Merge pull request #90 from hailo-ai/update-to-version-v2.11

update-to-version-2.11.0

README.rst

@@ -22,14 +22,14 @@ Hailo Model Zoo
    :height: 20
 
 
-.. |compiler| image:: https://img.shields.io/badge/Hailo%20Dataflow%20Compiler-3.26.0-brightgreen.svg
+.. |compiler| image:: https://img.shields.io/badge/Hailo%20Dataflow%20Compiler-3.27.0-brightgreen.svg
    :target: https://hailo.ai/company-overview/contact-us/
    :alt: Hailo Dataflow Compiler
    :width: 180
    :height: 20
 
 
-.. |runtime| image:: https://img.shields.io/badge/HailoRT%20(optional)-4.16.0-brightgreen.svg
+.. |runtime| image:: https://img.shields.io/badge/HailoRT%20(optional)-4.17.0-brightgreen.svg
    :target: https://hailo.ai/company-overview/contact-us/
    :alt: HailoRT
    :width: 170
@@ -57,13 +57,13 @@ The models are divided to:
 
 * Public models - which were trained on publicly available datasets.
 
-    * For Hailo-8 - `Classification <docs/public_models/HAILO8_Classification.rst>`_, `Object Detection <docs/public_models/HAILO8_Object_Detection.rst>`_, `Segmentation <docs/public_models/HAILO8_Semantic_Segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
+    * For Hailo-8 - `Classification <docs/public_models/HAILO8/HAILO8_classification.rst>`_, `Object Detection <docs/public_models/HAILO8/HAILO8_object_detection.rst>`_, `Segmentation <docs/public_models/HAILO8/HAILO8_semantic_segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
 
-    * For Hailo-8L - `Classification <docs/public_models/HAILO8L_Classification.rst>`_, `Object Detection <docs/public_models/HAILO8L_Object_Detection.rst>`_, `Segmentation <docs/public_models/HAILO8L_Semantic_Segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
+    * For Hailo-8L - `Classification <docs/public_models/HAILO8L/HAILO8l_classification.rst>`_, `Object Detection <docs/public_models/HAILO8L/HAILO8l_object_detection.rst>`_, `Segmentation <docs/public_models/HAILO8L/HAILO8l_semantic_segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
 
-    * For Hailo-15H - `Classification <docs/public_models/HAILO15H_Classification.rst>`_, `Object Detection <docs/public_models/HAILO15H_Object_Detection.rst>`_, `Segmentation <docs/public_models/HAILO15H_Semantic_Segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
+    * For Hailo-15H - `Classification <docs/public_models/HAILO15H/HAILO15H_classification.rst>`_, `Object Detection <docs/public_models/HAILO15H/HAILO15H_object_detection.rst>`_, `Segmentation <docs/public_models/HAILO15H/HAILO15H_semantic_segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
 
-    * For Hailo-15M - `Classification <docs/public_models/HAILO15M_Classification.rst>`_, `Object Detection <docs/public_models/HAILO15M_Object_Detection.rst>`_, `Segmentation <docs/public_models/HAILO15M_Semantic_Segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
+    * For Hailo-15M - `Classification <docs/public_models/HAILO15M/HAILO15M_classification.rst>`_, `Object Detection <docs/public_models/HAILO15M/HAILO15M_object_detection.rst>`_, `Segmentation <docs/public_models/HAILO15M/HAILO15M_semantic_segmentation.rst>`_, `other tasks <docs/PUBLIC_MODELS.rst>`_
 
 
 

docs/CHANGELOG.rst

@@ -1,6 +1,34 @@
 Changelog
 =========
 
+**v2.11**
+
+* Update to use Dataflow Compiler v3.27.0 (`developer-zone <https://hailo.ai/developer-zone/>`_)
+* Update to use HailoRT 4.17.0 (`developer-zone <https://hailo.ai/developer-zone/>`_)
+
+* New Models:
+
+  * FastSAM-s - Zero-shot Instance Segmentation
+  * Yolov9c - Latest Object Detection model of the YOLO family
+
+* Using HailoRT-pp for postprocessing of the following variants:
+
+  * nanodet
+
+  Postprocessing JSON configurations are now part of the cfg directory.
+
+* Introduced new flags for hailomz CLI:
+
+  * ``--start-node-names`` and ``--end-node-names`` for customizing parsing behavior.
+  * ``--classes`` for adjusting the number of classes in post-processing configuration.
+
+  The ``--performance`` flag, previously utilized for compiling models with their enhanced model script if available, now offers an additional functionality.
+  In instances where a model lacks an optimized model script, this flag triggers the compiler's Performance Mode to achieve the best performance
+
+  These flags simplify the process of compiling models generated from our retrain dockers.
+
+* Bug fixes
+
 **v2.10**
 
 * Update to use Dataflow Compiler v3.26.0 (`developer-zone <https://hailo.ai/developer-zone/>`_)
@@ -10,7 +38,7 @@ Changelog
 
   * yolov8
 
-* Porfiler change:
+* Profiler change:
 
   * Removal of ``--mode`` flag from ``hailomz profile`` command, which generates a report according to provided HAR state.
 
@@ -128,7 +156,7 @@ Changelog
   * yolov5m_seg
   * yolov5l_seg
 
-* New object detecion variants for high resolution images:
+* New object detection variants for high resolution images:
 
   * yolov7e6
   * yolov5n6_6.1
@@ -215,9 +243,9 @@ Changelog
 
 * ReID training docker for the Hailo model repvgg_a0_person_reid_512/2048
 
-**NOTE:**  Ubuntu 18.04 will be deprecated in Hailo Model Zoo future version
+**NOTE:**\  Ubuntu 18.04 will be deprecated in Hailo Model Zoo future version
 
-**NOTE:**  Python 3.6 will be deprecated in Hailo Model Zoo future version
+**NOTE:**\  Python 3.6 will be deprecated in Hailo Model Zoo future version
 
 **v2.1**
 
@@ -270,7 +298,7 @@ Changelog
   * unet_mobilenet_v2
 
 * Support Oxford-IIIT Pet Dataset
-* New mutli-network example: detection_pose_estimation which combines the following networks:
+* New multi-network example: detection_pose_estimation which combines the following networks:
 
   * yolov5m_wo_spp_60p
   * centerpose_repvgg_a0

docs/GETTING_STARTED.rst

@@ -9,8 +9,8 @@ System Requirements
 
 * Ubuntu 20.04/22.04, 64 bit (supported also on Windows, under WSL2)
 * Python 3.8/3.9/3.10, including ``pip`` and ``virtualenv``
-* Hailo Dataflow Compiler v3.26.0 (Obtain from `hailo.ai <http://hailo.ai>`_\ )
-* HailoRT 4.16.0 (Obtain from `hailo.ai <http://hailo.ai>`_\ ) - required only for inference on Hailo-8.
+* Hailo Dataflow Compiler v3.27.0 (Obtain from `hailo.ai <http://hailo.ai>`_\ )
+* HailoRT 4.17.0 (Obtain from `hailo.ai <http://hailo.ai>`_\ ) - required only for inference on Hailo-8.
 * The Hailo Model Zoo supports Hailo-8 connected via PCIe only.
 * Nvidia’s Pascal/Turing/Ampere GPU architecture (such as Titan X Pascal, GTX 1080 Ti, RTX 2080 Ti, or RTX A4000)
 * GPU driver version 525
@@ -24,8 +24,8 @@ Install Instructions
 Hailo Software Suite
 ^^^^^^^^^^^^^^^^^^^^
 
-The model requires the corresponding Dataflow Compiler version, and the optional HailoRT version. Therefore it is recommended to use the 
-`Hailo Software Suite <https://hailo.ai/developer-zone/sw-downloads/>`_, that includes all of Hailo's SW components and insures compatibility 
+The model requires the corresponding Dataflow Compiler version, and the optional HailoRT version. Therefore it is recommended to use the
+`Hailo Software Suite <https://hailo.ai/developer-zone/sw-downloads/>`_, that includes all of Hailo's SW components and insures compatibility
 across products versions.
 
 The Hailo Software Suite is composed of the Dataflow Compiler, HailoRT, TAPPAS and the Model Zoo (:ref:`see diagram below <sw_suite_figure>`).
@@ -116,6 +116,9 @@ The following scheme shows high-level view of the model-zoo evaluation process,
 
 By default, each stage executes all of its previously necessary stages according to the above diagram. The post-parsing stages also have an option to start from the product of previous stages (i.e., the Hailo Archive (HAR) file), as explained below. The operations are configured through a YAML file that exist for each model in the cfg folder. For a description of the YAML structure please see `YAML <YAML.rst>`_.
 
+**NOTE:**\  Hailo Model Zoo provides the following functionality for Model Zoo models only. If you wish to use your custom model, use the Dataflow Compiler directly.
+
+
 Parsing
 -------
 
@@ -131,6 +134,12 @@ The pre-trained models are stored on AWS S3 and will be downloaded automatically
 
    hailomz parse <model_name> --hw-arch hailo15h
 
+* To customize the parsing behavior, use ``--start-node-names`` and\or ``--end-node-names`` flags:
+
+.. code-block::
+
+    hailomz parse <model_name> --start-node-names <name1> --end-node-names <name1> <name2>
+
 Optimization
 ------------
 
@@ -169,30 +178,33 @@ To add input conversion to the model, use the input conversion flag:
 
     hailomz optimize <model_name> --input-conversion nv12_to_rgb
 
-Do not use the flag if an input conversion already exist in the alls or in the YAML.
+* Do not use the flag if an input conversion already exist in the alls or in the YAML.
 
 To add input resize to the model, use the resize flag:
 
 .. code-block::
 
     hailomz optimize <model_name> --resize 1080 1920
 
-Do not use the flag if resize already exist in the alls or in the YAML.
-
-Profiling
----------
+* Do not use the flag if resize already exist in the alls or in the YAML.
 
-To generate the model profiler report:
+To adjust the number of classes in post-processing configuration, use classes flag:
 
 .. code-block::
 
-   hailomz profile <model_name>
+    hailomz optimize <model_name> --classes 80
 
-To generate the model profiler report using a previously generated HAR file:
+* Use this flag only if post-process exists in the alls or in the YAML.
+
+Profiling
+---------
+
+To generate the model profiler report:
 
 .. code-block::
 
-   hailomz profile <model_name> --har /path/to/model.har
+   hailomz parse <model_name>
+   hailo profiler path/to/model.har
 
 * When profiling a Quantized HAR file (the result of the optimization process), the report contains information about your model and accuracy.
 

docs/OPTIMIZATION.rst

@@ -36,6 +36,8 @@ Both steps may degrade the model accuracy, therefore, evaluation is needed to ve
 .. figure:: images/quant_flow.svg
 
 
+**NOTE:**\  Hailo Model Zoo provides the following functionality for Model Zoo models only. If you wish to use your custom model, use the Dataflow Compiler directly.
+
 #. 
    First step includes full precision validation. This step is important to make sure parsing was successful and we built the pre/post processing and evaluation of the model correctly. In the Hailo Model Zoo, we can execute the following which will infer a specific model in full precision to verify that the accuracy is correct (this will be our baseline for measuring degradation):