#!/usr/bin/env python3 # This file is part of the OpenMV project. # # Copyright (c) 2013-2022 Ibrahim Abdelkader # Copyright (c) 2013-2022 Kwabena W. Agyeman # # This work is licensed under the MIT license, see the file LICENSE for details. # # This script converts tflite models and labels to a C structs. import sys, os import glob import argparse import binascii def main(): parser = argparse.ArgumentParser(description='Converts TFLite models to C file.') parser.add_argument('--input', action = 'store', help = 'Input tflite models directory.', required=True) parser.add_argument('--header', action = 'store_true', help = 'Generate header file.', required=False, default=False) args = parser.parse_args() tflm_builtin_models = [] tflm_builtin_models_index = [] print('/* NOTE: This file is auto-generated. */\n') with open(os.path.join(args.input, "index.txt"), 'r') as f: for l in f.readlines(): if not l.startswith("#"): tflm_builtin_models_index.append(os.path.basename(os.path.splitext(l.strip())[0])) models_list = glob.glob(os.path.join(args.input, "*tflite")) if (args.header): # Generate the header file print('// Built-in TFLite Models.') print('typedef struct {') print(' const char *name;') print(' const unsigned int n_labels;') print(' const char **labels;') print(' const unsigned int size;') print(' const unsigned char *data;') print('}tflm_builtin_model_t;\n') print('extern const tflm_builtin_model_t tflm_builtin_models[];') else: # Generate the C file print('#include "imlib_config.h"') print('#include "tflm_builtin_models.h"') for model_file in models_list: model_size = os.path.getsize(model_file) model_name = os.path.basename(os.path.splitext(model_file)[0]) labels_file = os.path.splitext(model_file)[0]+'.txt' # Generate model labels. labels = [] n_labels = 0 if os.path.exists(labels_file): with open(labels_file, 'r') as f: labels = ['"{:s}"'.format(l.strip()) for l in f.readlines()] n_labels = len(labels) print('static const char *tflm_{:s}_labels[] __attribute__((aligned(16))) = {{{:s}}};'.format(model_name, ', '.join(labels))) # Generate model data. print('static const unsigned char tflm_{:s}_data[] = {{'.format(model_name)) with open(model_file, 'rb') as f: for chunk in iter(lambda: f.read(12), b''): print(' ', end='') print(' '.join(['0x{:02x},'.format(x) for x in chunk])) print('};') # Store model info in builtin models table. tflm_builtin_models.append([ model_name, n_labels, 'tflm_{:s}_labels'.format(model_name), model_size, 'tflm_{:s}_data'.format(model_name)] ) # Generate built-in models table. print('const tflm_builtin_model_t tflm_builtin_models[] = {') for model in tflm_builtin_models: if model[0] in tflm_builtin_models_index: print(' #if defined(IMLIB_ENABLE_TFLM_BUILTIN_{:s})'.format(model[0].upper())) print(' {{ "{:s}", {:d}, {:s}, {:d}, {:s} }},'.format(*model)) if model[0] in tflm_builtin_models_index: print(' #endif') print(' {0, 0, 0, 0, 0}') print('};') if __name__ == '__main__': main()