ultralytics 8.0.129
add YOLOv8 Tencent NCNN export (#3529)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@ -79,7 +79,8 @@ class AutoBackend(nn.Module):
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super().__init__()
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w = str(weights[0] if isinstance(weights, list) else weights)
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nn_module = isinstance(weights, torch.nn.Module)
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pt, jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, paddle, triton = self._model_type(w)
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pt, jit, onnx, xml, engine, coreml, saved_model, pb, tflite, edgetpu, tfjs, paddle, ncnn, triton = \
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self._model_type(w)
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fp16 &= pt or jit or onnx or engine or nn_module or triton # FP16
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nhwc = coreml or saved_model or pb or tflite or edgetpu # BHWC formats (vs torch BCWH)
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stride = 32 # default stride
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@ -237,7 +238,7 @@ class AutoBackend(nn.Module):
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meta_file = model.namelist()[0]
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metadata = ast.literal_eval(model.read(meta_file).decode('utf-8'))
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elif tfjs: # TF.js
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raise NotImplementedError('YOLOv8 TF.js inference is not supported')
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raise NotImplementedError('YOLOv8 TF.js inference is not currently supported.')
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elif paddle: # PaddlePaddle
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LOGGER.info(f'Loading {w} for PaddlePaddle inference...')
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check_requirements('paddlepaddle-gpu' if cuda else 'paddlepaddle')
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@ -252,6 +253,8 @@ class AutoBackend(nn.Module):
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input_handle = predictor.get_input_handle(predictor.get_input_names()[0])
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output_names = predictor.get_output_names()
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metadata = w.parents[1] / 'metadata.yaml'
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elif ncnn: # PaddlePaddle
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raise NotImplementedError('YOLOv8 NCNN inference is not currently supported.')
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elif triton: # NVIDIA Triton Inference Server
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LOGGER.info('Triton Inference Server not supported...')
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'''
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