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exclude yolonas from image

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This commit is contained in:
MarcA711 2024-05-20 19:37:06 +00:00
parent cb9c097761
commit e53644d81a
3 changed files with 33 additions and 17 deletions
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6
docker/rockchip/Dockerfile
View File

@ -20,12 +20,6 @@ COPY --from=rootfs / /
ADD https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/librknnrt.so /usr/lib/ ADD https://github.com/MarcA711/rknn-toolkit2/releases/download/v2.0.0/librknnrt.so /usr/lib/
ADD https://github.com/MarcA711/rknn-models/releases/download/v2.0.0/deci-fp16-yolonas_s-rk3562-v2.0.0-1.rknn /models/
ADD https://github.com/MarcA711/rknn-models/releases/download/v2.0.0/deci-fp16-yolonas_s-rk3566-v2.0.0-1.rknn /models/
ADD https://github.com/MarcA711/rknn-models/releases/download/v2.0.0/deci-fp16-yolonas_s-rk3568-v2.0.0-1.rknn /models/
ADD https://github.com/MarcA711/rknn-models/releases/download/v2.0.0/deci-fp16-yolonas_s-rk3576-v2.0.0-1.rknn /models/
ADD https://github.com/MarcA711/rknn-models/releases/download/v2.0.0/deci-fp16-yolonas_s-rk3588-v2.0.0-1.rknn /models/
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffmpeg RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffmpeg
RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffprobe RUN rm -rf /usr/lib/btbn-ffmpeg/bin/ffprobe
ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-3/ffmpeg /usr/lib/btbn-ffmpeg/bin/ ADD --chmod=111 https://github.com/MarcA711/Rockchip-FFmpeg-Builds/releases/download/6.1-3/ffmpeg /usr/lib/btbn-ffmpeg/bin/

7
docs/docs/configuration/object_detectors.md
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@ -376,11 +376,16 @@ model: # required
input_pixel_format: bgr # required input_pixel_format: bgr # required
# shape of detection frame # shape of detection frame
input_tensor: nhwc input_tensor: nhwc
model_type: yolonas # required
``` ```
### Choosing a model ### Choosing a model
:::warning
yolo-nas models use weights from DeciAI. These weights are subject to their license and can't be used commercially. For more information, see: https://docs.deci.ai/super-gradients/latest/LICENSE.YOLONAS.html
:::
The inference time was determined on a rk3588 with 3 NPU cores. The inference time was determined on a rk3588 with 3 NPU cores.
| Model | Size in mb | Inference time in ms | | Model | Size in mb | Inference time in ms |

37
frigate/detectors/plugins/rknn.py
View File

@ -7,7 +7,7 @@ from typing import Literal
from pydantic import Field from pydantic import Field
from frigate.detectors.detection_api import DetectionApi from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig from frigate.detectors.detector_config import BaseDetectorConfig, ModelTypeEnum
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -15,9 +15,9 @@ DETECTOR_KEY = "rknn"
supported_socs = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"] supported_socs = ["rk3562", "rk3566", "rk3568", "rk3576", "rk3588"]
supported_models = ["^deci-fp16-yolonas_[sml]$"] supported_models = {ModelTypeEnum.yolonas: "^deci-fp16-yolonas_[sml]$"}
default_model = "deci-fp16-yolonas_s" # default_model = "deci-fp16-yolonas_s"
model_chache_dir = "/config/model_cache/rknn_cache/" model_chache_dir = "/config/model_cache/rknn_cache/"
@ -40,6 +40,16 @@ class Rknn(DetectionApi):
model_props = self.parse_model_input(config.model.path, soc) model_props = self.parse_model_input(config.model.path, soc)
if model_props["preset"]:
config.model.model_type = model_props["model_type"]
if model_props["model_type"] == ModelTypeEnum.yolonas:
logger.info("""
You are using yolo-nas with weights from DeciAI.
These weights are subject to their license and can't be used commercially.
For more information, see: https://docs.deci.ai/super-gradients/latest/LICENSE.YOLONAS.html
""")
from rknnlite.api import RKNNLite from rknnlite.api import RKNNLite
self.rknn = RKNNLite(verbose=False) self.rknn = RKNNLite(verbose=False)
@ -91,16 +101,23 @@ class Rknn(DetectionApi):
Full name could be: default-fp16-yolonas_s-rk3588-v2.0.0-1.rknn Full name could be: default-fp16-yolonas_s-rk3588-v2.0.0-1.rknn
""" """
if any(re.match(pattern, model_path) for pattern in supported_models): model_matched = False
for model_type, pattern in supported_models.items():
if re.match(pattern, model_path):
model_matched = True
model_props["model_type"] = model_type
if model_matched:
model_props["filename"] = model_path + f"-{soc}-v2.0.0-1.rknn" model_props["filename"] = model_path + f"-{soc}-v2.0.0-1.rknn"
if model_path == default_model: # if model_path == default_model:
model_props["path"] = "/models/" + model_props["filename"] # model_props["path"] = "/models/" + model_props["filename"]
else: # else:
model_props["path"] = model_chache_dir + model_props["filename"] model_props["path"] = model_chache_dir + model_props["filename"]
if not os.path.isfile(model_props["path"]): if not os.path.isfile(model_props["path"]):
self.download_model(model_props["filename"]) self.download_model(model_props["filename"])
else: else:
supported_models_str = ", ".join( supported_models_str = ", ".join(
model[1:-1] for model in supported_models model[1:-1] for model in supported_models