ATSS | Bridging the Gap Between | Computer Vision library
kandi X-RAY | ATSS Summary
kandi X-RAY | ATSS Summary
In this work, we first point out that the essential difference between anchor-based and anchor-free detection is actually how to define positive and negative training samples. Then we propose an Adaptive Training Sample Selection (ATSS) to automatically select positive and negative samples according to statistical characteristics of object, which significantly improves the performance of anchor-based and anchor-free detectors and bridges the gap between them. Finally, we demonstrate that tiling multiple anchors per location on the image to detect objects is a thankless operation under current situations. Extensive experiments conducted on MS COCO support our aforementioned analysis and conclusions. With the newly introduced ATSS, we improve state-of-the-art detectors by a large margin to 50.7% AP without introducing any overhead. For more details, please refer to our paper.
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Top functions reviewed by kandi - BETA
- Convert CloudScapes instance
- Convert a polygon to box coordinates
- Convert xy coordinates to xy coordinates
- Make data loader
- Build a dataset from a list of datasets
- Builds the transformer layers
- Make a batch data sampler
- Forward a single feature map
- Clip the bounding box
- Convolutional transform
- Perform an inference on a dataset
- Train detection model
- Generate a dictionary of instance objects from each image
- Forward convolution
- Select boxes over all the boxes
- Compute the classification loss
- Resize the bounding box
- Transpose the image
- Retrieve all C ++ extensions
- Add the last convolution layer
- Compute the predictions for the given boxes
- Subsample the given proposals
- Make a 2x3 convolutional convolutional
- Forward feature extraction
- Compute the inner layer
- Compute the RPNR model
ATSS Key Features
ATSS Examples and Code Snippets
Community Discussions
Trending Discussions on ATSS
QUESTION
We are running our project in TFS using Git. Recently it started giving Error
TF30042: The database is full. Contact your Team Foundation Server administrator. Server: ATSS-P-AAI\SqlExpress01, Error: 1105, Message: 'Could not allocate space for object 'dbo.tbl_Content'.'PK_tbl_Content' in database 'Tfs_DefaultCollection' because the 'PRIMARY' filegroup is full. Create disk space by deleting unneeded files, dropping objects in the filegroup, adding additional files to the filegroup, or setting autogrowth on for existing files in the filegroup.
I have checked and found that the tbl_content itself has occupied around 9.5GB of space while the total DB size is 10GB. One of my teammate had mistakenly checked in a repository with huge binary files before this happened. He has deleted the repository but seems like the tbl_content is still having same space.
I have tried setting autogrowth as well, but nothing seems to be working. We are now not able to use it anymore.
Any solutions are suggested.
...ANSWER
Answered 2020-Apr-02 at 14:50This is because you're using SQL Express. SQL Express is limited to databases of up to 10 GB.
The easy answer here is that you should upgrade your SQL edition. It may be possible to remove data from the database, but doing so without explicit instructions from Microsoft is not recommended.
QUESTION
I am logging to logstash,in json format,
my logs have the following fields, each field is a string and the atts
field is a stringified json (note: atts
sub fields are different each time)
here is an example:
{"name":"bob","last":"builder", "atts":"{\"a\":111, \"b\":222}"}
I would like to parse it to something like this:
...ANSWER
Answered 2017-Apr-05 at 14:25There is a json
filter. Just pass it the field you want to parse and a target where you want it.
Something like:
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