Add micro_speech function to process the spectrogram.

This commit is contained in:
iabdalkader 2020-11-19 02:15:15 +02:00
parent 8e14372d61
commit b26188faa5

View File

@ -18,6 +18,8 @@
#include "py/obj.h"
#include "py/objarray.h"
#include "libtf.h"
#include "py_tf.h"
#include "common.h"
#if MICROPY_PY_MICRO_SPEECH
#define kMaxAudioSampleSize (512)
@ -29,11 +31,14 @@
#define kFeatureElementCount (kFeatureSliceSize * kFeatureSliceCount)
#define kFeatureSliceStrideMs (20)
#define kFeatureSliceDurationMs (30)
#define kCategoryCount (4)
#define RAISE_OS_EXCEPTION(msg) nlr_raise(mp_obj_new_exception_msg(&mp_type_OSError, msg))
typedef struct _py_micro_speech_obj {
mp_obj_base_t base;
uint32_t n_slices;
bool new_slices;
int8_t spectrogram[kFeatureElementCount];
} py_micro_speech_obj_t;
@ -42,7 +47,7 @@ static const mp_obj_type_t py_micro_speech_type;
static void py_micro_speech_print(const mp_print_t *print, mp_obj_t self_in, mp_print_kind_t kind)
{
//py_micro_speech_obj_t *microspeech = MP_OBJ_TO_PTR(self_in);
printf("micro speech object\n");
printf("micro speech object yay!\n");
}
mp_obj_t py_micro_speech_make_new(const mp_obj_type_t *type, size_t n_args, size_t n_kw, const mp_obj_t *args)
@ -52,6 +57,7 @@ mp_obj_t py_micro_speech_make_new(const mp_obj_type_t *type, size_t n_args, size
py_micro_speech_obj_t *o = m_new_obj(py_micro_speech_obj_t);
o->base.type = &py_micro_speech_type;
o->n_slices = 0;
o->new_slices = false;
memset(o->spectrogram, 0, kFeatureElementCount);
if (libtf_initialize_micro_features() != 0) {
RAISE_OS_EXCEPTION("Failed to initialize micro features!");
@ -90,20 +96,115 @@ mp_obj_t py_micro_speech_audio_callback(mp_obj_t self_in, mp_obj_t buf_in)
microspeech->spectrogram + kFeatureSliceSize,
kFeatureElementCount - kFeatureSliceSize);
}
printf("slice index %ld\n", slice_index);
debug_printf("slice index %ld\n", slice_index);
size_t num_samples_read;
int8_t *new_slice = microspeech->spectrogram + (slice_index * kFeatureSliceSize);
if (libtf_generate_micro_features((int16_t*) pcmbuf.buf,
kMaxAudioSampleSize, kFeatureSliceSize, new_slice, &num_samples_read)) {
RAISE_OS_EXCEPTION("Feature generation failed!");
}
microspeech->new_slices = true;
return mp_const_none;
}
STATIC MP_DEFINE_CONST_FUN_OBJ_2(py_micro_speech_audio_callback_obj, py_micro_speech_audio_callback);
STATIC void py_tf_input_callback(void *callback_data, void *model_input, const unsigned int input_height,
const unsigned int input_width, const unsigned int input_channels, const bool is_signed, const bool is_float)
{
// Copy feature buffer to input tensor
for (int i = 0; i < kFeatureElementCount; i++) {
((int8_t *) model_input)[i] = ((int8_t *) callback_data)[i];
}
}
STATIC void py_tf_output_callback(void *callback_data, void *model_output, const unsigned int output_height,
const unsigned int output_width, const unsigned int output_channels, const bool is_signed, const bool is_float)
{
uint8_t *results = (uint8_t *) callback_data;
PY_ASSERT_TRUE_MSG(output_height == 1, "Expected model output height to be 1!");
PY_ASSERT_TRUE_MSG(output_width == 1, "Expected model output width to be 1!");
PY_ASSERT_TRUE_MSG(output_channels == 4, "Expected model output channels to be 4!");
for (int i=0; i<output_channels; i++) {
debug_printf("%.2f ", (double)((((uint8_t *) model_output)[i] ^ (is_signed ? 128 : 0)) / 255.0f));
//results[i] = (((uint8_t *) model_output)[i] ^ (is_signed ? 128 : 0)) / 255.0f;
results[i] = (((uint8_t *) model_output)[i] ^ (is_signed ? 128 : 0));
}
}
STATIC mp_obj_t py_micro_speech_listen(uint n_args, const mp_obj_t *args, mp_map_t *kw_args)
{
fb_alloc_mark();
py_tf_alloc_putchar_buffer();
uint32_t tensor_arena_size;
uint8_t *tensor_arena = fb_alloc_all(&tensor_arena_size, FB_ALLOC_PREFER_SIZE);
py_micro_speech_obj_t *microspeech = args[0];
py_tf_model_obj_t *arg_model = args[1];
float threshold = py_helper_keyword_float(n_args, args, 2, kw_args, MP_OBJ_NEW_QSTR(MP_QSTR_threshold), 0.9f);
uint32_t timeout = py_helper_keyword_int(n_args, args, 3, kw_args, MP_OBJ_NEW_QSTR(MP_QSTR_timeout), 1000);
int8_t spectrogram[kFeatureElementCount];
uint32_t results_count = 0;
uint8_t results[kCategoryCount];
uint32_t average_scores[kCategoryCount];
for (int i=0; i<kCategoryCount; i++) {
average_scores[i] = 0;
}
//mp_obj_list_t *output_list = mp_obj_new_list(kCategoryCount, NULL);
uint32_t start = HAL_GetTick();
uint32_t last_timestamp = start;
while (timeout == 0 || (HAL_GetTick() - start) < timeout) {
__WFI();
if (microspeech->new_slices == true) {
__disable_irq();
microspeech->new_slices = false;
memcpy(spectrogram, microspeech->spectrogram, kFeatureElementCount);
__enable_irq();
PY_ASSERT_FALSE_MSG(libtf_invoke(arg_model->model_data,
tensor_arena,
tensor_arena_size,
py_tf_input_callback,
spectrogram,
py_tf_output_callback,
results),
py_tf_putchar_buffer - (PY_TF_PUTCHAR_BUFFER_LEN - py_tf_putchar_buffer_len));
results_count++;
for (int i=0; i<kCategoryCount; i++) {
average_scores[i] += results[i];
}
if ((HAL_GetTick() - last_timestamp) > 1500) {
for (int i=0; i<kCategoryCount; i++) {
if (average_scores[i] / (results_count * 255.0f) > threshold) {
fb_alloc_free_till_mark();
return mp_obj_new_int(i);
}
average_scores[i] = 0;
}
results_count = 0;
last_timestamp = HAL_GetTick();
}
}
}
fb_alloc_free_till_mark();
return mp_obj_new_int(0);
}
STATIC MP_DEFINE_CONST_FUN_OBJ_KW(py_micro_speech_listen_obj, 2, py_micro_speech_listen);
STATIC const mp_rom_map_elem_t py_micro_speech_locals_dict_table[] = {
// instance methods
{ MP_ROM_QSTR(MP_QSTR_audio_callback), MP_ROM_PTR(&py_micro_speech_audio_callback_obj) },
{ MP_ROM_QSTR(MP_QSTR_listen), MP_ROM_PTR(&py_micro_speech_listen_obj) },
// class constants
};
STATIC MP_DEFINE_CONST_DICT(py_micro_speech_locals_dict, py_micro_speech_locals_dict_table);