#
coral
Here are 82 public repositories matching this topic...
Self-hosted NVR with object detection
rtsp
surveillance
tensorflow
ip-camera
nvr
cuda
motion-detection
yolo
object-detection
hardware-acceleration
hacktoberfest
darknet
coral
network-video-capture
google-coral
edgetpu
network-video-recorder
viseron
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Jun 24, 2022 - Python
Object detection for video surveillance
python
mqtt
video
stream
camera
ffmpeg
surveillance
gpu
detection
realtime
cuda
ip
mpegts
hardware-acceleration
zones
homeassistant
coral
tensorrt
tensrflow
person-detector
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Jan 14, 2022 - Python
Dual Edge TPU Adapter to use it on a system with single PCIe port on m.2 A/B/E/M slot
home-assistant
m2
coral
tpu
tensorflow-lite
tpu-benchmarks
tpu-acceleration
edge-ai
edgetpu
edge-tpu
m2-module
coral-tpu
pcie-card
pcie-interface
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Feb 15, 2022
TensorFlow Lite, Coral Edge TPU samples (Python/C++, Raspberry Pi/Windows/Linux).
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Jul 8, 2022 - Python
Offers a set of tools that create Granite UI authoring interfaces for Adobe Experience Manager components from Java code. This is a comprehensive solution that makes different widgets work in a coordinated manner, provides greater interactivity in AEM dialogs, and introduces additional features (customizable data lists, options selection, etc.)
java
maven
cq
granite
hacktoberfest
coral
wcm
autogenerate
aem64
aem65
aemaacs
touchui-dialogs
aem-component
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Jul 8, 2022 - Java
ROS package for Coral Edge TPU USB Accelerator
training
ros
face-detection
object-detection
human-pose-estimation
hacktoberfest
semantic-segmentation
coral
edgetpu
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Jun 23, 2022 - Python
This is a PyTorch implementation of the Unsupervised Domain Adaptation method proposed in the paper Deep CORAL: Correlation Alignment for Deep Domain Adaptation. Baochen Sun and Kate Saenko (ECCV 2016).
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Oct 12, 2018 - Python
Docker with Raspbian, SSH and the Coral USB Edge TPU libraries.
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Aug 23, 2021 - Dockerfile
Cat with prey detection on Raspberry Pi. Lock cat pet flap if prey is detected. Object detection implemented in TFLite with ImageNet v1 SSD. Inference on EdgeTPU (Google Coral USB). Stores images on AWS S3 and sends notifications to iOS device.
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Aug 15, 2021 - Python
Chapter 11: Transfer Learning/Domain Adaptation
nlp
sentiment-analysis
word-embeddings
keras
cnn
transfer-learning
maximum-mean-discrepancy
coral
domain-adaptation
glove-embeddings
central-moment-discrepancy
stacked-autoencoder
stacked-denoising-autoencoders
adversarial-training
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Jul 23, 2019 - Jupyter Notebook
Source code (Python, Node.js and Java) for a demo we built which has been shown at a number of conferences, including IoT Solutions World Congress in Barcelona, Google Cloud Next 2019 and Google I/O 2019. Using the Coral Dev Board we show incredible fast machine learning on the edge with minimal power consumption.
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Jun 25, 2022 - JavaScript
Node.js framework to create REST API with express and mongoose models
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Apr 27, 2022 - JavaScript
Raspberry Pi Supplement to Coral Edge TPU Demo
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Dec 22, 2019 - Python
some scripts I used to test Google's Edge TPU
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May 31, 2019 - Python
Authoring extension for the Adobe AEM Sites platform featuring live collaboration for content editors.
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Jun 16, 2021 - Java
TPU accelerated traffic lane segmentation engine for your Raspberry Pi
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Nov 6, 2021 - Python
R package for dynamic bioenergetic modeling of coral-Symbiodinium symbioses
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Mar 23, 2021 - R
[ Programming language ] - built in Golang and run in CVM. (WIP)
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Jun 21, 2022 - Go
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Oct 21, 2019 - Python
use edgetpu_compiler from anywhere with docker
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May 3, 2020 - Dockerfile
This work consists of designing a miniature autonomous car that can follow a road, detect signalisations and obstacles.
python
car
raspberry-pi
machine-learning
deep-learning
neural-network
tensorflow
raspberrypi
python3
autonomous-car
self-driving-car
autonomous-driving
autonomous-vehicles
coral
self-driving-cars
picamera
raspberry-pi-4
coral-tpu
usb-accelerator
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Mar 23, 2021 - Python
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Overview
Tulip's V2 Vaults idl is around ~263kb on disk. When attempting to initialize an idl account for this, the default doubling of size for future-proofing against increasingly larger idl sizes has the potential to attempt to create an idl with a size larger than the maximum allowed size during reallocation, which will cause a failure: