Few-Shot Object Detection (FsDet) - Training tools for custom data
This is a fork of Few-shot Object Detection (FsDet) method, adding an easy to use tool for training on custom datasets
Apache License 2.0 (Apache-2.0)
This is a fork of Few-shot Object Detection (FsDet) method (see https://github.com/ucbdrive/few-shot-object-detection), adding an easy to use tool for training on custom dataset.
Technical CategoriesComputer vision
11.01.2023 - 12:27
We have extended the FsDet framework with a tool that dynamically generates datasets from annotation files and drives the training process.
The tool has the following features:
- Determine the base and novel classes from the provided annotations (for the novel classes only a subset may be used for training).
- Determine how many instances are available, and set up the k-shot n-way problem accordingly.
- Prepare model structures for novel only and combined base+novel finetuning by adjusting the layer sizes to match the number of classes in the different sets.
- If the number of samples strongly varies, set up multiple training problems to make best use of the data, and run multiple fine-tuning steps.
The tool currently supports annotations in COCO format. However, this does not mean that COCO is required as a base model, as long as the annotations are provided in this format.