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…arning updates the model
README.md
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| ##### Run on AMD node with a connected Coral USB Accelerator with Adaptive Learning Support | ||
| Currently Smart Social Distancing supports Adaptive Learning framework on X86 nodes with connected USB TPU. for more information about Adaptive Learning visit [this page](https://github.com/neuralet/neuralet/tree/master/applications/adaptive-learning) |
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| Currently Smart Social Distancing supports Adaptive Learning framework on X86 nodes with connected USB TPU. for more information about Adaptive Learning visit [this page](https://github.com/neuralet/neuralet/tree/master/applications/adaptive-learning) | |
| Currently Smart Social Distancing supports Adaptive Learning framework on X86 nodes with connected USB TPU. For more information about Adaptive Learning visit [this page](https://github.com/neuralet/neuralet/tree/master/applications/adaptive-learning) |
| import threading | ||
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| class ConfigEngine: |
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Can't we reuse the ConfigEngine from libs/ConfigEngine.py here?
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Yeah, thanks for suggestion. Done.
start_services_adaptive.bash
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| bash /repo/sample_startup.bash $CONFIG & | ||
| bash /repo/update_model.bash $CONFIG & | ||
| #trap "echo exitting because the model name is not compatible with adaptive learning.>&2;kill $(jobs -p)" SIGUSR1 |
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I guess you can remove this comment with the if above
update_model.bash
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| fi | ||
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| response=$(curl 0.0.0.0:8000/process-video-cfg) |
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This endpoint has recently been renamed to start-process-video
adaptive-learning/README.md
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| ### Clone Neuralet Repository | ||
| Make sure you have the prerequisites and then clone this repository to your local system by running this command: | ||
| ``` | ||
| git clone https://github.com/neuralet/neuralet.git |
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I saw you added several files for adaptive learning. Is it still necessary to clone from neuralet/neuralet?
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No, it was just the copy of the original README, I changed it and referred to the original one for more details.
README.md
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| ##### Run on AMD node with a connected Coral USB Accelerator with Adaptive Learning Support | ||
| Currently Smart Social Distancing supports Adaptive Learning framework on X86 nodes with connected USB TPU. for more information about Adaptive Learning visit [this page](https://github.com/neuralet/neuralet/tree/master/applications/adaptive-learning) | ||
| Important notes: | ||
| 1. you must install [Docker Compose](https://github.com/docker/compose) to be able to use Adaptive Learning. |
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| 1. you must install [Docker Compose](https://github.com/docker/compose) to be able to use Adaptive Learning. | |
| 1. You must install [Docker Compose](https://github.com/docker/compose) to be able to use Adaptive Learning. |
README.md
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| ``` | ||
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| ##### Run on AMD node with a connected Coral USB Accelerator with Adaptive Learning Support | ||
| Currently Smart Social Distancing supports Adaptive Learning framework on X86 nodes with connected USB TPU. for more information about Adaptive Learning visit [this page](https://github.com/neuralet/neuralet/tree/master/applications/adaptive-learning) |
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Is https://github.com/neuralet/neuralet/tree/master/applications/adaptive-learning the same README than the one uploaded in adaptive-learning/README.md, if so please link to the smart-social-distance one
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I linked to the original code base in smart-social-distancing one since the original one is a general solution and smart-social-distancing is just a use case. Thanks.
config-coral.ini
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| #wether repeat the video processing when video reached to its final frame or not. | ||
| Repeat = false |
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| #wether repeat the video processing when video reached to its final frame or not. | |
| Repeat = false | |
| # Whether to loop the video processing when video reached to its final frame or not. | |
| Repeat = false |
This config allows for starting all over the video once it's finished? Could we change the name of the config to something like LoopVideoFile. Something that's clear that affects only when consuming a video file after it finishes. And not a camera
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Yeah, you are right. Done
libs/distancing.py
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| frame_num += 1 | ||
| if frame_num % 100 == 1: | ||
| logger.info(f'processed frame {frame_num} for {video_uri}') | ||
| if self.repeat == 'true' and frame_num % total_frames == 0: |
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I think that the repeat parameter should be a boolean and init it using the function get_boolean from the config_engine.
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Thanks. Done.
add Adaptive Learning support for USB TPU.
for more information about Adaptive Learning visit here