Lilly Thomas
Lilly Thomas
Hi ardiya! Thanks for putting together this repository. Could you tell me what would need to be done to run this on non-MNIST greyscale images? Thanks so much in advance!...
Hi there, Thanks for sharing this repo. I am wondering if you could provide some insight into what the `use_angle_condition` parameter in libs/fast_rcnn/build_fast_rcnn1.py is controlling, and why it is set...
Hi there, Thank you for providing this repo. When I execute the inference script, I end up with the error `ValueError: Dimension 0 in both shapes must be equal, but...
Hi Youngwook, Thanks for offering this implementation. I'm curious, how would I go about using my own images with this network? For example, I anticipate using 256x256 RGB images. Thanks...
The purpose of this PR is to create a notebook demonstrating how to run inference on new NAIP scenes. It may also serve the purpose of demonstrating sim search with...
Relates to https://github.com/orgs/Clay-foundation/discussions/291
Our 3 data products scoped for v0 training (https://github.com/Clay-foundation/model/issues/19, https://github.com/Clay-foundation/model/issues/18, https://github.com/Clay-foundation/model/issues/20) have a median spatial resolution of 20 meters. We'll assume a single resolution model for v0, using 20m resolution...
(Currently WIP) notebook for unet w customized c2smsfloods benchmark dataset
- Modifies the `datacube.py` script to generate minicubes with partial inputs including SAR and DEM. Also configured to prodice ("most cloud-free") bi-monthly cubes in a start/end time range. - Now,...
We've completed our first benchmarking exercise for Clay v0 using the Microsoft Flood detection dataset (see https://github.com/Clay-foundation/model/issues/83 for details). The exercise entailed a comparison of a model "trained from scratch"...