… loading

- Updated pipeline.py to load hyperparameters from STAC Item JSON, streamlining model configuration.
- Modified training_pipeline to accept a path to the STAC Item, allowing for flexible hyperparameter management.
- Revised README.md to reflect changes in hyperparameter handling and usage of STAC Item.
- Enhanced stac-item.json with additional metadata and structure for better integration.
- Removed outdated CODE_EXPLAINED.md and README.md from tests directory to clean up documentation.

… and compatibility

- Refactored Dockerfile to streamline the build process, using a base image from GHCR for both CPU and GPU.
- Enhanced pipeline.py to support new model weight loading mechanisms and improved error handling for model paths.
- Updated README.md to reflect changes in framework version and model usage, including new data directory structure.
- Revised stac-item.json to include updated model weights source and additional metadata for better integration.
- Improved smoke tests to validate the new pipeline functionality and ensure compatibility with the latest TensorFlow/Keras versions.
- Added per-file ignores in Ruff for specific linting rules in pipeline.py.

…improvements

- Added functions to resolve local and remote input directories and files, improving flexibility in handling model paths.
- Implemented a zip extraction utility for loading models from compressed files.
- Updated `resolve_model_href` to support both local and remote SavedModel directories, enhancing compatibility with various model formats.
- Modified smoke tests to validate the new `split_dataset` functionality alongside training wrappers, ensuring robust model training and validation.

… and dependencies

- Refactored Dockerfile to separate build, runtime, test, and inference stages for better clarity and efficiency.
- Updated `pyproject.toml` to remove unnecessary lint ignores.
- Enhanced `pipeline.py` with improved model resolution and added support for lazy imports.
- Revised README.md for clarity on architecture and usage.
- Added test fixtures for a toy dataset and implemented step tests for the RAMP pipeline.
- Updated STAC item schema to version 1.1.0 and included additional metadata properties.

- Simplified the `resolve_model_href` function to focus on .onnx and .zip formats.
- Improved error handling for unsupported model formats and missing files.
- Updated ZIP extraction logic to ensure proper directory creation and cache management.
- Removed deprecated code and comments for better readability.

…ipeline.py

- Consolidated multi-line string definitions into single lines for consistency.
- Removed unnecessary blank lines to enhance code clarity.
- Streamlined parameter retrieval in several functions for better readability.

…TAC item references

- Removed the default baseline URL in `pipeline.py` and raised a ValueError if weights are not provided.
- Updated `pretrained_source` and `checkpoint` URLs in `stac-item.json` to point to the new Hugging Face location.
- Adjusted the `create_toy_data` function to ensure it uses a GeoJSON file for labels, aligning with the expectations in `pipeline.py`.

…peline.py

- Updated type hints for several functions to use Optional and Union for better clarity.
- Introduced a new function `_normalize_to_savedmodel_dir` to streamline model path normalization.
- Improved error handling and readability in model resolution and checkpoint restoration logic.
- Consolidated ZIP handling and model loading processes for better maintainability.

… unused cache function; update hyperparameters specification in stac-item.json

…export steps

…raining functions

…alization and update assertions