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Releases: Deci-AI/super-gradients

3.2.0

15 Aug 12:52
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What's Changed

New Contributors

Full Changelog: 3.1.3...3.2.0

3.1.3

19 Jul 10:09
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New features
predict() support for pose estimation (PR: #1142) and classification (PR: #1220)
The possibility to log scalar values with explicit time units associated with it: log losses per step, use TimerCallback that measures and log batch time (PR: #1181)
Support torch compile (PR: #1172)
Class agnostic NMS (PR: #1232)
Allow to compute & log per-class mAP scores (PR: #1238)
Small features
Add batch_size option to predict (PR: #1273)
Allows to pass user-defined target of IoU thresholds without asking user to edit IoUThresholds enum in SG codebase (PR: #1223)
Add DetectionVerticalFlip for bounding box detection augmentation (PR: #1237)
Support the option for multiple ignored indices for segmentation metrics (PR: #1177)
Simpify torch schedulers integration (PR: #1230)
support single output in YoloX NMS (PR: #813)
Compute the best threshold for each class in an efficient manner without added loops (PR: #973)
Bug fix
Hotfix/alg 1470 drop boxes padding by (PR: #1107)
Fix evaluate from recipe by (PR: #1170)
fixed bug of whitespace by (PR: #1173)
Fix collections.Iterable -> typing.Iterable to fix crash in python 3.10 by @BloodAxe in #1178
Fix missing encoding (PR: #1185)
default quantization params set in qat from config (PR: #1192)
Fix mkdirs in checkpoint (PR: #1198)
Fix DEKR’s replace_head & improve repr for keypoints transforms (PR: #1227)
Getting rid of “module.” heritage (PR: #1184)
Fix LayerNorm have a bias parameter attribute but is not instance of torch primitive modules (PR: #1229)
moved exceptions from training (PR: #1260)
Added explicit casting of input in predict pipeline. (PR: #1281)
kd ema model unrwap model fix (PR: #1283)
New Contributors
@allankouidri made their first contribution in #1185
@djm93dev made their first contribution in #1199
@danielafrimi made their first contribution in #1220
@RanZilberstein made their first contribution in #1228
@itaylevy-deci made their first contribution in #973
@LukeAI made their first contribution in #1237
@jorgectf made their first contribution in #1240
@jacobmarks made their first contribution in #1278

3.1.2

07 Jun 12:13
83ce129
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What's Changed

New Contributors

Full Changelog: 3.1.1...3.1.2

3.1.1

03 May 19:59
1c67ce3
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This GitHub Release was done automatically by CircleCI

3.1.0: removed dependencies between sanity tests and updated yaml with varia…

02 May 15:50
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This GitHub Release was done automatically by CircleCI

3.0.9

19 Apr 14:08
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Release notes 3.0.9
Features

  • Object Detection (Yolox, PPyoloE) predict function on images, videos, GIF, and folders paths. The predict function works out of the box, no need to define pre and post-processing. Both pre and post-processing are taken from the training. Examples here. PR: #815, #804, #807, #829, #845

  • Support yolov5 format detection dataset by for YoloX, PPyoloE #847

  • Base recipes for PPYoloE and Yolox of RF100 dataset.

  • DetectionOutputAdapter tutorial. The DetectionOutputAdapter is a class that converts the output of a detection model into a user-appropriate format.

  • Segformer model and recipe

  • Predict function on images and videos - taking the pre+post processing from the training recipe.

  • QAT&PTQ notebooks

  • Added student_adapter feature to KDModule, which lets the user pass a manipulated version of the input to the student model. PR: #820

  • Introduce min_samples param to dataloader_params, which repeats the dataset in case its size is smaller than the value of this parameter. PR: #838

Bug fixes:

3.0.8

02 Apr 07:52
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Bug fixes:
Fix the compatibility of ONNX conversion with torch 1.11+
Fix the docker publication
Fix Pre-Prediciton callback override bug
Fix dataloader multiprocessing (for Mac OS and Windows)
Fix strict_load not being passed in evaluate_from_recipe
Resolve many potential circular imports
Correct albumentations import log
Fix incorrect tensor type & device when entire batch has no targets
Fix documentation format in many files

Features:
New documentation for many features (EMA, AMP, QAT, Knowledge-Distillation, Dataloaders, Optimizer, Schedulers…)
Added Lion optimizer
Added registration for SG Logger (to allow custom-defined loggers to be used from YAML)
DDRNet 39 pre-trained segmentation model
Mapillary dataset
RoboFlow100 benchmark and all 100 datasets
QATTrainer for training with QAT
QAT from recipe script
PP-YoloE pre-trained models
Pose Estimation models loss functions
Added Auxiliary heads to Unet
Channel wise distillation
ONNX Simplifier on ONNX conversion
Unet and Loss function for binary segmentation
New Transforms: DetectionPadToSize, DetectionImagePermute
Allow activation factory type to take resolved type as inp
New strict_load mode: key_matching.

3.0.7

01 Feb 23:08
646c2fa
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Full Changelog: 3.0.6...3.0.7

3.0.6

11 Jan 11:20
b54a9ad
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What's Changed

Bugfixes:

Features:

New Contributors

Full Changelog: 3.0.5...3.0.6

3.0.5

28 Dec 17:14
f460027
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What's Changed

  • Added warning for drop_last when train_loader is not divisible by batch_size by @shaydeci in #586
  • fix compute_detection_metrics_per_cls return value when no detection … by @ofrimasad in #583
  • Quantization infra mods for different calibrators and learnable amax by @spsancti in #537
  • PLFM-3331 Register experiments with model name by @roikoren755 in #585
  • fix ignore index for DiceCEEdgeLoss by @lkdci in #588

Full Changelog: 3.0.4...3.0.5