boochow

import sensor, lcd, image

sensor.reset()
sensor.set_framesize(sensor.QVGA)
sensor.set_pixformat(sensor.RGB565)
sensor.set_hmirror(False)
lcd.init(freq=15000000)

face_cascade = image.HaarCascade("frontalface", stages=25)
while (True):

boochow

[env:m5stack-fire]
platform = espressif32
board = m5stack-fire
framework = arduino
board_build.partitions = custom.csv
lib_deps = tfmicro
build_flags = -Ilib/tfmicro/third_party/gemmlowp -Ilib/tfmicro/third_party/flatbuffers/include 

boochow

#include<Arduino.h>
#include<math.h>
#include "tensorflow/lite/experimental/micro/kernels/all_ops_resolver.h"
#include "tensorflow/lite/experimental/micro/micro_error_reporter.h"
#include "tensorflow/lite/experimental/micro/micro_interpreter.h"
#include "sine_model_data.h"
#include <M5Stack.h>

#define BLACK 0x0000
#define WHITE 0xFFFF

boochow

[env:m5stack-fire]
platform = espressif32
board = m5stack-fire
framework = arduino
build_flags = -Ilib/tfmicro/third_party/gemmlowp -Ilib/tfmicro/third_party/flatbuffers/include 

boochow

#include "accelerometer_handler.h"

#include "constants.h"

#include <Arduino.h>
#include <M5Stack.h>
#include "utility/MPU9250.h"

MPU9250 IMU;

boochow

extern TfLiteStatus SetupAccelerometer(tflite::ErrorReporter* error_reporter);
extern bool ReadAccelerometer(tflite::ErrorReporter* error_reporter,
                              float* input, int length, bool reset_buffer);

boochow

[env:m5stack-fire]
platform = espressif32
board = m5stack-fire
framework = arduino
monitor_speed = 115200
build_flags = -DARDUINOSTL_M_H -Ilib/tfmicro/third_party/gemmlowp -Ilib/tfmicro/third_party/flatbuffers/include 

boochow

import tensorflow as tf

seq_length = 128

model = tf.keras.Sequential([
      tf.keras.layers.Conv2D(
          8, (4, 3),
          padding="same",
          activation="relu",
          input_shape=(seq_length, 3, 1)),                # output_shape=(batch, 128, 3, 8)

boochow

void loop() {
  // Attempt to read new data from the accelerometer
  bool got_data = ReadAccelerometer(error_reporter, model_input->data.f,
                                    input_length, should_clear_buffer);
  // Don't try to clear the buffer again
  should_clear_buffer = false;
  // If there was no new data, wait until next time
  if (!got_data) return;
  // Run inference, and report any error
  TfLiteStatus invoke_status = interpreter->Invoke();

boochow

#include "output_handler.h"
#include <Arduino.h>
#include <M5Stack.h>

void DrawWing() {
  int x = 60;
  int y = 20;
  int w = 200;
  int h = 200;
  int t = 20;