feat(bridge): classification 自適應解析 + 推論期動態切換

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新增 classification 推論支援，核心是「不預設模型長相」：

- output shape 自適應：支援 (1,C)/(C,)/(1,C,1,1)/(C,1,1)/(1,1,1,C)
  及任何 squeeze 後為一維的張量；類別數從 shape 動態取得，
  移除原本寫死的 num_classes=1000
- 無法解析時明確報錯（附實際 shape），不靜默回空結果
- logits vs 已 softmax 自動偵測：sum≈1.0 且全非負才跳過 softmax
  （容差 1e-4，實測 float32 softmax 偏差最大僅 ~4e-7）
- label 為純顯示層：有注入用 label、沒有則輸出原始 enum class_N
- input size 三層來源：SDK > 宣告值 > 檔名猜測，log 標示來源
- 新增 handle_set_inference_options：不重載模型即可改解析方式與 label

修正：
- _detect_model_type 改為外部指定優先，解決未知檔名被誤判成
  tiny_yolov3 而回傳空結果的根因
- handle_disconnect/reset 未清 label 狀態，導致換模型後沿用舊 label 表
- load_model 失敗路徑會污染全域 metadata，改為 defer-until-success
- taskType 值域統一為 object_detection（原本回 detection）
- 檔名解析原本只取 width 丟棄 height，非正方形模型會被壓成正方形

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

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jim800121chen 2026-07-22 19:26:51 +08:00

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local-tool/server/scripts/kneron_bridge.py

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local-tool/server/scripts/test_kneron_bridge_classification.py Normal file

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