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plugins: cleanup package sizes

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This commit is contained in:
Koushik Dutta
2022-01-21 23:59:38 -08:00
parent b6e7d270e0
commit dc5f4b4e9e
16 changed files with 56 additions and 100 deletions
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24
common/src/wrtc-convertors.ts
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@@ -5,16 +5,19 @@ import { listenZero } from "./listen-cluster";
import { ffmpegLogInitialOutput } from "./media-helpers";
let wrtc: any;
try {
wrtc = require('wrtc');
}
catch (e) {
console.warn('loading wrtc failed. trying @koush/wrtc fallback.');
wrtc = require('@koush/wrtc');
}
function initalizeWebRtc() {
if (wrtc)
return;
try {
wrtc = require('wrtc');
}
catch (e) {
console.warn('loading wrtc failed. trying @koush/wrtc fallback.');
wrtc = require('@koush/wrtc');
}
Object.assign(global, wrtc);
const { RTCVideoSource, RTCAudioSource } = wrtc.nonstandard;
Object.assign(global, wrtc);
}
interface RTCSession {
pc: RTCPeerConnection;
@@ -90,6 +93,7 @@ export function addBuiltins(console: Console, mediaManager: MediaManager) {
],
};
initalizeWebRtc();
const pc = new RTCPeerConnection(configuration);
const id = Math.random().toString();
const session: RTCSession = {
@@ -106,6 +110,8 @@ export function addBuiltins(console: Console, mediaManager: MediaManager) {
}
}
const { RTCVideoSource, RTCAudioSource } = wrtc.nonstandard;
const videoSource = new RTCVideoSource();
pc.addTrack(videoSource.createTrack());

4
plugins/core/package-lock.json generated
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@@ -1,12 +1,12 @@
{
"name": "@scrypted/core",
"version": "0.0.179",
"version": "0.0.181",
"lockfileVersion": 2,
"requires": true,
"packages": {
"": {
"name": "@scrypted/core",
"version": "0.0.179",
"version": "0.0.181",
"license": "Apache-2.0",
"dependencies": {
"@koush/wrtc": "^0.5.0",

2
plugins/core/package.json
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@@ -1,6 +1,6 @@
{
"name": "@scrypted/core",
"version": "0.0.179",
"version": "0.0.181",
"description": "Scrypted Core plugin. Provides the UI, websocket, and engine.io APIs.",
"author": "Scrypted",
"license": "Apache-2.0",

4
plugins/homekit/package-lock.json generated
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@@ -1,12 +1,12 @@
{
"name": "@scrypted/homekit",
"version": "0.0.171",
"version": "0.0.172",
"lockfileVersion": 2,
"requires": true,
"packages": {
"": {
"name": "@scrypted/homekit",
"version": "0.0.171",
"version": "0.0.172",
"dependencies": {
"hap-nodejs": "file:../../external/HAP-NodeJS",
"lodash": "^4.17.21",

2
plugins/homekit/package.json
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@@ -40,5 +40,5 @@
"@types/qrcode": "^1.4.1",
"@types/url-parse": "^1.4.3"
},
"version": "0.0.171"
"version": "0.0.172"
}

3
plugins/homekit/src/battery.ts
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@@ -1,6 +1,5 @@
import { Battery, ScryptedDevice, ScryptedInterface } from "@scrypted/sdk";
import { Accessory, Characteristic } from "./hap";
import { Battery as HAPBattery, BatteryLevel, StatusLowBattery } from "hap-nodejs/src/lib/definitions";
import { Battery as HAPBattery, StatusLowBattery, Accessory, Characteristic } from "./hap";
import { bindCharacteristic } from "./common";
export function maybeAddBatteryService(device: ScryptedDevice & Battery, accessory: Accessory) {

4
plugins/homekit/src/common.ts
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@@ -1,8 +1,6 @@
import { EventDetails, EventListener, EventListenerRegister, Refresh, ScryptedDevice, ScryptedDeviceType, ScryptedInterface } from '@scrypted/sdk';
import { CharacteristicEventTypes, WithUUID } from 'hap-nodejs';
import { Characteristic } from 'hap-nodejs/src';
import { Accessory, Service, SnapshotRequest } from './hap';
import { Accessory, Service, SnapshotRequest, Characteristic, CharacteristicEventTypes, WithUUID } from './hap';
export interface DummyDevice {
interfaces?: string[];

8
plugins/homekit/src/hap.ts
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@@ -1 +1,7 @@
export * from '../../../external/HAP-NodeJS/src/index';
export * from 'hap-nodejs/src/index';
export * from "hap-nodejs/src/lib/definitions";
export * from 'hap-nodejs/src/lib/util/eventedhttp';
export * from 'hap-nodejs/src/lib/definitions';
export * from 'hap-nodejs/src';
export * from 'hap-nodejs/src/lib/camera';
export * from 'hap-nodejs/src/lib/camera/RecordingManagement';

2
plugins/homekit/src/main.ts
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@@ -9,7 +9,7 @@ import { randomBytes } from 'crypto';
import qrcode from 'qrcode';
import packageJson from "../package.json";
import { randomPinCode } from './pincode';
import { EventedHTTPServer } from 'hap-nodejs/dist/lib/util/eventedhttp';
import { EventedHTTPServer } from './hap';
import { getHAPUUID, initializeHapStorage } from './hap-utils';
const { systemManager, deviceManager } = sdk;

7
plugins/homekit/src/types/camera.ts
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@@ -11,16 +11,13 @@ import { once } from 'events';
import debounce from 'lodash/debounce';
import { CameraRecordingDelegate } from '../hap';
import { AudioRecordingCodec, AudioRecordingCodecType, AudioRecordingSamplerate, CameraRecordingOptions } from 'hap-nodejs/src/lib/camera/RecordingManagement';
import { ffmpegLogInitialOutput } from '@scrypted/common/src/media-helpers';
import { RtpDemuxer } from '../rtp/rtp-demuxer';
import { HomeKitRtpSink, startRtpSink } from '../rtp/rtp-ffmpeg-input';
import { ContactSensor, OccupancySensor } from 'hap-nodejs/src/lib/definitions';
import { handleFragmentsRequests, iframeIntervalSeconds } from './camera/camera-recording';
import { createSnapshotHandler } from './camera/camera-snapshot';
import { evalRequest } from './camera/camera-transcode';
import { CharacteristicEventTypes, DataStreamConnection, Service, WithUUID } from 'hap-nodejs/src';
import { RecordingManagement } from 'hap-nodejs/src/lib/camera';
import { AudioRecordingCodec, AudioRecordingCodecType, AudioRecordingSamplerate, CameraRecordingOptions, RecordingManagement, OccupancySensor, CharacteristicEventTypes, DataStreamConnection, Service, WithUUID } from '../hap';
import { defaultObjectDetectionContactSensorTimeout } from '../camera-mixin';
import os from 'os';
@@ -204,7 +201,7 @@ addSupportedType({
video: {
},
}, selectedStream || {});
const bitrate = request.video.max_bit_rate * 1000;
const bitrate = 10000000;//request.video.max_bit_rate * 1000;
reconfigured.video.bitrate = bitrate;
device.setVideoStreamOptions(reconfigured);

4
plugins/homekit/src/types/camera/camera-recording.ts
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@@ -1,15 +1,13 @@
import { FFMpegInput, MotionSensor, ScryptedDevice, ScryptedMimeTypes, VideoCamera, AudioSensor, MediaStreamOptions } from '@scrypted/sdk'
import { H264Level, H264Profile } from '../../hap';
import net from 'net';
import sdk from '@scrypted/sdk';
import { AudioRecordingCodecType, AudioRecordingSamplerateValues, CameraRecordingConfiguration } from 'hap-nodejs/src/lib/camera/RecordingManagement';
import { AudioRecordingCodecType, AudioRecordingSamplerateValues, CameraRecordingConfiguration } from '../../hap';
import { FFMpegFragmentedMP4Session, startFFMPegFragmetedMP4Session } from '@scrypted/common/src/ffmpeg-mp4-parser-session';
import { evalRequest } from './camera-transcode';
import { parseFragmentedMP4 } from '@scrypted/common/src/stream-parser';
import { levelToFfmpeg, profileToFfmpeg } from './camera-utils';
const { log, mediaManager, deviceManager } = sdk;

3
plugins/homekit/src/types/doorbell.ts
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@@ -1,8 +1,7 @@
import { BinarySensor, ScryptedDevice, ScryptedDeviceType, ScryptedInterface } from '@scrypted/sdk'
import { ContactSensor, StatelessProgrammableSwitch } from 'hap-nodejs/src/lib/definitions';
import { Characteristic, CharacteristicEventTypes, CharacteristicGetCallback, Service, ContactSensor, StatelessProgrammableSwitch } from '../hap';
import { addSupportedType, bindCharacteristic, DummyDevice, HomeKitSession, supportedTypes } from '../common'
import { Characteristic, CharacteristicEventTypes, CharacteristicGetCallback, Service } from '../hap';
import { makeAccessory } from './common';
addSupportedType({

2
plugins/rtsp/src/rtsp.ts
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@@ -61,7 +61,7 @@ export class RtspCamera extends CameraBase<UrlMediaStreamOptions> {
// Note the trailing colon.
// issue: https://github.com/koush/scrypted/issues/134
const parsedUrl = url.parse(vso.url);
this.console.log('rtsp stream url', parsedUrl.toString());
this.console.log('rtsp stream url', vso.url);
const username = this.storage.getItem("username");
const password = this.storage.getItem("password");
if (username) {

10
plugins/tensorflow-lite/src/detect/__init__.py
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@@ -14,7 +14,7 @@ import time
import os
import binascii
from urllib.parse import urlparse
import multiprocessing
import threading
from pipeline import run_pipeline
from gi.repository import Gst
@@ -37,7 +37,7 @@ class PipelineValve:
allowPacketCounter: int
def __init__(self, gst, name) -> None:
self.allowPacketCounter = 1
self.mutex = multiprocessing.Lock()
self.mutex = threading.Lock()
valve = gst.get_by_name(name + "Valve")
self.pad = valve.get_static_pad("src")
self.name = name
@@ -91,7 +91,7 @@ class DetectionSession:
self.future = Future()
self.running = False
self.attached = False
self.mutex = multiprocessing.Lock()
self.mutex = threading.Lock()
self.valve: PipelineValve = None
self.last_sample = time.time()
@@ -120,7 +120,7 @@ class DetectPlugin(scrypted_sdk.ScryptedDeviceBase, ObjectDetection):
def __init__(self, nativeId: str | None = None):
super().__init__(nativeId=nativeId)
self.detection_sessions: Mapping[str, DetectionSession] = {}
self.session_mutex = multiprocessing.Lock()
self.session_mutex = threading.Lock()
def detection_event(self, detection_session: DetectionSession, detection_result: ObjectsDetected, event_buffer: bytes = None):
detection_result['detectionId'] = detection_session.id
@@ -211,7 +211,7 @@ class DetectPlugin(scrypted_sdk.ScryptedDeviceBase, ObjectDetection):
detection_session.future.add_done_callback(
lambda _: self.end_session(detection_session))
if detection_session and time.time() - detection_session.last_sample > 30:
if detection_session and time.time() - detection_session.last_sample > 30 and not mediaObject:
print('detection session has not received a sample in 30 seconds, terminating', detection_session.id)
ending = True

76
plugins/tensorflow-lite/src/tflite/__init__.py
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@@ -1,7 +1,6 @@
from __future__ import annotations
from scrypted_sdk.types import ObjectDetectionModel, ObjectDetectionResult, ObjectsDetected, Setting
from .third_party.sort import Sort
import multiprocessing
import threading
import io
from .common import *
from PIL import Image
@@ -12,17 +11,15 @@ from pycoral.utils.edgetpu import list_edge_tpus
from pycoral.utils.edgetpu import make_interpreter
import tflite_runtime.interpreter as tflite
import re
import numpy as np
import scrypted_sdk
from typing import Any, List
from detect import DetectionSession, DetectPlugin
class TrackerDetectionSession(DetectionSession):
class TensorFlowLiteSession(DetectionSession):
def __init__(self) -> None:
super().__init__()
self.tracker = Sort()
def parse_label_contents(contents: str):
@@ -57,7 +54,7 @@ class TensorFlowLitePlugin(DetectPlugin):
'fs/mobilenet_ssd_v2_coco_quant_postprocess.tflite').read()
self.interpreter = tflite.Interpreter(model_content=model)
self.interpreter.allocate_tensors()
self.mutex = multiprocessing.Lock()
self.mutex = threading.Lock()
async def getDetectionModel(self) -> ObjectDetectionModel:
_, height, width, channels = self.interpreter.get_input_details()[
@@ -79,58 +76,19 @@ class TensorFlowLitePlugin(DetectPlugin):
d['settings'] = [setting]
return d
def create_detection_result(self, objs, size, tracker: Sort = None, convert_to_src_size=None):
def create_detection_result(self, objs, size, convert_to_src_size=None):
detections: List[ObjectDetectionResult] = []
detection_result: ObjectsDetected = {}
detection_result['detections'] = detections
detection_result['inputDimensions'] = size
tracker_detections = []
for obj in objs:
element = []
element.append(obj.bbox.xmin)
element.append(obj.bbox.ymin)
element.append(obj.bbox.xmax)
element.append(obj.bbox.ymax)
element.append(obj.score)
tracker_detections.append(element)
tracker_detections = np.array(tracker_detections)
trdata = []
trackerFlag = False
if tracker and tracker_detections.any():
trdata = tracker.update(tracker_detections)
trackerFlag = True
if trackerFlag and (np.array(trdata)).size:
for td in trdata:
x0, y0, x1, y1, trackID = td[0].item(), td[1].item(
), td[2].item(), td[3].item(), td[4].item()
overlap = 0
for ob in objs:
dx0, dy0, dx1, dy1 = ob.bbox.xmin, ob.bbox.ymin, ob.bbox.xmax, ob.bbox.ymax
area = (min(dx1, x1)-max(dx0, x0)) * \
(min(dy1, y1)-max(dy0, y0))
if (area > overlap):
overlap = area
obj = ob
detection: ObjectDetectionResult = {}
detection['id'] = str(trackID)
detection['boundingBox'] = (
obj.bbox.xmin, obj.bbox.ymin, obj.bbox.xmax - obj.bbox.xmin, obj.bbox.ymax - obj.bbox.ymin)
detection['className'] = self.labels.get(obj.id, obj.id)
detection['score'] = obj.score
detections.append(detection)
else:
for obj in objs:
detection: ObjectDetectionResult = {}
detection['boundingBox'] = (
obj.bbox.xmin, obj.bbox.ymin, obj.bbox.xmax - obj.bbox.xmin, obj.bbox.ymax - obj.bbox.ymin)
detection['className'] = self.labels.get(obj.id, obj.id)
detection['score'] = obj.score
detections.append(detection)
detection: ObjectDetectionResult = {}
detection['boundingBox'] = (
obj.bbox.xmin, obj.bbox.ymin, obj.bbox.xmax - obj.bbox.xmin, obj.bbox.ymax - obj.bbox.ymin)
detection['className'] = self.labels.get(obj.id, obj.id)
detection['score'] = obj.score
detections.append(detection)
if convert_to_src_size:
detections = detection_result['detections']
@@ -155,29 +113,25 @@ class TensorFlowLitePlugin(DetectPlugin):
'score_threshold', score_threshold))
return score_threshold
def run_detection_jpeg(self, detection_session: TrackerDetectionSession, image_bytes: bytes, settings: Any) -> ObjectsDetected:
def run_detection_jpeg(self, detection_session: TensorFlowLiteSession, image_bytes: bytes, settings: Any) -> ObjectsDetected:
stream = io.BytesIO(image_bytes)
image = Image.open(stream)
_, scale = common.set_resized_input(
self.interpreter, image.size, lambda size: image.resize(size, Image.ANTIALIAS))
tracker = None
if detection_session:
tracker = detection_session.tracker
score_threshold = self.parse_settings(settings)
with self.mutex:
self.interpreter.invoke()
objs = detect.get_objects(
self.interpreter, score_threshold=score_threshold, image_scale=scale)
return self.create_detection_result(objs, image.size, tracker=tracker)
return self.create_detection_result(objs, image.size)
def get_detection_input_size(self, src_size):
return input_size(self.interpreter)
def run_detection_gstsample(self, detection_session: TrackerDetectionSession, gstsample, settings: Any, src_size, convert_to_src_size) -> ObjectsDetected:
def run_detection_gstsample(self, detection_session: TensorFlowLiteSession, gstsample, settings: Any, src_size, convert_to_src_size) -> ObjectsDetected:
score_threshold = self.parse_settings(settings)
gst_buffer = gstsample.get_buffer()
@@ -186,7 +140,7 @@ class TensorFlowLitePlugin(DetectPlugin):
objs = detect.get_objects(
self.interpreter, score_threshold=score_threshold)
return self.create_detection_result(objs, src_size, detection_session.tracker, convert_to_src_size)
return self.create_detection_result(objs, src_size, convert_to_src_size)
def create_detection_session(self):
return TrackerDetectionSession()
return TensorFlowLiteSession()

1
plugins/tensorflow-lite/src/tflite/third_party/sort/__init__.py vendored
View File

@@ -1 +0,0 @@
../../../../../../external/sort/sort.py