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use new pycoral libraries

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This commit is contained in:
Blake Blackshear 2021-08-07 15:34:55 -05:00
parent 4818c08fe2
commit dc759a3e56
3 changed files with 17 additions and 21 deletions
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2
docker/Dockerfile.base
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@ -26,7 +26,7 @@ RUN apt-get -qq update \
&& APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn apt-key adv --fetch-keys https://packages.cloud.google.com/apt/doc/apt-key.gpg \ && APT_KEY_DONT_WARN_ON_DANGEROUS_USAGE=DontWarn apt-key adv --fetch-keys https://packages.cloud.google.com/apt/doc/apt-key.gpg \
&& echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" > /etc/apt/sources.list.d/coral-edgetpu.list \ && echo "deb https://packages.cloud.google.com/apt coral-edgetpu-stable main" > /etc/apt/sources.list.d/coral-edgetpu.list \
&& echo "libedgetpu1-max libedgetpu/accepted-eula select true" | debconf-set-selections \ && echo "libedgetpu1-max libedgetpu/accepted-eula select true" | debconf-set-selections \
&& apt-get -qq update && apt-get -qq install --no-install-recommends -y libedgetpu1-max python3-tflite-runtime \ && apt-get -qq update && apt-get -qq install --no-install-recommends -y libedgetpu1-max python3-tflite-runtime python3-pycoral \
&& rm -rf /var/lib/apt/lists/* /wheels \ && rm -rf /var/lib/apt/lists/* /wheels \
&& (apt-get autoremove -y; apt-get autoclean -y) && (apt-get autoremove -y; apt-get autoclean -y)

28
frigate/edgetpu.py
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@ -9,6 +9,7 @@ from abc import ABC, abstractmethod
from typing import Dict from typing import Dict
import numpy as np import numpy as np
from pycoral.adapters import detect
import tflite_runtime.interpreter as tflite import tflite_runtime.interpreter as tflite
from setproctitle import setproctitle from setproctitle import setproctitle
from tflite_runtime.interpreter import load_delegate from tflite_runtime.interpreter import load_delegate
@ -97,25 +98,20 @@ class LocalObjectDetector(ObjectDetector):
def detect_raw(self, tensor_input): def detect_raw(self, tensor_input):
self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input) self.interpreter.set_tensor(self.tensor_input_details[0]["index"], tensor_input)
self.interpreter.invoke() self.interpreter.invoke()
boxes = np.squeeze(
self.interpreter.get_tensor(self.tensor_output_details[0]["index"]) objects = detect.get_objects(self.interpreter, 0.4)
)
label_codes = np.squeeze(
self.interpreter.get_tensor(self.tensor_output_details[1]["index"])
)
scores = np.squeeze(
self.interpreter.get_tensor(self.tensor_output_details[2]["index"])
)
detections = np.zeros((20, 6), np.float32) detections = np.zeros((20, 6), np.float32)
for i, score in enumerate(scores): for i, obj in enumerate(objects):
if i == 20:
break
detections[i] = [ detections[i] = [
label_codes[i], obj.id,
score, obj.score,
boxes[i][0], obj.bbox.ymin,
boxes[i][1], obj.bbox.xmin,
boxes[i][2], obj.bbox.ymax,
boxes[i][3], obj.bbox.xmax,
] ]
return detections return detections

8
frigate/video.py
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@ -404,10 +404,10 @@ def detect(
for d in region_detections: for d in region_detections:
box = d[2] box = d[2]
size = region[2] - region[0] size = region[2] - region[0]
x_min = int((box[1] * size) + region[0]) x_min = int((box[1]) + region[0])
y_min = int((box[0] * size) + region[1]) y_min = int((box[0]) + region[1])
x_max = int((box[3] * size) + region[0]) x_max = int((box[3]) + region[0])
y_max = int((box[2] * size) + region[1]) y_max = int((box[2]) + region[1])
det = ( det = (
d[0], d[0],
d[1], d[1],