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Move to onnx format for rknn

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This commit is contained in:
Nicolas Mowen 2025-10-07 11:37:32 -06:00
parent a9942c9d6d
commit b0e84327b0
1 changed files with 28 additions and 4 deletions
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32
frigate/util/rknn_converter.py
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@ -14,7 +14,7 @@ logger = logging.getLogger(__name__)
MODEL_TYPE_CONFIGS = { MODEL_TYPE_CONFIGS = {
"yolo-generic": { "yolo-generic": {
"mean_values": [[0, 0, 0]], "mean_values": [[0, 0, 0]],
"std_values": [[255, 255, 255]], "std_values": [[1, 1, 1]],
"target_platform": None, # Will be set dynamically "target_platform": None, # Will be set dynamically
}, },
"yolonas": { "yolonas": {
@ -179,6 +179,22 @@ def convert_onnx_to_rknn(
config = MODEL_TYPE_CONFIGS[model_type].copy() config = MODEL_TYPE_CONFIGS[model_type].copy()
config["target_platform"] = soc config["target_platform"] = soc
# RKNN toolkit requires .onnx extension, create temporary copy if needed
temp_onnx_path = None
onnx_model_path = onnx_path
if not onnx_path.endswith(".onnx"):
import shutil
temp_onnx_path = f"{onnx_path}.onnx"
logger.debug(f"Creating temporary ONNX copy: {temp_onnx_path}")
try:
shutil.copy2(onnx_path, temp_onnx_path)
onnx_model_path = temp_onnx_path
except Exception as e:
logger.error(f"Failed to create temporary ONNX copy: {e}")
return False
try: try:
from rknn.api import RKNN # type: ignore from rknn.api import RKNN # type: ignore
@ -188,18 +204,18 @@ def convert_onnx_to_rknn(
if model_type == "jina-clip-v1-vision": if model_type == "jina-clip-v1-vision":
load_output = rknn.load_onnx( load_output = rknn.load_onnx(
model=onnx_path, model=onnx_model_path,
inputs=["pixel_values"], inputs=["pixel_values"],
input_size_list=[[1, 3, 224, 224]], input_size_list=[[1, 3, 224, 224]],
) )
elif model_type == "arcface-r100": elif model_type == "arcface-r100":
load_output = rknn.load_onnx( load_output = rknn.load_onnx(
model=onnx_path, model=onnx_model_path,
inputs=["data"], inputs=["data"],
input_size_list=[[1, 3, 112, 112]], input_size_list=[[1, 3, 112, 112]],
) )
else: else:
load_output = rknn.load_onnx(model=onnx_path) load_output = rknn.load_onnx(model=onnx_model_path)
if load_output != 0: if load_output != 0:
logger.error("Failed to load ONNX model") logger.error("Failed to load ONNX model")
@ -219,6 +235,14 @@ def convert_onnx_to_rknn(
except Exception as e: except Exception as e:
logger.error(f"Error during RKNN conversion: {e}") logger.error(f"Error during RKNN conversion: {e}")
return False return False
finally:
# Clean up temporary file if created
if temp_onnx_path and os.path.exists(temp_onnx_path):
try:
os.remove(temp_onnx_path)
logger.debug(f"Removed temporary ONNX file: {temp_onnx_path}")
except Exception as e:
logger.warning(f"Failed to remove temporary ONNX file: {e}")
def cleanup_stale_lock(lock_file_path: Path) -> bool: def cleanup_stale_lock(lock_file_path: Path) -> bool: