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Truncate and Difficult tags effect on YOLO model performance?
2019 Community Moderator ElectionExtract features using pre-trained (Tensorflow) CNNTensorflow or Theano: Is there a special option for evaluation to use less memory?YOLO object detection model?YOLO performance on iOS devices?YOLO model: passing m exemples to the model?Tensorflow issue with placeholdersPython kernel dying while loading pre trained YOLO modelImplemetning yolo model with Tensor modelYOLO v2 (Dark-flow model) latency profilingLimitation of Keras/Tensorflow for solving Linear Regression taskstraining new model cfg and weight file in yolo
With regards to the pascal/voc xml annotation file that we feed into the YOLO algorithm to train it on images. It has 2 tags, namely truncated (if the object is being obscured, I believe), and difficult (if its hard to make out the object), which are each booleans. Does the algorithm take these into account during training, and does it help boost performance? Same thing goes for the pose tag.
As is, I've been leaving them all as 0, and the model performs okay, but could definitely be improved, and was wondering if this is an avenue I could explore.
I'm using Darkflow, the tensorflow implementation of yolo, if that makes any difference.
Thanks for the assist!
machine-learning computer-vision yolo darkflow
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
add a comment |
With regards to the pascal/voc xml annotation file that we feed into the YOLO algorithm to train it on images. It has 2 tags, namely truncated (if the object is being obscured, I believe), and difficult (if its hard to make out the object), which are each booleans. Does the algorithm take these into account during training, and does it help boost performance? Same thing goes for the pose tag.
As is, I've been leaving them all as 0, and the model performs okay, but could definitely be improved, and was wondering if this is an avenue I could explore.
I'm using Darkflow, the tensorflow implementation of yolo, if that makes any difference.
Thanks for the assist!
machine-learning computer-vision yolo darkflow
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
add a comment |
With regards to the pascal/voc xml annotation file that we feed into the YOLO algorithm to train it on images. It has 2 tags, namely truncated (if the object is being obscured, I believe), and difficult (if its hard to make out the object), which are each booleans. Does the algorithm take these into account during training, and does it help boost performance? Same thing goes for the pose tag.
As is, I've been leaving them all as 0, and the model performs okay, but could definitely be improved, and was wondering if this is an avenue I could explore.
I'm using Darkflow, the tensorflow implementation of yolo, if that makes any difference.
Thanks for the assist!
machine-learning computer-vision yolo darkflow
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
With regards to the pascal/voc xml annotation file that we feed into the YOLO algorithm to train it on images. It has 2 tags, namely truncated (if the object is being obscured, I believe), and difficult (if its hard to make out the object), which are each booleans. Does the algorithm take these into account during training, and does it help boost performance? Same thing goes for the pose tag.
As is, I've been leaving them all as 0, and the model performs okay, but could definitely be improved, and was wondering if this is an avenue I could explore.
I'm using Darkflow, the tensorflow implementation of yolo, if that makes any difference.
Thanks for the assist!
machine-learning computer-vision yolo darkflow
machine-learning computer-vision yolo darkflow
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
edited yesterday
Jean-Vicente De Carvalho
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
asked yesterday
Jean-Vicente De CarvalhoJean-Vicente De Carvalho
4117
4117
add a comment |
add a comment |
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