v0.2.1 (March 26, 2024)
Code license changed to MIT License
.
Rotate90
: New transform to rotate image by 90 degreesTrainer
: Option for validating on loss value.
infer.py
: New optional cmd argument to rotate image before inference.
- Change UAV dataset hosting (now in ULiège Open Data Repository)
- It is now possible to resume a training session when a validation frequency > 1 is used.
- Solving the problem of continuously increasing training time over epochs.
Alexandre-Delplanque (19):
- 0fb5a68 - Merge branch 'feature' into main
- 506e1e1 - chore: update CHANGELOG.md
- c101dca - fix: update code version
- 031cc1a - chore: minor change
- 4a2c68a - fix: update code version
- b424c5b - Merge pull request #3 from Alexandre-Delplanque/new-license
- ce16958 - chore: update CHANGELOG.md
- d2b9078 - chore: final licence changes
- f063a82 - chore: switch to MIT License
- d6b3ffb - fix: change how images are rotated
- c67404b - feat: add Rotate90 transform
- 39e317a - fix: increasing training time over epochs
- 4baeab1 - fix: resume training when using valid_freq
- d86ec37 - fix: new link for UAV dataset #2
- 53dd60a - fix: weights to device when not None (_ssim_loss)
- b082fc4 - feat: rotation option for infer.py tool
- c0bfc31 - fix: only CSV's images when -all arg is False
- addbc9b - Merge branch 'feature' of https://github.com/Alexandre-Delplanque/Herd-Net into feature
- d480319 - feat: option for evaluation with loss in Trainer
v0.2.0 (March 29, 2023)
CustomLogger
: Argument to disable logging to CSV files (use to much memory).Trainer
: Arguments to set the validation frequency during training (valid_freq
) and to choose whether to save logs to CSV files (csv_logger
).HerdNet
: New method for reshaping classes (reshape_classes()
), useful for loading pre-trained parameters.FolderDataset
: New flag (from_folder
) inself.data
attribute.
sampler.py
: New python module for hosting samplers for data loading.
train.py
: New keys:wandb_run
,model.freeze
(HerdNet only),datasets.class_def
,datasets.sampler
andtraining_settings.valid_freq
. Now use the class definition (i.e.,datasets.class_def
) to make sure the labels match the species names.test.py
: New keys:wandb_run
anddataset.class_def
. Now use the class definition (i.e.,dataset.class_def
) 1) to make sure the labels match the species names, and 2) for plotting precision-recall curves, saving the detections, the metrics and the confusion matrix.
Alexandre-Delplanque (17):
- ff94a5e - chore: update README.md
- 03ccd66 - version: update version number and modified date
- 4791624 - chore: add CHANGELOG.md
- eb159c7 - docs: create doc folder and update configs md
- f18f9f9 - feat: add new keys to configs
- 7f91167 - feat: add sampler option in train.py tool
- bea0fc4 - feat: samplers.py - hosts samplers for dataloading
- d883b49 - feat: save classes, mean, std in PTH files
- 8189dc7 - feat: add 'from_folder' flag in FolderDataset data
- 907a221 - feat: +class def., +labeled results, +conf. matrix
- 7b4bc74 - feat: +class def., +validation freq., -cross-val
- 884673d - fix: add head_conv attribute to HerdNet module
- 7b88af8 - feat: valid_freq and csv_logger args (Trainer)
- d88ff21 - feat: add option to disable csv logs
- 7071569 - fix: PointsToMask one-hot encoding option
- 782d877 - fix: FocalLoss, avoid NaN when output is 0 or 1
- deec190 - add article reference
v0.1.0 (January 23, 2023)
Initial version of the code, used for producing the results of the reference paper "From Crowd to Herd Counting: How to Precisely Detect and Count African Mammals using Aerial Imagery and Deep Learning?".
Alexandre-Delplanque (11):
- f6586a1 - Add LICENSE
- 9164bd9 - Create LICENSE.md
- e5d5e5c - Merge branch 'main' of https://github.com/Alexandre-Delplanque/Herd-Net
- 303ca64 - Upgrade infer tool and use tqdm for progress bars
- ca8e03d - Update Colab notebook link
- 4179b60 - Add infer.py tool and demo notebook
- 48e2072 - Update README.md
- 17f8efc - Update environment.yml
- 77c3bbe - Update README.md
- 3423d85 - initial code commit
- d176d9f - Initial commit