diff --git a/libraries/TFLiteMicro/examples/hello_world/README.md b/libraries/TFLiteMicro/examples/hello_world/README.md new file mode 100644 index 00000000000..6fadc59a176 --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/README.md @@ -0,0 +1,18 @@ +# Hello World Example + +This example is designed to demonstrate the absolute basics of using [TensorFlow +Lite for Microcontrollers](https://www.tensorflow.org/lite/microcontrollers). +It includes the full end-to-end workflow of training a model, converting it for +use with TensorFlow Lite for Microcontrollers for running inference on a +microcontroller. + +The model is trained to replicate a `sine` function and generates a pattern of +data to either blink LEDs or control an animation, depending on the capabilities +of the device. + +## Deploy to ESP32 + +The sample has been tested on ESP-IDF version `release/v4.2` and `release/v4.4` with the following devices: +- [ESP32-DevKitC](http://esp-idf.readthedocs.io/en/latest/get-started/get-started-devkitc.html) +- [ESP32-S3-DevKitC](https://docs.espressif.com/projects/esp-idf/en/latest/esp32s3/hw-reference/esp32s3/user-guide-devkitc-1.html) +- [ESP-EYE](https://github.com/espressif/esp-who/blob/master/docs/en/get-started/ESP-EYE_Getting_Started_Guide.md) diff --git a/libraries/TFLiteMicro/examples/hello_world/constants.cpp b/libraries/TFLiteMicro/examples/hello_world/constants.cpp new file mode 100644 index 00000000000..bc32fc3f9c0 --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/constants.cpp @@ -0,0 +1,19 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#include "constants.h" + +// This is a small number so that it's easy to read the logs +const int kInferencesPerCycle = 20; diff --git a/libraries/TFLiteMicro/examples/hello_world/constants.h b/libraries/TFLiteMicro/examples/hello_world/constants.h new file mode 100644 index 00000000000..f452893209d --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/constants.h @@ -0,0 +1,32 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_CONSTANTS_H_ +#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_CONSTANTS_H_ + +// This constant represents the range of x values our model was trained on, +// which is from 0 to (2 * Pi). We approximate Pi to avoid requiring additional +// libraries. +const float kXrange = 2.f * 3.14159265359f; + +// This constant determines the number of inferences to perform across the range +// of x values defined above. Since each inference takes time, the higher this +// number, the more time it will take to run through the entire range. The value +// of this constant can be tuned so that one full cycle takes a desired amount +// of time. Since different devices take different amounts of time to perform +// inference, this value should be defined per-device. +extern const int kInferencesPerCycle; + +#endif // TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_CONSTANTS_H_ diff --git a/libraries/TFLiteMicro/examples/hello_world/hello_world.ino b/libraries/TFLiteMicro/examples/hello_world/hello_world.ino new file mode 100644 index 00000000000..04fdd064a48 --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/hello_world.ino @@ -0,0 +1,111 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + + +#include "tensorflow/lite/micro/micro_mutable_op_resolver.h" +#include "tensorflow/lite/micro/micro_interpreter.h" +#include "tensorflow/lite/micro/system_setup.h" +#include "tensorflow/lite/schema/schema_generated.h" + +#include "model.h" +#include "constants.h" +#include "output_handler.h" + +// Globals, used for compatibility with Arduino-style sketches. +namespace { +const tflite::Model* model = nullptr; +tflite::MicroInterpreter* interpreter = nullptr; +TfLiteTensor* input = nullptr; +TfLiteTensor* output = nullptr; +int inference_count = 0; + +constexpr int kTensorArenaSize = 2000; +uint8_t tensor_arena[kTensorArenaSize]; +} // namespace + +// The name of this function is important for Arduino compatibility. +void setup() { + // Map the model into a usable data structure. This doesn't involve any + // copying or parsing, it's a very lightweight operation. + model = tflite::GetModel(g_model); + if (model->version() != TFLITE_SCHEMA_VERSION) { + MicroPrintf("Model provided is schema version %d not equal to supported " + "version %d.", model->version(), TFLITE_SCHEMA_VERSION); + return; + } + + // Pull in only the operation implementations we need. + static tflite::MicroMutableOpResolver<1> resolver; + if (resolver.AddFullyConnected() != kTfLiteOk) { + return; + } + + // Build an interpreter to run the model with. + static tflite::MicroInterpreter static_interpreter( + model, resolver, tensor_arena, kTensorArenaSize); + interpreter = &static_interpreter; + + // Allocate memory from the tensor_arena for the model's tensors. + TfLiteStatus allocate_status = interpreter->AllocateTensors(); + if (allocate_status != kTfLiteOk) { + MicroPrintf("AllocateTensors() failed"); + return; + } + + // Obtain pointers to the model's input and output tensors. + input = interpreter->input(0); + output = interpreter->output(0); + + // Keep track of how many inferences we have performed. + inference_count = 0; +} + +// The name of this function is important for Arduino compatibility. +void loop() { + // Calculate an x value to feed into the model. We compare the current + // inference_count to the number of inferences per cycle to determine + // our position within the range of possible x values the model was + // trained on, and use this to calculate a value. + float position = static_cast(inference_count) / + static_cast(kInferencesPerCycle); + float x = position * kXrange; + + // Quantize the input from floating-point to integer + int8_t x_quantized = x / input->params.scale + input->params.zero_point; + // Place the quantized input in the model's input tensor + input->data.int8[0] = x_quantized; + + // Run inference, and report any error + TfLiteStatus invoke_status = interpreter->Invoke(); + if (invoke_status != kTfLiteOk) { + MicroPrintf("Invoke failed on x: %f\n", + static_cast(x)); + return; + } + + // Obtain the quantized output from model's output tensor + int8_t y_quantized = output->data.int8[0]; + // Dequantize the output from integer to floating-point + float y = (y_quantized - output->params.zero_point) * output->params.scale; + + // Output the results. A custom HandleOutput function can be implemented + // for each supported hardware target. + HandleOutput(x, y); + + // Increment the inference_counter, and reset it if we have reached + // the total number per cycle + inference_count += 1; + if (inference_count >= kInferencesPerCycle) inference_count = 0; +} diff --git a/libraries/TFLiteMicro/examples/hello_world/model.cpp b/libraries/TFLiteMicro/examples/hello_world/model.cpp new file mode 100644 index 00000000000..f04a9f661c6 --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/model.cpp @@ -0,0 +1,237 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +// Automatically created from a TensorFlow Lite flatbuffer using the command: +// xxd -i model.tflite > model.cc + +// This is a standard TensorFlow Lite model file that has been converted into a +// C data array, so it can be easily compiled into a binary for devices that +// don't have a file system. + +// See train/README.md for a full description of the creation process. + +#include "model.h" + +// Keep model aligned to 8 bytes to guarantee aligned 64-bit accesses. +alignas(8) const unsigned char g_model[] = { + 0x1c, 0x00, 0x00, 0x00, 0x54, 0x46, 0x4c, 0x33, 0x14, 0x00, 0x20, 0x00, + 0x1c, 0x00, 0x18, 0x00, 0x14, 0x00, 0x10, 0x00, 0x0c, 0x00, 0x00, 0x00, + 0x08, 0x00, 0x04, 0x00, 0x14, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00, + 0x98, 0x00, 0x00, 0x00, 0xc8, 0x00, 0x00, 0x00, 0x1c, 0x03, 0x00, 0x00, + 0x2c, 0x03, 0x00, 0x00, 0x30, 0x09, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x60, 0xf7, 0xff, 0xff, + 0x10, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00, + 0x44, 0x00, 0x00, 0x00, 0x05, 0x00, 0x00, 0x00, 0x73, 0x65, 0x72, 0x76, + 0x65, 0x00, 0x00, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x73, 0x65, 0x72, 0x76, + 0x69, 0x6e, 0x67, 0x5f, 0x64, 0x65, 0x66, 0x61, 0x75, 0x6c, 0x74, 0x00, + 0x01, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xbc, 0xff, 0xff, 0xff, + 0x09, 0x00, 0x00, 0x00, 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0x03, 0x00, 0x00, 0x00, 0x40, 0x00, 0x00, 0x00, + 0x24, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0xd8, 0xff, 0xff, 0xff, + 0x06, 0x00, 0x00, 0x00, 0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, + 0x0c, 0x00, 0x0c, 0x00, 0x0b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04, 0x00, + 0x0c, 0x00, 0x00, 0x00, 0x72, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x72, + 0x0c, 0x00, 0x10, 0x00, 0x0f, 0x00, 0x00, 0x00, 0x08, 0x00, 0x04, 0x00, + 0x0c, 0x00, 0x00, 0x00, 0x09, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x09}; +const int g_model_len = 2488; diff --git a/libraries/TFLiteMicro/examples/hello_world/model.h b/libraries/TFLiteMicro/examples/hello_world/model.h new file mode 100644 index 00000000000..488f47b3afd --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/model.h @@ -0,0 +1,31 @@ +/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +// Automatically created from a TensorFlow Lite flatbuffer using the command: +// xxd -i model.tflite > model.cc + +// This is a standard TensorFlow Lite model file that has been converted into a +// C data array, so it can be easily compiled into a binary for devices that +// don't have a file system. + +// See train/README.md for a full description of the creation process. + +#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MODEL_H_ +#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MODEL_H_ + +extern const unsigned char g_model[]; +extern const int g_model_len; + +#endif // TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MODEL_H_ diff --git a/libraries/TFLiteMicro/examples/hello_world/output_handler.cpp b/libraries/TFLiteMicro/examples/hello_world/output_handler.cpp new file mode 100644 index 00000000000..0d5f80ee202 --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/output_handler.cpp @@ -0,0 +1,23 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#include "output_handler.h" +#include "tensorflow/lite/micro/micro_log.h" + +void HandleOutput(float x_value, float y_value) { + // Log the current X and Y values + MicroPrintf("x_value: %f, y_value: %f\n", static_cast(x_value), + static_cast(y_value)); +} diff --git a/libraries/TFLiteMicro/examples/hello_world/output_handler.h b/libraries/TFLiteMicro/examples/hello_world/output_handler.h new file mode 100644 index 00000000000..a16846043b3 --- /dev/null +++ b/libraries/TFLiteMicro/examples/hello_world/output_handler.h @@ -0,0 +1,24 @@ +/* Copyright 2019 The TensorFlow Authors. All Rights Reserved. + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +==============================================================================*/ + +#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_OUTPUT_HANDLER_H_ +#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_OUTPUT_HANDLER_H_ + +#include "tensorflow/lite/c/common.h" + +// Called by the main loop to produce some output based on the x and y values +void HandleOutput(float x_value, float y_value); + +#endif // TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_OUTPUT_HANDLER_H_ diff --git a/libraries/TFLiteMicro/examples/micro_speech/README.md b/libraries/TFLiteMicro/examples/micro_speech/README.md new file mode 100644 index 00000000000..ed293bf2e06 --- /dev/null +++ b/libraries/TFLiteMicro/examples/micro_speech/README.md @@ -0,0 +1,22 @@ +# Micro Speech Example + +This example shows how to run a 20 kB model that can recognize 2 keywords, +"yes" and "no", from speech data. + +The application listens to its surroundings with a microphone and indicates +when it has detected a word by displaying data on a screen. + +## Deploy to ESP32 + +The sample has been tested on ESP-IDF version `release/v4.2` and `release/v4.4` with the following devices: +- [ESP32-DevKitC](http://esp-idf.readthedocs.io/en/latest/get-started/get-started-devkitc.html) +- [ESP32-S3-DevKitC](https://docs.espressif.com/projects/esp-idf/en/latest/esp32s3/hw-reference/esp32s3/user-guide-devkitc-1.html) +- [ESP-EYE](https://github.com/espressif/esp-who/blob/master/docs/en/get-started/ESP-EYE_Getting_Started_Guide.md) + +### Sample output + + * When a keyword is detected you will see following output sample output on the log screen: + +``` +Heard yes () at