Squashed 'tinyml-modelzoo/' changes from 574d0a75c..41c7e5bc8

41c7e5bc8 TINYML_ALGO-706
2de4f335e TINYML_ALGO-706

git-subtree-dir: tinyml-modelzoo
git-subtree-split: 41c7e5bc83e0d557fe23c805298c2358c8df7ab2

Author: Adithya-Thonse

examples/MNIST_image_classification/config_image_classification_mnist.yaml

@@ -4,7 +4,7 @@ common:
   target_device: MSPM0G5187
 dataset:
   dataset_name: mnist_image_classification
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/mnist_classes.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/mnist_classes.zip
 data_processing_feature_extraction:
   feature_extraction_name: Mnist_Default
 training:

examples/MNIST_image_classification/readme.md

@@ -35,7 +35,7 @@
   - **Source:** MNIST dataset exported via torchvision
   - **Classes:** 10 digits (0-9)
   - **Image Format:** 28x28 grayscale PNG images
-  - **Download:** [mnist_classes.zip](https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/mnist_classes.zip)
+  - **Download:** [mnist_classes.zip](https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/mnist_classes.zip)
 
 
 For dataset recreation instructions, refer to `readme_dataset_creation.md`.

examples/MNIST_image_classification/readme_dataset_creation.md

@@ -4,7 +4,7 @@
 ## Overview
 This repository provides:
 1. **The MNIST dataset** in `.zip` format, exported into a folder structure compatible with the Modelmaker flow.  
-   - Download here: [mnist_classes.zip](https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/mnist_classes.zip)  
+   - Download here: [mnist_classes.zip](https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/mnist_classes.zip)  
 2. **A Python script** (`dataset_mnist_creation.py`) used to convert the original [torchvision.datasets.MNIST](https://pytorch.org/vision/stable/generated/torchvision.datasets.MNIST.html) into the required format.
 
 Since the MNIST dataset is **not proprietary** but publicly available through `torchvision.datasets`, this script is included to allow anyone to regenerate the dataset if needed.

examples/PLAID_nilm_classification/config.yaml

@@ -3,7 +3,7 @@ common:
   target_device: F28P55
 dataset:
   dataset_name: plaid_submetered
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/plaid_nilm_submetered_dataset.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/plaid_nilm_submetered_dataset.zip
 data_processing_feature_extraction:
   feat_ext_transform:
   - FFT_FE

examples/PLAID_nilm_classification/readme.md

@@ -34,7 +34,7 @@ The classes here correspond to **11 different appliance types**:
 10. **Vacuum**
 11. **Washing Machine**
 
-In this dataset, each class directory contains files corresponding to the voltage and current measurements when only that appliance class is turned on. While the dataset is extensive, we have taken a subset of it to use with ModelMaker. You can find the dataset subset here: [PLAID_submetered_dataset](https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/plaid_nilm_submetered_dataset.zip)
+In this dataset, each class directory contains files corresponding to the voltage and current measurements when only that appliance class is turned on. While the dataset is extensive, we have taken a subset of it to use with ModelMaker. You can find the dataset subset here: [PLAID_submetered_dataset](https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/plaid_nilm_submetered_dataset.zip)
 
 ## Usage in Tiny ML ModelZoo
 
@@ -59,7 +59,7 @@ common:
 dataset:
     enable: True
     dataset_name: plaid_submetered
-    input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/plaid_nilm_submetered_dataset.zip
+    input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/plaid_nilm_submetered_dataset.zip
 ```
 
 The important parameters here are: task type `generic_timeseries_classification` has been selected. The target device is set to `F28P55`, ensuring that ModelMaker generates a compiled output that runs on this device. Dataset loading is enabled, and the correct dataset path to the zip folder is provided.

examples/ac_arc_fault/config_MSPM0.yaml

@@ -3,9 +3,9 @@ common:
   target_device: MSPM0G5187
 dataset:
   dataset_name: ac_arc_fault_log300_example_dsk
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/ac_arc_fault_log300.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/ac_arc_fault_log300.zip
 
-  # input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/ac_arc_fault.zip
+  # input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/ac_arc_fault.zip
   # split_type: within_files
   # split_factor:
   # - 0.6

examples/branched_model_parameters/config.yaml

@@ -3,7 +3,7 @@ common:
   target_device: F28P55
 dataset:
   dataset_name: wisdm_example
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/wisdm_dataset.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/wisdm_dataset.zip
 data_processing_feature_extraction:
   data_proc_transforms:
   - SimpleWindow

examples/dc_arc_fault/config_anomaly_detection_dsi.yaml

@@ -3,7 +3,7 @@ common:
   target_device: F28P55
 dataset:
   dataset_name: arc_fault_example_dsi_ad
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/arc_fault_dsi_anomaly_detection.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/arc_fault_dsi_anomaly_detection.zip
 data_processing_feature_extraction:
   data_proc_transforms:
   - SimpleWindow

examples/dc_arc_fault/config_anomaly_detection_dsk.yaml

@@ -3,7 +3,7 @@ common:
   target_device: F28P55
 dataset:
   dataset_name: arc_fault_example_dsk_ad
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/arc_fault_dsk_anomaly_detection.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/arc_fault_dsk_anomaly_detection.zip
 data_processing_feature_extraction:
   data_proc_transforms:
   - SimpleWindow

examples/dc_arc_fault/config_dsi.yaml

@@ -3,7 +3,7 @@ common:
   target_device: F28P55
 dataset:
   dataset_name: arc_fault_example_dsi
-  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_03_00/datasets/arc_fault_classification_dsi.zip
+  input_data_path: https://software-dl.ti.com/C2000/esd/mcu_ai/01_04_00/datasets/arc_fault_classification_dsi.zip
 data_processing_feature_extraction:
   data_proc_transforms:
   - Downsample