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[RKNPU2] Update quantitative model (#879)

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* 对RKNPU2后端进行修改，当模型为非量化模型时，不在NPU执行normalize操作，当模型为量化模型时，在NUP上执行normalize操作

* 更新RKNPU2框架，输出数据的数据类型统一返回fp32类型

* 更新scrfd，拆分disable_normalize和disable_permute

* 更新scrfd代码，支持量化

* 更新scrfd python example代码

* 更新模型转换代码，支持量化模型

* 更新文档

* 按照要求修改

* 按照要求修改

* 修正模型转换文档

* 更新一下转换脚本
This commit is contained in:
Zheng_Bicheng
2022-12-19 13:58:43 +08:00
committed by GitHub
parent 383887dede
commit dc13eb7049
18 changed files with 92 additions and 148 deletions
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29
tools/rknpu2/export.py
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@@ -21,6 +21,7 @@ def get_config():
parser = argparse.ArgumentParser()
parser.add_argument("--verbose", default=True, help="rknntoolkit verbose")
parser.add_argument("--config_path")
parser.add_argument("--target_platform")
args = parser.parse_args()
return args
@@ -34,30 +35,19 @@ if __name__ == "__main__":
model = RKNN(config.verbose)
# Config
if yaml_config["normalize"] == "None":
model.config(target_platform=yaml_config["target_platform"])
else:
mean_values = [[256 * mean for mean in mean_ls]
for mean_ls in yaml_config["normalize"]["mean"]]
std_values = [[256 * std for std in std_ls]
for std_ls in yaml_config["normalize"]["std"]]
model.config(
mean_values=mean_values,
std_values=std_values,
target_platform=yaml_config["target_platform"])
mean_values = yaml_config["mean"]
std_values = yaml_config["std"]
model.config(mean_values=mean_values, std_values=std_values, target_platform=config.target_platform)
# Load ONNX model
print(type(yaml_config["outputs"]))
print("yaml_config[\"outputs\"] = ", yaml_config["outputs"])
if yaml_config["outputs"] == "None":
if yaml_config["outputs_nodes"] is None:
ret = model.load_onnx(model=yaml_config["model_path"])
else:
ret = model.load_onnx(
model=yaml_config["model_path"], outputs=yaml_config["outputs"])
ret = model.load_onnx(model=yaml_config["model_path"], outputs=yaml_config["outputs_nodes"])
assert ret == 0, "Load model failed!"
# Build model
ret = model.build(do_quantization=None)
ret = model.build(do_quantization=yaml_config["do_quantization"], dataset=yaml_config["dataset"])
assert ret == 0, "Build model failed!"
# Init Runtime
@@ -69,9 +59,8 @@ if __name__ == "__main__":
os.mkdir(yaml_config["output_folder"])
model_base_name = os.path.basename(yaml_config["model_path"]).split(".")[0]
model_device_name = yaml_config["target_platform"].lower()
model_device_name = config.target_platform.lower()
model_save_name = model_base_name + "_" + model_device_name + ".rknn"
ret = model.export_rknn(
os.path.join(yaml_config["output_folder"], model_save_name))
ret = model.export_rknn(os.path.join(yaml_config["output_folder"], model_save_name))
assert ret == 0, "Export rknn model failed!"
print("Export OK!")