mirror of
https://github.com/espressif/esp-sr.git
synced 2025-09-15 15:28:44 +08:00
129 lines
4.8 KiB
Python
129 lines
4.8 KiB
Python
import io
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import os
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import argparse
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import shutil
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import math
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import sys
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sys.dont_write_bytecode = True
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from pack_model import pack_models
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def calculate_total_size(folder_path):
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total_size = 0
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for file_name in os.listdir(folder_path):
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path = os.path.join(folder_path, file_name)
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if os.path.isdir(path):
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total_size = total_size + calculate_total_size(path)
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if os.path.isfile(path):
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total_size = total_size + os.path.getsize(path)
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return total_size
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def copy_wakenet_from_sdkconfig(model_path, sdkconfig_path, target_path):
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"""
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Copy wakenet model from model_path to target_path based on sdkconfig
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"""
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models = []
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with io.open(sdkconfig_path, "r") as f:
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for label in f:
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label = label.strip("\n")
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if 'CONFIG_SR_WN' in label and '#' not in label[0]:
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if '=' in label:
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label = label.split("=")[0]
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if '_MULTI' in label:
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label = label[:-6]
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model_name = label.split("_SR_WN_")[-1].lower()
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models.append(model_name)
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for item in models:
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wakeword_model_path = model_path + '/wakenet_model/' + item
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if os.path.exists(wakeword_model_path):
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shutil.copytree(wakeword_model_path, target_path+'/'+item)
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def copy_multinet_from_sdkconfig(model_path, sdkconfig_path, target_path):
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"""
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Copy multinet model from model_path to target_path based on sdkconfig
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"""
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with io.open(sdkconfig_path, "r") as f:
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models_string = ''
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for label in f:
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label = label.strip("\n")
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if 'CONFIG_SR_MN' in label and label[0] != '#':
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models_string += label
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models = []
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if "CONFIG_SR_MN_CN_MULTINET3_SINGLE_RECOGNITION" in models_string:
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models.append('mn3_cn')
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elif "CONFIG_SR_MN_CN_MULTINET4_5_SINGLE_RECOGNITION_QUANT8" in models_string:
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models.append('mn4q8_cn')
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elif "CONFIG_SR_MN_CN_MULTINET4_5_SINGLE_RECOGNITION" in models_string:
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models.append('mn4_cn')
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elif "CONFIG_SR_MN_CN_MULTINET5_RECOGNITION_QUANT8" in models_string:
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models.append('mn5q8_cn')
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elif "CONFIG_SR_MN_CN_MULTINET6_QUANT" in models_string:
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models.append('mn6_cn')
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elif "CONFIG_SR_MN_CN_MULTINET6_AC_QUANT" in models_string:
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models.append('mn6_cn_ac')
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elif "CONFIG_SR_MN_CN_MULTINET7_QUANT" in models_string:
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models.append('mn7_cn')
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elif "CONFIG_SR_MN_CN_MULTINET7_AC_QUANT" in models_string:
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models.append('mn7_cn_ac')
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if "CONFIG_SR_MN_EN_MULTINET5_SINGLE_RECOGNITION_QUANT8" in models_string:
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models.append('mn5q8_en')
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elif "CONFIG_SR_MN_EN_MULTINET5_SINGLE_RECOGNITION" in models_string:
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models.append('mn5_en')
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elif "CONFIG_SR_MN_EN_MULTINET6_QUANT" in models_string:
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models.append('mn6_en')
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elif "CONFIG_SR_MN_EN_MULTINET7_QUANT" in models_string:
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models.append('mn7_en')
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if "MULTINET6" in models_string or "MULTINET7" in models_string:
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models.append('fst')
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for item in models:
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shutil.copytree(model_path + '/multinet_model/' + item, target_path+'/'+item)
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def copy_nsnet_from_sdkconfig(model_path, sdkconfig_path, target_path):
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"""
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Copy nsnet model from model_path to target_path based on sdkconfig
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"""
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with io.open(sdkconfig_path, "r") as f:
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models_string = ''
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for label in f:
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label = label.strip("\n")
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if 'CONFIG_SR_NSN' in label and label[0] != '#':
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models_string += label
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models = []
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if "CONFIG_SR_NSN_NSNET1" in models_string:
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models.append('nsnet1')
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if "CONFIG_SR_NSN_NSNET2" in models_string:
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models.append('nsnet2')
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for item in models:
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shutil.copytree(model_path + '/nsnet_model/' + item, target_path+'/'+item)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='Model generator tool')
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parser.add_argument('-d1', '--sdkconfig_path')
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parser.add_argument('-d2', '--model_path')
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parser.add_argument('-d3', '--build_path')
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args = parser.parse_args()
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sdkconfig_path = args.sdkconfig_path
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model_path = args.model_path + '/model'
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target_path = args.build_path + '/srmodels'
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image_file = "srmodels.bin"
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if os.path.exists(target_path):
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shutil.rmtree(target_path)
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os.makedirs(target_path)
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copy_multinet_from_sdkconfig(model_path, sdkconfig_path, target_path)
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copy_wakenet_from_sdkconfig(model_path, sdkconfig_path, target_path)
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copy_nsnet_from_sdkconfig(model_path, sdkconfig_path, target_path)
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pack_models(target_path, image_file)
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total_size = os.path.getsize(os.path.join(target_path, image_file))
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recommended_size = int(math.ceil(total_size/1024))
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print("Recommended model partition size: %dK" % (recommended_size))
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