Update README.md

README.md

@@ -2,7 +2,7 @@
 license: other
 license_name: sla0044
 license_link: >-
-  https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/LICENSE.md
+  https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/LICENSE.md
 ---
 # GMP HAR model
 
@@ -64,8 +64,8 @@ The inference time is reported is calculated on STM32 board **B-U585I-IOT02A** r
 
 | Model                                                                        | Format | Input Shape | Target Board  | Activation RAM (KiB) | Runtime RAM (KiB) | Weights Flash (KiB) | Code Flash (KiB) | Total RAM (KiB)   | Total Flash (KiB) | Inference Time (ms) | STM32Cube.AI version  |
 |:----------------------------------------------------------------------------:|:------:|:-----------:|:-------:|:--------------------:|:-----------------:|:-------------------:|:----------------:|:-----------------:|:-----------------:|:---------------------:|:---------------------:|
-| [GMP wl 24](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_24/gmp_wl_24.h5)  | FLOAT32| 24 x 3 x 1  | B-U585I-IOT02A | 4.25          | 2.08              | 5.70                | 12.29            |  6.33             | 18.96             | 4.42      | 10.0.0     |
-| [GMP wl 48](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_48/gmp_wl_48.h5)  | FLOAT32| 48 x 3 x 1  | B-U585I-IOT02A | 8.83          | 2.08              | 5.70                | 12.29            |  10.91            | 18.96             | 10.64     | 10.0.0     |
+| [GMP wl 24](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_24/gmp_wl_24.h5)  | FLOAT32| 24 x 3 x 1  | B-U585I-IOT02A | 4.25          | 2.08              | 5.70                | 12.29            |  6.33             | 18.96             | 4.42      | 10.0.0     |
+| [GMP wl 48](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_48/gmp_wl_48.h5)  | FLOAT32| 48 x 3 x 1  | B-U585I-IOT02A | 8.83          | 2.08              | 5.70                | 12.29            |  10.91            | 18.96             | 10.64     | 10.0.0     |
 
 
 
@@ -77,13 +77,13 @@ Dataset details: A custom dataset and not publically available, Number of classe
 
 | Model                                                                                          |  Format  | Resolution | Accuracy (%) |
 |:----------------------------------------------------------------------------------------------:|:--------:|:----------:|:-------------:|
-| [GMP wl 24](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_custom_dataset/mobility_v1/gmp_wl_24/gmp_wl_24.h5)            | FLOAT32  | 24 x 3 x 1 | 94.08         |
-| [GMP wl 48](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_custom_dataset/mobility_v1/gmp_wl_48/gmp_wl_48.h5)            | FLOAT32  | 48 x 3 x 1 | 93.84         |
+| [GMP wl 24](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_custom_dataset/mobility_v1/gmp_wl_24/gmp_wl_24.h5)            | FLOAT32  | 24 x 3 x 1 | 94.08         |
+| [GMP wl 48](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_custom_dataset/mobility_v1/gmp_wl_48/gmp_wl_48.h5)            | FLOAT32  | 48 x 3 x 1 | 93.84         |
 
 
 Confusion matrix for GMP wl 24 with Float32 weights for mobility_v1 dataset is given below.
 
-![plot](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/doc/img/mobility_v1_gmp_wl_24_confusion_matrix.png)
+![plot](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/doc/img/mobility_v1_gmp_wl_24_confusion_matrix.png)
 
 ### Accuracy with WISDM dataset
 
@@ -92,8 +92,8 @@ Dataset details: [link](([WISDM](https://www.cis.fordham.edu/wisdm/dataset.php))
 
 | Model                                                                                  |  Format  |  Resolution |  Accuracy (%)  |
 |:--------------------------------------------------------------------------------------:|:--------:|:-----------:|:--------------:|
-| [GMP wl 24](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_24/gmp_wl_24.h5)            | FLOAT32  | 24 x 3 x 1  | 84.49          |
-| [GMP wl 48](https://github.com/STMicroelectronics/stm32ai-modelzoo/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_48/gmp_wl_48.h5)            | FLOAT32  | 48 x 3 x 1  | 87.05          |
+| [GMP wl 24](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_24/gmp_wl_24.h5)            | FLOAT32  | 24 x 3 x 1  | 84.49          |
+| [GMP wl 48](https://github.com/STMicroelectronics/stm32ai-modelzoo/tree/main/human_activity_recognition/gmp/ST_pretrainedmodel_public_dataset/WISDM/gmp_wl_48/gmp_wl_48.h5)            | FLOAT32  | 48 x 3 x 1  | 87.05          |
 
 
 ## Retraining and Integration in a simple example: