut session_guard = self
            .session
            .lock()
            .map_err(|_| TensorError::Engine("获取 Session 锁失败 (Poisoned)".to_string()))?;

        let result = session_guard
            .run(inputs![TensorRef::from_array_view(&input_array).map_err(
                |e| TensorError::Engine(format!("构建输入失败: {e}"))
            )?])
            .map_err(|e| TensorError::Engine(format!("执行模型推理失败: {e}")))?;
        // .context("执行模型推理失败")?;
        println!("模型输出原始数据: {:?}", result);

        // Ok(result.swap_remove(0).into_tensor())
        let raw_value = &result[0];

        // raw_tensor.into_plain_array()?
        let (shape_ref, slice) = raw_value.try_extract_tensor::<f32>().map_err(|_| {
            TensorError::Engine("Tract 实体张量无法转换为 ndarray::ArrayD".to_string())
        })?;
        // 提前利用克隆(Clone)备份好当前未转维度前的真实 shape (Vec<usize>)
        let shape_vec: Vec<usize> = shape_ref.to_vec().iter().map(|v| *v as usize).collect();
        let shape_vec_slice = shape_vec.as_slice();

        let view = ndarray::ArrayViewD::from_shape(shape_vec_slice, slice)
            .map_err(|_| TensorError::Engine("构建 ndarray ArrayViewD 失败".to_string()))?;

        let array3 = view.to_owned().into_dimensionality::<Ix3>().map_err(|_| {
            TensorError::DimensionMismatch {
                expected: "3D 检测矩阵 [Batch, Box_Count, Box_Attributes]".to_string(),
                actual: shape_vec, // 优雅降维失败时动态捕获
            }
        })?;
        Ok(DetOutput::Detection(array3))

        // 在引擎内部消化掉 DatumType 强耦合
    }
}

impl DetEngine for DetRuntime {}