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Squashed 'tinyml-modelzoo/' changes from c4c185f2..b88d82c5
b88d82c5 Pull request #23: Added export_samples_per_class option in the config file and added ondevice learning documentation REVERT: c4c185f2 fixed broken links git-subtree-dir: tinyml-modelzoo git-subtree-split: b88d82c5d0f3adfce210029001e964c0d7a619ea
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docs/deploying_anomaly_detection_models_from_modelzoo_to_device/readme.md

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@@ -159,7 +159,9 @@ Once all prerequisites are met, follow these steps to deploy the model on your d
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**2. Import the Project**
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- Go to **File** > **Import Projects**
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- A dialog box will appear. Click **Browse** to select the project folder.<img src="assets/import_project.png" alt="Import Project Dialog" width="1200">
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- A dialog box will appear. Click **Browse** to select the project folder.
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<img src="assets/import_project.png" alt="Import Project Dialog" width="1200">
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- Select the `generic_timeseries_anomalydetection` folder
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```
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{F29H85X_SDK_INSTALL_PATH}/examples/rtlibs/ai/examples/generic_timeseries_anomalydetection
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```
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<img src="assets/f29h85x_select_example_from_sdk.png" alt="Import Project Dialog" width="1200">
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- **For C2000 F28x devices** (F28003x, F28004x, F28P55x, F28P65x): Navigate to your C2000Ware installation directory:
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```
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{C2000WARE_INSTALL_PATH}/libraries/ai/examples/generic_timeseries_anomalydetection
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```
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<img src="assets/f28p55x_select_example_from_sdk.png" alt="Import Project Dialog" width="1200">
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**3. Open the folder and select the example for the device you are using and click finish**
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**9. Flash the Project**
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Right click on target config > **Flash Project**
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<img src="assets/flash_view.png" alt="Debug Perspective" width="1200">
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### Start Debug Session
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After flashing, the debug perspective should open automatically and click the Green resume button on top left corner. If not, go to **Run** > **Debug**.
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<img src="assets/debug_view.png" alt="Resume Button in Debug Perspective" width="1200">
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### Run the Program
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4. **Compare to threshold** to determine if the sample is normal or anomalous
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5. **Display results** in the console
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<img src="assets/result.png" alt="Anomaly Detection Test Results" width="1200">
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<img src="assets/result.png" alt="Anomaly Detection Test Results" width="1200">
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**Understanding the Results:**
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- **Reconstruction Error**: Mean Squared Error between input and autoencoder output

docs/ondevice_training/anomaly_detection_odt.md

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