Release AI-ModelZoo-3.1.0:

- Support for STEdgeAI Core v2.1.0 (STM32Cube.AI v10.1.0).
- Application code for STM32N6 board is now directly available in the STM32 model zoo repository; eliminating the need for separate downloads.
- Support of On device evaluation and On device prediction on the STM32N6570-DK boards integrated in evaluation and prediction services.
- More models supported : Yolov11, LSTM model added in the Speech Enhancement, ST Yolo X variants.
- ClearML support.
- A few bug fixes and improvements like proper imports, OD metrics alignments.

Signed-off-by: khaoula boutiche <[email protected]>

Release AI-ModelZoo-3.0.0:

- Included additional models compatible with the STM32N6570-DK board.
- Expanded models in all use cases.
- Expanded use case support to include Instance Segmentation and Speech Enhancement.
- Added Pytorch support through the speech enhancement Use Case.
- Model Zoo hosted on Hugging Face

Signed-off-by: khaoula boutiche <[email protected]>

Release AI-ModelZoo-2.1.1:

- Fixed some bugs.
- Added more detailed information in README files.
- Updated development cloud benchmark notebook to include MPU boards.


Signed-off-by: khaoula boutiche <[email protected]>

Release AI-ModelZoo-2.1.0:

- Included additional models compatible with the STM32MP257F-DK2 board.
- Added support for per-tensor quantization.
- Integrated support for ONNX model quantization and evaluation.
- Included support for STEdgeAI (STM32Cube.AI v9.1.0 and subsequent versions).
- Expanded use case support to include Pose Estimation and Semantic Segmentation.
- Standardized logging information for a unified experience.


Signed-off-by: khaoula boutiche <[email protected]>

Release AI-ModelZoo-2.0.1:

   - Disclosed some ST object detection models: `st_yolo_lc_v1` and `ssd_mobilenet_v2_fpnlite` with various resolutions.
   - Disclosed some ST image classification models: `st_efficientnet_lc_v1`, `st_fdmobilenet_v1`, `st_resnet_8_hybrid_v1`, and `st_resnet_8_hybrid_v2` in different resolutions.
   - Fixed minor bugs and updated README documentation.


Signed-off-by: khaoula boutiche <[email protected]>

Release AI-ModelZoo-2.0.0

- Aligned and uniformed architecture for all the use case folders.
- Modular design to run different operation modes (training, benchmarking, evaluation, deployment, quantization) independently or with an option of chaining multiple modes in a single launch.
- A single entry point to the code, with a single configuration file to configure all the modes.
- Added Bring Your Own Model (BYOM) feature.
- More training capabilities proposed (transfer learning, fine tuning,
training from scratch).
- Addition of Object Detection models.

Update:

      - Identity provider migration update

Signed-off-by: khaoula boutiche <[email protected]>

Release AI-ModelZoo-1.3.0:

	- Updating LICENSE.md at root
	- Updating AED/ with the following:
		- Adding readme under getting_started
		- Adding STM32Cube.AI "version" param in .yaml files and columns in readmes
	- Updating common/ with the following:
		- Support for STM32Cube.AI version in common_benchmark.py functions
		- Adding input param for .conf file in stn32ai_deploy() function in common_deploy.py
		- Fix a bug in stm32ai_dc and updating readme
	- Updating hand_posture/ with the following:
		- Support L7 and L8 ToF sensors for hand posture recognition
		- Adding STM32Cube.AI "version" param in .yaml files and columns in readmes
		- Adding a publicly available dataset for training + LICENSE
	- Updating HAR/ with the following:
		- Provide the new getting started for HAR use case IOT U5
		- Update the tutorial readmes accordingly\
		- Updating models/ footprints on STM32Cube.AI version 8.1.0
		- Adding STM32Cube.AI "version" param in .yaml files and columns in readmes
	- Updating image_classification/ with the following:
		- Support for deployment using the hardware setup for NUCLEO-H743ZI2 board
		- Adding STM32Cube.AI "version" param in .yaml files and columns in readmes
		- Integrating 'quantization_dataset' param in .yaml files to quantize on specific subset
	- Updating object_detection/ with the following:
		- Have an Object Detection getting started enabled for SSD models
		- Adding deployment/ scripts for the getting started
		- Updating models/ footprints on STM32Cube.AI version 8.1.0
		- Adding STM32Cube.AI "version" param in .yaml files and columns in readmes
		- Integrating 'quantization_dataset' param in .yaml files to quantize on specific subset
	- Updating tutorials/ with the following:
		- Adding notebook that describe onnx quantization

Signed-off-by: yhaddou <[email protected]>

First release AI-ModelZoo-1.0.0

Signed-off-by: yhaddou <[email protected]>