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Allow using full tensorflow in cpu/edgetpu detector plugins (#5611)

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It supports the same entrypoints, given that tflite is a small cut-out
of the big tensorflow picture.

This patch was created for downstream usage in nixpkgs, where we don't
have the tflite python package, but do have the full tensorflow package.
This commit is contained in:
Martin Weinelt 2023-03-03 23:44:17 +00:00 committed by GitHub
parent 42eaa13402
commit 161e7b3fd7
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2 changed files with 12 additions and 5 deletions
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8
frigate/detectors/plugins/cpu_tfl.py
View File

@ -5,7 +5,11 @@ from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig
from typing import Literal
from pydantic import Extra, Field
import tflite_runtime.interpreter as tflite
try:
from tflite_runtime.interpreter import Interpreter
except ModuleNotFoundError:
from tensorflow.lite.python.interpreter import Interpreter
logger = logging.getLogger(__name__)
@ -22,7 +26,7 @@ class CpuTfl(DetectionApi):
type_key = DETECTOR_KEY
def __init__(self, detector_config: CpuDetectorConfig):
self.interpreter = tflite.Interpreter(
self.interpreter = Interpreter(
model_path=detector_config.model.path or "/cpu_model.tflite",
num_threads=detector_config.num_threads or 3,
)

9
frigate/detectors/plugins/edgetpu_tfl.py
View File

@ -5,8 +5,11 @@ from frigate.detectors.detection_api import DetectionApi
from frigate.detectors.detector_config import BaseDetectorConfig
from typing import Literal
from pydantic import Extra, Field
import tflite_runtime.interpreter as tflite
from tflite_runtime.interpreter import load_delegate
try:
from tflite_runtime.interpreter import Interpreter, load_delegate
except ModuleNotFoundError:
from tensorflow.lite.python.interpreter import Interpreter, load_delegate
logger = logging.getLogger(__name__)
@ -33,7 +36,7 @@ class EdgeTpuTfl(DetectionApi):
logger.info(f"Attempting to load TPU as {device_config['device']}")
edge_tpu_delegate = load_delegate("libedgetpu.so.1.0", device_config)
logger.info("TPU found")
self.interpreter = tflite.Interpreter(
self.interpreter = Interpreter(
model_path=detector_config.model.path or "/edgetpu_model.tflite",
experimental_delegates=[edge_tpu_delegate],
)