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lib/libtf: Add support for 1D/1D regression models.
* Fixes #1751. * Fixes #1739.
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@ -72,6 +72,8 @@ int libtf_generate_micro_features(const int16_t *input, // Audio samples
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int8_t *output, // Slice data
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size_t *num_samples_read); // Number of samples used
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int libtf_regression_1Dinput_1Doutput(const unsigned char *model_data, uint8_t* tensor_arena, libtf_parameters_t* params, float* input_data, float* output_data);
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#ifdef __cplusplus
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}
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#endif
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@ -8,10 +8,13 @@
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*
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* Python Tensorflow library wrapper.
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*/
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#include <stdio.h>
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#include "py/runtime.h"
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#include "py/obj.h"
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#include "py/objlist.h"
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#include "py/objtuple.h"
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#include "py/objarray.h"
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#include "py/binary.h"
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#include "py_helper.h"
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#include "imlib_config.h"
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@ -254,6 +257,53 @@ STATIC py_tf_model_obj_t *py_tf_load_alloc(mp_obj_t path_obj)
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}
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}
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STATIC mp_obj_t py_tf_regression(uint n_args, const mp_obj_t *args, mp_map_t *kw_args)
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{
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fb_alloc_mark();
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py_tf_alloc_putchar_buffer();
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// read model
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py_tf_model_obj_t *arg_model = py_tf_load_alloc(args[0]);
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size_t input_size = (&arg_model->params)->input_width;
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size_t output_size = (&arg_model->params)->output_channels;
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// read input
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mp_obj_array_t *arg_input_array = args[1];
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// check for the input size
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if (input_size != arg_input_array->len) {
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mp_raise_msg(&mp_type_ValueError, MP_ERROR_TEXT("Input array size is not same as model input size!"));
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}
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float input_array[input_size];
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for (size_t i=0; i<input_size; i++) {
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input_array[i] = (float) mp_obj_float_get(
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mp_binary_get_val_array(arg_input_array->typecode, arg_input_array->items, i)
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);
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}
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uint8_t *tensor_arena = fb_alloc(arg_model->params.tensor_arena_size, FB_ALLOC_PREFER_SPEED | FB_ALLOC_CACHE_ALIGN);
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float output_data[output_size];
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// predict the output using tflite model
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if (libtf_regression_1Dinput_1Doutput(arg_model->model_data,
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tensor_arena, &arg_model->params, input_array, output_data) != 0){
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mp_raise_msg(&mp_type_OSError, MP_ERROR_TEXT("Coundnt execute the model to predict the output"));
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}
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// read output
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mp_obj_list_t * out = (mp_obj_list_t *) mp_obj_new_list(output_size, NULL);
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for (size_t j=0; j<(output_size); j++) {
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out->items[j] = mp_obj_new_float(output_data[j]);
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}
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fb_alloc_free_till_mark();
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return out;
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}
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STATIC MP_DEFINE_CONST_FUN_OBJ_KW(py_tf_regression_obj, 2, py_tf_regression);
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typedef struct py_tf_input_data_callback_data {
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image_t *img;
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rectangle_t *roi;
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@ -788,7 +838,8 @@ STATIC const mp_rom_map_elem_t locals_dict_table[] = {
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{ MP_ROM_QSTR(MP_QSTR_output_zero_point), MP_ROM_PTR(&py_tf_output_zero_point_obj) },
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{ MP_ROM_QSTR(MP_QSTR_classify), MP_ROM_PTR(&py_tf_classify_obj) },
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{ MP_ROM_QSTR(MP_QSTR_segment), MP_ROM_PTR(&py_tf_segment_obj) },
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{ MP_ROM_QSTR(MP_QSTR_detect), MP_ROM_PTR(&py_tf_detect_obj) }
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{ MP_ROM_QSTR(MP_QSTR_detect), MP_ROM_PTR(&py_tf_detect_obj) },
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{ MP_ROM_QSTR(MP_QSTR_regression), MP_ROM_PTR(&py_tf_regression_obj) }
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};
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STATIC MP_DEFINE_CONST_DICT(locals_dict, locals_dict_table);
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@ -811,13 +862,15 @@ STATIC const mp_rom_map_elem_t globals_dict_table[] = {
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{ MP_ROM_QSTR(MP_QSTR_classify), MP_ROM_PTR(&py_tf_classify_obj) },
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{ MP_ROM_QSTR(MP_QSTR_segment), MP_ROM_PTR(&py_tf_segment_obj) },
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{ MP_ROM_QSTR(MP_QSTR_detect), MP_ROM_PTR(&py_tf_detect_obj) },
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{ MP_ROM_QSTR(MP_QSTR_regression), MP_ROM_PTR(&py_tf_regression_obj) }
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#else
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{ MP_ROM_QSTR(MP_QSTR_load), MP_ROM_PTR(&py_func_unavailable_obj) },
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{ MP_ROM_QSTR(MP_QSTR_load_builtin_model), MP_ROM_PTR(&py_func_unavailable_obj) },
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{ MP_ROM_QSTR(MP_QSTR_free_from_fb), MP_ROM_PTR(&py_func_unavailable_obj) },
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{ MP_ROM_QSTR(MP_QSTR_classify), MP_ROM_PTR(&py_func_unavailable_obj) },
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{ MP_ROM_QSTR(MP_QSTR_segment), MP_ROM_PTR(&py_func_unavailable_obj) },
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{ MP_ROM_QSTR(MP_QSTR_detect), MP_ROM_PTR(&py_func_unavailable_obj) }
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{ MP_ROM_QSTR(MP_QSTR_detect), MP_ROM_PTR(&py_func_unavailable_obj) },
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{ MP_ROM_QSTR(MP_QSTR_regression), MP_ROM_PTR(&py_func_unavailable_obj) }
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#endif // IMLIB_ENABLE_TF
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};
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