blakeblackshear.frigate/frigate/detectors/plugins/rknn.py
Blake Blackshear 14235c42b9
Remove all AGPL licensed YOLO references from Frigate (#10717)
* Remove yolov8 support from Frigate

* Remove yolov8 from dev

* Remove builds

* Formatting and remove yolov5

* Fix lint

* remove models download

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
2024-03-30 05:46:17 -05:00

119 lines
3.8 KiB
Python

import logging
import os.path
from typing import Literal
try:
from hide_warnings import hide_warnings
except: # noqa: E722
def hide_warnings(func):
pass
from pydantic import Field
from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig
logger = logging.getLogger(__name__)
DETECTOR_KEY = "rknn"
supported_socs = ["rk3562", "rk3566", "rk3568", "rk3588"]
class RknnDetectorConfig(BaseDetectorConfig):
type: Literal[DETECTOR_KEY]
core_mask: int = Field(default=0, ge=0, le=7, title="Core mask for NPU.")
class Rknn(DetectionApi):
type_key = DETECTOR_KEY
def __init__(self, config: RknnDetectorConfig):
# find out SoC
try:
with open("/proc/device-tree/compatible") as file:
soc = file.read().split(",")[-1].strip("\x00")
except FileNotFoundError:
logger.error("Make sure to run docker in privileged mode.")
raise Exception("Make sure to run docker in privileged mode.")
if soc not in supported_socs:
logger.error(
"Your SoC is not supported. Your SoC is: {}. Currently these SoCs are supported: {}.".format(
soc, supported_socs
)
)
raise Exception(
"Your SoC is not supported. Your SoC is: {}. Currently these SoCs are supported: {}.".format(
soc, supported_socs
)
)
if not os.path.isfile("/usr/lib/librknnrt.so"):
if "rk356" in soc:
os.rename("/usr/lib/librknnrt_rk356x.so", "/usr/lib/librknnrt.so")
elif "rk3588" in soc:
os.rename("/usr/lib/librknnrt_rk3588.so", "/usr/lib/librknnrt.so")
self.core_mask = config.core_mask
self.height = config.model.height
self.width = config.model.width
if True:
os.makedirs("/config/model_cache/rknn", exist_ok=True)
if (config.model.width != 320) or (config.model.height != 320):
logger.error(
"Make sure to set the model width and height to 320 in your config.yml."
)
raise Exception(
"Make sure to set the model width and height to 320 in your config.yml."
)
if config.model.input_pixel_format != "bgr":
logger.error(
'Make sure to set the model input_pixel_format to "bgr" in your config.yml.'
)
raise Exception(
'Make sure to set the model input_pixel_format to "bgr" in your config.yml.'
)
if config.model.input_tensor != "nhwc":
logger.error(
'Make sure to set the model input_tensor to "nhwc" in your config.yml.'
)
raise Exception(
'Make sure to set the model input_tensor to "nhwc" in your config.yml.'
)
from rknnlite.api import RKNNLite
self.rknn = RKNNLite(verbose=False)
if self.rknn.load_rknn(self.model_path) != 0:
logger.error("Error initializing rknn model.")
if self.rknn.init_runtime(core_mask=self.core_mask) != 0:
logger.error(
"Error initializing rknn runtime. Do you run docker in privileged mode?"
)
raise Exception(
"RKNN does not currently support any models. Please see the docs for more info."
)
def __del__(self):
self.rknn.release()
@hide_warnings
def inference(self, tensor_input):
return self.rknn.inference(inputs=tensor_input)
def detect_raw(self, tensor_input):
output = self.inference(
[
tensor_input,
]
)
return self.postprocess(output[0])