# Model loading method[[中文]](./README_CN.md) In esp-sr, both WakeNet and MultiNet will use a large amount of model data, and the model data is located in `ESP-SR_PATH/model/`. Currently esp-sr supports the following model loading methods: ESP32: - Load directly from Flash ESP32S3: - Load from Flash spiffs partition - Load from external SDCard So that on ESP32S3 you can: - Greatly reduce the size of the user application APP BIN - Convenient for users to perform OTA - Supports reading and changing models from SD card, which is more convenient and can reduce the size of module Flash used in the project - When the user is developing the code, when the modification does not involve the model, it can avoid flashing the model data every time, greatly reducing the flashing time and improving the development efficiency ## 1. Model configuration introduction Run `idf.py menuconfig` navigate to `ESP Speech Recognition`: ![overview](../img/model-1.png) ### 1.1 Net to use acceleration This option can configure the acceleration mode of the model, the user does not need to modify it, please keep the default configuration. ### 1.2 model data path This option is only available on ESP32S3. It indicates the storage location of the model data. It supports the choice of `spiffs partition` or `SD Card`. - `spiffs partition` means that the model data is stored in the Flash spiffs partition, and the model data will be loaded from the Flash spiffs partition - `SD Card` means that the model data is stored in the SD card, and the model data will be loaded from the SD Card ### 1.3 use wakenet This option is turned on by default. When the user only uses `AEC` or `BSS`, etc., and does not need to run `WakeNet` or `MultiNet`, please turn off this option, which will reduce the size of the project firmware in some cases. - Wake word engine Wake word model engine selection. ESP32 supports: - WakeNet 5 (quantized with 16-bit) ESP32S3 supports: - WakeNet 7 (quantized with 16-bit) - WakeNet 7 (quantized with 8-bit) - WakeNet 8 (quantized with 16-bit) - Wake word name Wake-up word selection, the wake-up words supported by each wake-up engine are different. For more details, please refer to [WakeNet](../wake_word_engine/README.md) . ### 1.4 use multinet This option is turned on by default. When users only use WakeNet or other algorithm modules, please turn off this option, which will reduce the size of the project firmware in some cases. - langugae Speech commands recognition language selection, ESP32 only supports Chinese, ESP32S3 supports Chinese or English. - speech commands recognition model model selection. ESP32 supports: - chinese single recognition (MultiNet2) ESP32S3 supports: - chinese single recognition (MultiNet3) - chinese continuous recognition (MultiNet3) - chinese single recognition (MultiNet4) - Add speech commands Users add speech commands according to their needs. For more details, please refer to [MultiNet](../speech_command_recognition/README.md) . ## 2. How to use After the user completes the above configuration choices, please refer to esp-skainet to initialize and use the application layer. Here is an introduction to the code implementation of model data loading in the project. ### 2.1 Use ESP32 When the user uses ESP32, since it only supports loading the model data directly from the Flash, the model data in the code will automatically read the required data from the Flash according to the address. ### 2.2 Use ESP32S3 #### 2.2.1 Model data in SPIFFS When the user configuration #1.2 model data storage location is `spiffs partition`, the user needs to: - Write a partition table: ``` model, data, spiffs, , SIZE, ``` Among them, `SIZE` can refer to the recommended size when the user uses 'idf.py build' to compile, for example: ``` Recommended model partition size: 500K ``` - Initialize the spiffs partition **Use the provided API**: User can use `srmodel_spiffs_init()` API to initialize spiffs. **Write by yourself**: When users need to store other files in the spiffs partition at the same time, such as web pages, they can write the spiffs initialization function by themselves. Pay attention to the configuration of `esp_vfs_spiffs_conf`: - base_path: The model storage `base_path` is `srmodel` and cannot be changed - partition_label: The partition label of the model is `model`, which needs to be consistent with the `Name` in the above partition table After completing the above configuration, the project will automatically generate `model.bin` after the project is compiled, and flash it to the spiffs partition. **Note: After the user changes the model, be sure to run `idf.py clean` before compiling again.** #### 2.2.1 Model data in SD Card When the user configuration #1.2 model data storage location is `SD Card`, the user needs to: - Manually move model data Move the model to SDCard. After the user completes the above configuration, you can compile first. After compiling, copy the files in the `ESP-SR_PATH/model/target/` directory to the root directory of the SD card. - Custom model path If the user wants to place the model in the specified folder, he can modify the `get_model_base_path()` function by himself, located in `ESP-SR_PATH/model/model_path.c`. For example, if the specified folder is `espmodel` in the SD card directory, the function can be modified to: ``` char *get_model_base_path(void) { #if defined CONFIG_MODEL_IN_SDCARD return "sdcard/espmodel"; #elif defined CONFIG_MODEL_IN_SPIFFS return "srmodel"; #else return NULL; #endif } ``` - Initialize the SD card The user needs to initialize the SD card to enable the system to record the SD card. The user can directly call `sd_card_mount("/sdcard")` to initialize the SD card that supports the development board if use esp-skainet. Otherwise, you need to write it yourself.