New answers tagged object-detection
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Object detection models usually generate multiple detections per object. Duplicates are removed in a post-processing step called Non-Maximum Suppression (NMS).
The Pytorch code that performs this post-processing is called here in the RegionProposalNetwork class. The filtering loop you've mentioned performs the NMS and applies the score_thresh threshold (...
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Heatmap in the sense of Corner net is the heatmap of the pooled corner values. As discussed in the paper, there is a corner pooling operation that gives you the vector values for a pixel point being a corner(it may or not). The output from the corner pooling is CxHxW. Then to generate a heat map you train the network similar to the Grad-CAM method. Training ...
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Generally, a model is considered to be overfitted when there's a huge gap between training and test/validation performances.
So during the training, you monitor the loss on validation data, and training data, and stop training if validation loss stagnates/increases given the training loss keeps decreasing.
In your scenario, I'm not sure what the total loss ...
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As you said, a CNN would be able to detect objects in different positions if the dataset contains enough examples of such cases, though the network is able to generalize and should be able to detect objects in slightly changed positions and orientations.
The term "translation invariance" does not mean that translating an object in the image would ...
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Good question! Using Yolo to recognise characters would be a good experiment to try. It may be because of the density of characters on a page -- systems like Yolo are very good at detecting a small number e.g. 2,3 or 10, objects, but don't work so well when the number of objects is the hundreds as you might have with OCR. A better approach might be to try ...
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Yes, the functionality should is there. But, don't you think you are overdoing the scales. You have at least 18 scales mentioned here. Too much of anything is bad. There is a reason it likes things divisible by 32 because at that increase in size something more meaningful will show up in the image. Spamming sizes like this won't help you at all, it would ...
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