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https://github.com/modelscope/modelscope.git
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remove error log
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/13891446
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@@ -65,6 +65,7 @@ class MTTR(nn.Module):
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# keep only the valid frames (frames which are annotated):
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# (for example, in a2d-sentences only the center frame in each window is annotated).
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for layer_out in backbone_out:
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valid_indices = valid_indices.to(layer_out.tensors.device)
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layer_out.tensors = layer_out.tensors.index_select(
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0, valid_indices)
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layer_out.mask = layer_out.mask.index_select(0, valid_indices)
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@@ -31,7 +31,7 @@ class FaceEmotionPipeline(Pipeline):
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logger.info('load model done')
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def preprocess(self, input: Input) -> Dict[str, Any]:
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img = LoadImage.convert_to_ndarray(input['img_path'])
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img = LoadImage.convert_to_ndarray(input)
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return img
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def forward(self, input: Dict[str, Any]) -> Dict[str, Any]:
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@@ -39,7 +39,6 @@ class NanoDettForFaceHumanHandDetectionPipeline(Pipeline):
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cls_list, bbox_list, score_list = det_infer.inference(
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self.model, self.device, input)
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logger.info(cls_list, bbox_list, score_list)
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return {
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OutputKeys.LABELS: cls_list,
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OutputKeys.BOXES: bbox_list,
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@@ -30,7 +30,7 @@ class HandStaticPipeline(Pipeline):
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logger.info('load model done')
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def preprocess(self, input: Input) -> Dict[str, Any]:
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img = LoadImage.convert_to_ndarray(input['img_path'])
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img = LoadImage.convert_to_ndarray(input)
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return img
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def forward(self, input: Dict[str, Any]) -> Dict[str, Any]:
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