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predict: make models a separate download

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This commit is contained in:
Koushik Dutta
2023-03-16 23:29:02 -07:00
parent 6ba3386157
commit 2bce019677
10 changed files with 25 additions and 56 deletions
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20
plugins/coreml/download_models.sh
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@@ -1,20 +0,0 @@
#!/bin/sh
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
rm -rf all_models
mkdir -p all_models
cd all_models
wget https://github.com/koush/coreml-survival-guide/raw/master/MobileNetV2%2BSSDLite/ObjectDetection/ObjectDetection/MobileNetV2_SSDLite.mlmodel
wget https://raw.githubusercontent.com/koush/coreml-survival-guide/master/MobileNetV2%2BSSDLite/coco_labels.txt

1
plugins/coreml/fs/MobileNetV2_SSDLite.mlmodel
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@@ -1 +0,0 @@
../all_models/MobileNetV2_SSDLite.mlmodel

1
plugins/coreml/fs/coco_labels.txt
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@@ -1 +0,0 @@
../all_models/coco_labels.txt

9
plugins/coreml/src/coreml/__init__.py
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@@ -29,16 +29,17 @@ class CoreMLPlugin(PredictPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.Set
def __init__(self, nativeId: str | None = None):
super().__init__(MIME_TYPE, nativeId=nativeId)
modelPath = os.path.join(os.environ['SCRYPTED_PLUGIN_VOLUME'], 'zip', 'unzipped', 'fs', 'MobileNetV2_SSDLite.mlmodel')
self.model = ct.models.MLModel(modelPath)
labelsFile = self.downloadFile('https://raw.githubusercontent.com/koush/coreml-survival-guide/master/MobileNetV2%2BSSDLite/coco_labels.txt', 'coco_labels.txt')
modelFile = self.downloadFile('https://github.com/koush/coreml-survival-guide/raw/master/MobileNetV2%2BSSDLite/ObjectDetection/ObjectDetection/MobileNetV2_SSDLite.mlmodel', 'MobileNetV2_SSDLite.mlmodel')
self.model = ct.models.MLModel(modelFile)
self.modelspec = self.model.get_spec()
self.inputdesc = self.modelspec.description.input[0]
self.inputheight = self.inputdesc.type.imageType.height
self.inputwidth = self.inputdesc.type.imageType.width
labels_contents = scrypted_sdk.zip.open(
'fs/coco_labels.txt').read().decode('utf8')
labels_contents = open(labelsFile, 'r').read()
self.labels = parse_label_contents(labels_contents)
self.loop = asyncio.get_event_loop()

19
plugins/tensorflow-lite/download_models.sh
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@@ -1,19 +0,0 @@
#!/bin/sh
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
mkdir -p all_models
wget https://dl.google.com/coral/canned_models/all_models.tar.gz
tar -C all_models -xvzf all_models.tar.gz
rm -f all_models.tar.gz

1
plugins/tensorflow-lite/fs/coco_labels.txt
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@@ -1 +0,0 @@
../all_models/coco_labels.txt

1
plugins/tensorflow-lite/fs/mobilenet_ssd_v2_coco_quant_postprocess.tflite
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@@ -1 +0,0 @@
../all_models/mobilenet_ssd_v2_coco_quant_postprocess.tflite

1
plugins/tensorflow-lite/fs/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite
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@@ -1 +0,0 @@
../all_models/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite

13
plugins/tensorflow-lite/src/predict/__init__.py
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@@ -8,6 +8,8 @@ from typing import Any, List, Tuple, Mapping
import asyncio
import time
from .rectangle import Rectangle, intersect_area, intersect_rect, to_bounding_box, from_bounding_box, combine_rect
import urllib.request
import os
from detect import DetectionSession, DetectPlugin
@@ -126,6 +128,17 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.Set
loop = asyncio.get_event_loop()
loop.call_later(4 * 60 * 60, lambda: self.requestRestart())
def downloadFile(self, url: str, filename: str):
filesPath = os.path.join(os.environ['SCRYPTED_PLUGIN_VOLUME'], 'files')
fullpath = os.path.join(filesPath, filename)
if os.path.isfile(fullpath):
return fullpath
os.makedirs(filesPath, exist_ok=True)
tmp = fullpath + '.tmp'
urllib.request.urlretrieve(url, tmp)
os.rename(tmp, fullpath)
return fullpath
def getClasses(self) -> list[str]:
return list(self.labels.values())

15
plugins/tensorflow-lite/src/tflite/__init__.py
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@@ -40,8 +40,11 @@ class TensorFlowLitePlugin(PredictPlugin, scrypted_sdk.BufferConverter, scrypted
def __init__(self, nativeId: str | None = None):
super().__init__(MIME_TYPE, nativeId=nativeId)
labels_contents = scrypted_sdk.zip.open(
'fs/coco_labels.txt').read().decode('utf8')
tfliteFile = self.downloadFile('https://raw.githubusercontent.com/google-coral/test_data/master/ssd_mobilenet_v2_coco_quant_postprocess.tflite', 'ssd_mobilenet_v2_coco_quant_postprocess.tflite')
edgetpuFile = self.downloadFile('https://raw.githubusercontent.com/google-coral/test_data/master/ssd_mobilenet_v2_coco_quant_postprocess_edgetpu.tflite', 'ssd_mobilenet_v2_coco_quant_postprocess_edgetpu.tflite')
labelsFile = self.downloadFile('https://raw.githubusercontent.com/google-coral/test_data/master/coco_labels.txt', 'coco_labels.txt')
labels_contents = open(labelsFile, 'r').read()
self.labels = parse_label_contents(labels_contents)
self.interpreters = queue.Queue()
self.interpreter_count = 0
@@ -54,13 +57,11 @@ class TensorFlowLitePlugin(PredictPlugin, scrypted_sdk.BufferConverter, scrypted
self.edge_tpu_found = str(edge_tpus)
# todo co-compile
# https://coral.ai/docs/edgetpu/compiler/#co-compiling-multiple-models
model = scrypted_sdk.zip.open(
'fs/mobilenet_ssd_v2_coco_quant_postprocess_edgetpu.tflite').read()
# face_model = scrypted_sdk.zip.open(
# 'fs/mobilenet_ssd_v2_face_quant_postprocess.tflite').read()
for idx, edge_tpu in enumerate(edge_tpus):
try:
interpreter = make_interpreter(model, ":%s" % idx)
interpreter = make_interpreter(edgetpuFile, ":%s" % idx)
interpreter.allocate_tensors()
_, height, width, channels = interpreter.get_input_details()[
0]['shape']
@@ -77,11 +78,9 @@ class TensorFlowLitePlugin(PredictPlugin, scrypted_sdk.BufferConverter, scrypted
except Exception as e:
print('unable to use Coral Edge TPU', e)
self.edge_tpu_found = 'Edge TPU not found'
model = scrypted_sdk.zip.open(
'fs/mobilenet_ssd_v2_coco_quant_postprocess.tflite').read()
# face_model = scrypted_sdk.zip.open(
# 'fs/mobilenet_ssd_v2_face_quant_postprocess.tflite').read()
interpreter = tflite.Interpreter(model_content=model)
interpreter = tflite.Interpreter(model_path=tfliteFile)
interpreter.allocate_tensors()
_, height, width, channels = interpreter.get_input_details()[
0]['shape']