.. _release_note_1.5:

=======================
Palette SDK Version 1.5 
=======================

The SDK version 1.5.0 brings a wide range of enhancements to quantization, pipeline efficiency, GStreamer integration, and developer experience. This release introduces new post-training quantization features, automatic mixed-precision support, and updates to our machine learning acceleration framework. Additionally, pipeline improvements have been made for better performance, flexibility, and out-of-the-box usability.  

New Features & Enhancements
--------------------------- 
.. list-table::
   :widths: 20 10 20 30
   :header-rows: 1

   * - **Category**
     - **Availability**
     - **Feature Name**
     - **Description**
   * - Quantization
     - GA
     - Post-Training Quantization (PTQ) - Channel Equalization
     - Improves quantization accuracy by balancing per-channel distributions. Validated on Densenet-121.
   * - Quantization
     - Alpha
     - Automatic Mixed-Precision Quantization
     - Optimizes performance using INT8 and FP16. Uses binary search for best trade-off. Currently CPU-only, GPU support planned.
   * - Quantization
     - Beta
     - Quantization-Aware Training (QAT)
     - Provides high accuracy for Yolo models (Yolo v8). Requires additional tuning for transformers.
   * - MLA Acceleration
     - GA
     - Extended MLA Operator Support
     - Added support for Argmax and Resize. Bilinear interpolation supports up to 63x scaling. Enhanced non-vectorized Argmax.
   * - MLA Acceleration
     - GA
     - MLA Runtime Resiliency & Reliability
     - Improved execution consistency and error handling.
   * - GStreamer
     - GA
     - PyGst Plugin for GStreamer
     - New plugin for integrating Python post-processing in GStreamer. Enables seamless Python-to-GStreamer transition. YoloV8 pipeline included.
   * - GStreamer
     - GA
     - Out-of-the-Box Experience Enhancements
     - Redesigned services using ports 8001-8004 for compatibility. PCIe-based pipelines moved to `gst-App-Code`. New GStreamer workflow tools.
   * - Pipeline Optimization
     - GA
     - Improved PeopleTracker Pipeline Efficiency
     - Integrated Centernet + ReID + Tracker updates for improved tracking.
   * - Pipeline Optimization
     - Beta
     - Pipeline Accuracy Measurement Framework
     - Supports PeopleTracker, YoloV8n, Baxter pipeline, YoloV7, DETR, and EffDet. Pending support for Yolov5, PeopleDetector, and OpenPose.
   * - Pipeline Optimization
     - GA
     - Ethernet and PCIe Enhancements
     - Simplified Ethernet pipeline execution via Dispatcher + Config Manager. ``gstBufferPool`` integration for efficiency. Ethernet over PCIe fully supported.
   * - SDK & CLI
     - GA
     - SDK & CLI Enhancements
     - Install script now includes dependency checks. Improved GStreamer plugin documentation. Standardized naming conventions. New runtime profiler and tracer.
   * - SoC Software
     - GA
     - SoC Software Updates
     - Added H.265 encoding support for TVS. Enhanced file transfer over PCIe. Common C++ APIs for EV74 and MLA. Memory leak detection via Valgrind.
   * - Deployment
     - GA
     - MPK Commands & Deployment Enhancements
     - MPK commands now support Ethernet & PCIe. New CLI tools for app deployment.Virtual Ethernet support in PCIe mode.


Performance Validations
----------------------- 
.. list-table::
   :widths: 10 20 10 30
   :header-rows: 1

   * - **Type**
     - **Model Name**
     - **FPS**
     - **Explanation**
   * - PCIe
     - MaskRCNN
     - 20
     - Achieved 20 FPS performance under PCIe deployment.
   * - PCIe
     - OpenPose
     - 45
     - Performance measured at 45 FPS on PCIe.
   * - PCIe
     - YOLOv5
     - 20
     - Running at 20 FPS over PCIe.
   * - PCIe
     - YOLOv7
     - 20
     - Running at 20 FPS under PCIe deployment.
   * - Standalone
     - YoloV8
     - 80 (20*4)
     - Runs at 20 FPS per camera, tested with 4 cameras.
   * - Standalone
     - DETR
     - 30
     - Achieved 30 FPS over Ethernet.
   * - Standalone
     - OpenPose
     - 50
     - Optimized to run at 50 FPS over Ethernet.
   * - Standalone
     - YOLOv5
     - 20
     - Achieved 20 FPS performance over Ethernet.
   * - Standalone
     - YOLOv7
     - 20
     - Achieved 20 FPS over Ethernet.
   * - Standalone
     - YOLOv7 (4-Camera)
     - 12 (per cam)
     - Each of the 4 cameras operates at 12 FPS.
   * - Standalone
     - PeopleTracker
     - 30
     - Achieved 30 FPS under Ethernet.
   * - Standalone
     - EfficientDet
     - 20
     - Running at 20 FPS over Ethernet.
   * - Standalone
     - PeopleDetector (4-Camera)
     - 20 (per cam)
     - Each camera runs at 20 FPS under Ethernet.
      


Bug Fixes
----------

  - Improved system stability for long-duration ML workloads.  
  - Optimized quantization evaluation for faster execution.  

 
Known Issues
------------

  - Some pipeline accuracy measurement tools are still in progress.
  - Certain Ethernet pipelines experience occasional memory issues.  
  - YoloV8_4cams pipeline exhibits instability during long-term testing.