3588上python=3.9.6版本测试完成
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wood_detect/1.jpg
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wood_detect/1.jpg
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Before Width: | Height: | Size: 333 KiB After Width: | Height: | Size: 333 KiB |
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wood_detect/wood_detect.py
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wood_detect/wood_detect.py
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wood_detect/wood_detect.rknn
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wood_detect/wood_detect.rknn
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wood_exist/1.png
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wood_exist/1.png
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Before Width: | Height: | Size: 394 KiB After Width: | Height: | Size: 394 KiB |
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wood_exist/wood_exist.py
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wood_exist/wood_exist.py
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@ -13,7 +13,7 @@ ROI RKNN 图像分类模块
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"""
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"""
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import os
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import os
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from typing import Dict
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from typing import Dict,Union
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import cv2
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import cv2
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import numpy as np
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import numpy as np
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@ -37,7 +37,7 @@ CLASS_NAMES: Dict[int, str] = {
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# 全局 RKNN 实例(单例)
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# 全局 RKNN 实例(单例)
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# =====================================================
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# =====================================================
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_global_rknn: RKNNLite | None = None
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_global_rknn: Union[RKNNLite, None] = None
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def _init_rknn_model(model_path: str) -> RKNNLite:
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def _init_rknn_model(model_path: str) -> RKNNLite:
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wood_exist/wood_exist_cls.rknn
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wood_exist/wood_exist_cls.rknn
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wood_ng/1.png
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wood_ng/1.png
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Before Width: | Height: | Size: 394 KiB After Width: | Height: | Size: 394 KiB |
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wood_ng/wood_ng.py
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wood_ng/wood_ng.py
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@ -13,7 +13,7 @@ ROI RKNN 图像分类模块
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"""
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"""
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import os
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import os
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from typing import Dict
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from typing import Dict,Union
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import cv2
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import cv2
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import numpy as np
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import numpy as np
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@ -37,7 +37,7 @@ CLASS_NAMES: Dict[int, str] = {
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# 全局 RKNN 实例(单例)
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# 全局 RKNN 实例(单例)
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# =====================================================
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# =====================================================
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_global_rknn: RKNNLite | None = None
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_global_rknn: Union[RKNNLite, None] = None
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def _init_rknn_model(model_path: str) -> RKNNLite:
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def _init_rknn_model(model_path: str) -> RKNNLite:
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wood_ng/wood_ng_cls.rknn
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wood_ng/wood_ng_cls.rknn
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