viseron
tensorflow-yolo-v3
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viseron | tensorflow-yolo-v3 | |
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13 | 3 | |
1,388 | 895 | |
- | - | |
9.0 | 0.0 | |
13 days ago | 11 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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viseron
- Viseron 2.2.0 - Self-hosted, local only NVR and AI Computer Vision software.
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PoE Camera Recommendations
I'm using 4 Dahua turret cameras, also setup exactly like u/o4b describes. Works flawlessly. While I'm also using Frigate, there's another similar piece of software called Viseron that I've just become aware of that looks similar. I can't speak for it at all as I'm very happy with Frigate, but if you're starting from nothing, you may as well consider which may work better for you.
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Viseron 2.0.0 - Self-hosted, local only NVR and AI Computer Vision software.
Check out the release notes: https://github.com/roflcoopter/viseron/releases/tag/v2.0.0
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surveillance station
Viseron
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Best self-hosteable NVR
I have been using zoneminder for years and love it. If you can actually get a tensorflow unit, Frigate can be good. Just heard about Viseron, and am looking at trying it. https://github.com/roflcoopter/viseron
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Have 16-camera Reolink NVR, looking for self-hosted person detection and notification solution
There is also: https://github.com/roflcoopter/viseron - which again, using mqtt. You would need to bridge it to Signal.
- Frigate without a coral? Worried about my CPU being hammered.
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Six-core CPUs finally overtake quad-core processors on Steam
I do love having my threadripper in my home docker server though. Home assistant, plex, viseron, etc. all love the available CPU.
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Indoor home security camera with privacy in mind
If not motioneye, there are a bunch of other free options. I run zoneminder - it should work there with filters to move clips from primary storage on a schedule. You could do it with this one + rclone as well: https://github.com/roflcoopter/viseron
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My wife and brother worked together to get me an RPi4 for Xmas! I'm so excited to throw HomeAssistant on it once we get home
viseron works pretty well for me with cpu only.
tensorflow-yolo-v3
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How to use custom model for flutter app?
I used yolov4 and trained model on my classes, then saved weights in file.weights. Now, I want to integrate that model into my flutter app. On firebase, there is an option to use a custom model but that requires uploading .tflite file. My question is how can I convert my trained model weights and upload them as .tflite so could be used in my app. I have tried following this https://github.com/mystic123/tensorflow-yolo-v3 but not success. I would appreciate your help in the conversion of .weights to .tflite or suggest of there is any other way round
- “ValueError: cannot reshape array of size 278540 into shape (256,128,3,3)” Conversion YOLOv3 .weights to .pb
What are some alternatives?
frigate - NVR with realtime local object detection for IP cameras
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
alpr-unconstrained - License Plate Detection and Recognition in Unconstrained Scenarios
edge-tpu-tiny-yolo - Run Tiny YOLO-v3 on Google's Edge TPU USB Accelerator.
moonfire-nvr - Moonfire NVR, a security camera network video recorder
keras-yolo3 - Training and Detecting Objects with YOLO3
OS-NVR - OS-NVR is a lightweight extensible CCTV system. Mirror of Codeberg.
yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0
os-nvr
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
frigate-hass-integration - Frigate integration for Home Assistant
tensorflow-lite-YOLOv3 - YOLOv3: convert .weights to .tflite format for tensorflow lite. Convert .weights to .pb format for tensorflow serving