Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

Last update: Dec 27, 2022

Overview

lacmus

The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork.

The project is being developed by a non-profit organization Liza Alert.

Demonstration

Picture 1

Picture 2

Video 1

See more examples.

Training data

You can download Lacmus Drone Dataset (LaDD) from mail.ru cloud

https://cloud.mail.ru/public/2k53/2bJVwYSa7

You also can download Lacmus version of Stenford Drone Dataset (SDD) from mail.ru cloud

https://cloud.mail.ru/public/4GKW/3FW26Sq77

Usage

Read more about training steps and atraining data at train documentation to learn how to train the model.

Pretrained models

The models are avalable here.

Partners

Comments

Пользовательская документация - работа с данными
Добавить в вики инструкцию по тому как добавлять данные в проект и как отправлять их на сервер.

Добавить инструкцию с тем как снимть данные для операторов БПЛА с перечнем поз.

enhancement documentation
opened by gosha20777 5
Dataset format + cropping
Класcы для работы с датасетом LADD ("подмножество" формата Pascal VOC).

чтение датасета (список изображений, чтение аннотаций к изображению)

формирование датасета (добавление изображений, формирование файла аннотаций, формирование файлов ImageSets)

Скрипт для формирования нового датасета путем нарезки изображений из имеющегося датасета. Новый датасет сохраняется в формате Pascal VOC и готов для обучения. Изображение нарезается прямоугольниками "по сетке".

настраиваются размеры итоговых изображений, размеры "нахлеста" изображений друг на друга

в датасет добавляется равное количество изображений с людьми и без людей (сбалансированный датасет)

выполняется параллельная обработка изображений для ускорения работы
opened by nvsit 4
docker image(GPU) failed to built

Hi! i've tried to build GPU-version of docker image on my ubuntu 16.04(nvidia 418.67, Cuda 10.1 and got this error in the end.

sudo docker build --file Dockerfile.gpu -t rescuer_la . Sending build context to Docker daemon 14.56MB Step 1/24 : FROM tensorflow/tensorflow:1.12.0-gpu-py3 ---> 413b9533f92a Step 2/24 : ENV DEBIAN_FRONTEND noninteractive ---> Using cache ---> 8a52f51116f2 Step 3/24 : RUN apt-get update -qq && apt-get install --no-install-recommends -y build-essential g++ git wget apt-transport-https curl cython libopenblas-base python3-numpy python3-scipy python3-h5py python3-yaml python3-pydot && apt-get clean && rm -rf /var/lib/apt/lists/* ---> Using cache ---> a545cb38439e Step 4/24 : RUN pip3 --no-cache-dir install -U numpy==1.13.3 ---> Using cache ---> 98d345ea0a28 Step 5/24 : ARG KERAS_VERSION=2.2.4 ---> Using cache ---> 7b09457df232 Step 6/24 : ENV KERAS_BACKEND=tensorflow ---> Using cache ---> 85a448c8d80b Step 7/24 : RUN pip3 --no-cache-dir install --no-dependencies git+https://github.com/fchollet/keras.git@${KERAS_VERSION} ---> Using cache ---> 1c91dbe3620b Step 8/24 : RUN python3 -c "import tensorflow; print(tensorflow.version)" && dpkg-query -l > /dpkg-query-l.txt && pip3 freeze > /pip3-freeze.txt ---> Running in 08e7f4469a36 Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in from tensorflow.python.pywrap_tensorflow_internal import * File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in _pywrap_tensorflow_internal = swig_import_helper() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description) File "/usr/lib/python3.5/imp.py", line 242, in load_module return load_dynamic(name, filename, file) File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic return _load(spec) ImportError: libcuda.so.1: cannot open shared object file: No such file or directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "", line 1, in File "/usr/local/lib/python3.5/dist-packages/tensorflow/init.py", line 24, in from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/init.py", line 49, in from tensorflow.python import pywrap_tensorflow File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 74, in raise ImportError(msg) ImportError: Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in from tensorflow.python.pywrap_tensorflow_internal import * File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in _pywrap_tensorflow_internal = swig_import_helper() File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description) File "/usr/lib/python3.5/imp.py", line 242, in load_module return load_dynamic(name, filename, file) File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic return _load(spec) ImportError: libcuda.so.1: cannot open shared object file: No such file or directory

Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/errors

for some common reasons and solutions. Include the entire stack trace above this error message when asking for help. The command '/bin/sh -c python3 -c "import tensorflow; print(tensorflow.version)" && dpkg-query -l > /dpkg-query-l.txt && pip3 freeze > /pip3-freeze.txt' returned a non-zero code: 1

opened by aprentis 3

CUDNN_STATUS_INTERNAL_ERROR

CUDNN_STATUS_INTERNAL_ERROR while loading the model

2021-04-05 20:44:46.086918: E tensorflow/stream_executor/cuda/cuda_dnn.cc:328] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2021-04-05 20:44:46.087682: E tensorflow/stream_executor/cuda/cuda_dnn.cc:328] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
[2021-04-05 20:44:46,090] ERROR in app: Exception on /image [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/flask/app.py", line 2447, in wsgi_app
    response = self.full_dispatch_request()
  File "/usr/local/lib/python3.6/dist-packages/flask/app.py", line 1952, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "/usr/local/lib/python3.6/dist-packages/flask/app.py", line 1821, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "/usr/local/lib/python3.6/dist-packages/flask/_compat.py", line 39, in reraise
    raise value
  File "/usr/local/lib/python3.6/dist-packages/flask/app.py", line 1950, in full_dispatch_request
    rv = self.dispatch_request()
  File "/usr/local/lib/python3.6/dist-packages/flask/app.py", line 1936, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "inference.py", line 132, in predict_image
    caption = run_detection_image(request.json['data'])
  File "inference.py", line 49, in run_detection_image
    boxes, scores, labels = model.predict_on_batch(np.expand_dims(image, axis=0))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py", line 1788, in predict_on_batch
    outputs = predict_function(iterator)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/def_function.py", line 780, in call
    result = self._call(*args, **kwds)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/def_function.py", line 814, in _call
    results = self._stateful_fn(*args, **kwds)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 2829, in call
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 1848, in _filtered_call
    cancellation_manager=cancellation_manager)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 1924, in _call_flat
    ctx, args, cancellation_manager=cancellation_manager))
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 550, in call
    ctx=ctx)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/execute.py", line 60, in quick_execute
    inputs, attrs, num_outputs)
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
  (0) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
     [[node retinanet-bbox/conv1/Conv2D (defined at inference.py:49) ]]
     [[retinanet-bbox/filtered_detections/map/while/body/_1/retinanet-bbox/filtered_detections/map/while/strided_slice_2/_32]]
  (1) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
     [[node retinanet-bbox/conv1/Conv2D (defined at inference.py:49) ]]
0 successful operations.
0 derived errors ignored. [Op:__inference_predict_function_7071]

Function call stack:
predict_function -> predict_function

Mon Apr  5 23:06:13 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.102.04   Driver Version: 450.102.04   CUDA Version: 11.0     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce MX230       Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   64C    P3    N/A /  N/A |    218MiB /  2002MiB |     22%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A       956      G   /usr/lib/xorg/Xorg                 95MiB |
|    0   N/A  N/A      1301      G   /usr/bin/gnome-shell              121MiB |
+-----------------------------------------------------------------------------+

docker version: Docker version 19.03.8, build afacb8b7f0

opened by gosha20777 2

Bug: Could not find registration proxy for IID: {ADD8BA80-002B-8F0F-00C04FD062}
Describe the bug Version - 0.3.2 os - Win10

при попытке загрузить директорию с файлами через USB выдает ошибку Сообщение программы:

Error Интерфейс не зарегистрирован Не удалось найти регистрацию прокси-сервера для IID: {ADD8BA80-002B-8F0F-00C04FD062}
bug
opened by Denaizer 2
Bug: Program crash with exit code 134
Describe the bug Program crashes with 134 status code when material.avalonia theme is installed.

To Reproduce Steps to reproduce the behavior:

Go to 'file - open directory'

Click on 'predict all' button

Open another directory with images (file - open directory)

Exuted with code 134

Desktop (please complete the following information):

OS: Ubuntu 19.04

CPU: Intel Core i7-6500U

GPU: GeForce GTX 950M

Additional context It seems to me that this is due to incorrect visualization errors at material.avalonia theme.
bug
opened by gosha20777 2
docker image(CPU) failed to start.

Hi, i`ve successfully built CPU image, but it failed to start with this error.

sudo docker run --rm -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=unix$DISPLAY --workdir=$(pwd) --volume="/home/$USER:/home/$USER" --volume="/etc/group:/etc/group:ro" --volume="/etc/passwd:/etc/passwd:ro" --volume="/etc/shadow:/etc/shadow:ro" --volume="/etc/sudoers.d:/etc/sudoers.d:ro" rescuer_la No protocol specified No protocol specified

Unhandled Exception: System.Exception: XOpenDisplay failed at Avalonia.X11.AvaloniaX11Platform.Initialize(X11PlatformOptions options) at Avalonia.Controls.AppBuilderBase1.Setup() at Avalonia.Controls.AppBuilderBase1.Start[TMainWindow](Func`1 dataContextProvider) at RescuerLaApp.Program.Main(String[] args) in /app/install/RescuerLaApp/Program.cs:line 14

opened by aprentis 2
Thread safe issue with visual_effect_generator

Bug description The visual_effect_generator, as all python generators, is not thread-safe. That can cause an exception when using several worker threads, especially within single process.

How to reproduce Enter the lacmus directory and run train.py with --workers > 1 but without --multiprocessing:

keras_retinanet/bin/train.py --backbone mobilenet_v3_small --no-snapshots --batch-size 8 --max-queue-size=10 --workers=8 --epoch 1 --steps 200 pascal ../../../data/ful

Actual result On one or another training step the process stops with an exception "ValueError: generator already executing"

Callstack: Traceback (most recent call last): File "keras_retinanet/bin/train.py", line 546, in main() File "keras_retinanet/bin/train.py", line 541, in main initial_epoch=args.initial_epoch File "/home/jupyter-kseniia/.local/lib/python3.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper return func(*args, **kwargs) File "/home/jupyter-kseniia/.local/lib/python3.7/site-packages/keras/engine/training.py", line 1732, in fit_generator initial_epoch=initial_epoch) File "/home/jupyter-kseniia/.local/lib/python3.7/site-packages/keras/engine/training_generator.py", line 185, in fit_generator generator_output = next(output_generator) File "/home/jupyter-kseniia/.local/lib/python3.7/site-packages/keras/utils/data_utils.py", line 625, in get six.reraise(*sys.exc_info()) File "/home/jupyter-kseniia/.conda/envs/lacmus-k/lib/python3.7/site-packages/six.py", line 703, in reraise raise value File "/home/jupyter-kseniia/.local/lib/python3.7/site-packages/keras/utils/data_utils.py", line 610, in get inputs = future.get(timeout=30) File "/home/jupyter-kseniia/.conda/envs/lacmus-k/lib/python3.7/multiprocessing/pool.py", line 657, in get raise self._value File "/home/jupyter-kseniia/.conda/envs/lacmus-k/lib/python3.7/multiprocessing/pool.py", line 121, in worker result = (True, func(*args, **kwds)) File "/home/jupyter-kseniia/.local/lib/python3.7/site-packages/keras/utils/data_utils.py", line 406, in get_index return _SHARED_SEQUENCES[uid][i] File "keras_retinanet/bin/../../keras_retinanet/preprocessing/generator.py", line 375, in getitem inputs, targets = self.compute_input_output(group) File "keras_retinanet/bin/../../keras_retinanet/preprocessing/generator.py", line 347, in compute_input_output image_group, annotations_group = self.random_visual_effect_group(image_group, annotations_group) File "keras_retinanet/bin/../../keras_retinanet/preprocessing/generator.py", line 212, in random_visual_effect_group image_group[index], annotations_group[index] File "keras_retinanet/bin/../../keras_retinanet/preprocessing/generator.py", line 195, in random_visual_effect_group_entry visual_effect = next(self.visual_effect_generator) ValueError: generator already executing terminate called without an active exception terminate called recursively Aborted (core dumped)
bug

opened by prickly-u 1
Fix readme logo and organization logo
Удалить лого Лиза Алерт из ридми.

Добавить лого lacmus

Выкинуть лого Лиза Алерт из организации lacmus foundation и заменить его на lacmus

добавить секцию partners в readme

добавить лого DTL, Сбер.Клауд, Liza Alert в партнёры.

bug documentation
opened by gosha20777 1

Bug: System.NullReferenceException throws while loading file

Version - 0.3.2 OS - Linux/Windows

На последнем и предпоследнем релизе есть плавающий глюк, систематику еще не выявил. При попытке загрузить с жесткого диска файлы программа падает с таким сообщением:

 Unhandled Exception: System.NullReferenceException: Object reference not set to an instance of an object.
   at RescuerLaApp.Models.Frame.<>c__DisplayClass38_0.<Load>b__0(Object o)
   in /home/user/files/projects/lacmus/RescuerLaApp/Models/Frame.cs:line 77
   at System.Threading.ExecutionContext.RunInternal(ExecutionContext executionContext, ContextCallback callback, Object state)
--- End of stack trace from previous location where exception was thrown ---
   at System.Threading.ThreadPoolWorkQueue.Dispatch()

От количества файлов это не зависит, битых файлов нет.

bug

opened by Denaizer 1

Feat: add fucnction to reset image back to 100% size

Пилоты очень просили доп. опцию - центрирования и возврата обработанной фотографии к 100%, т.к. при работе на трекпаде фото может "улетать" за пределы галактики.
enhancement

opened by Denaizer 1
Detections are of shape `(1, 200700, 6)` but decode_openvino_detections uses the wrong number of dims

https://github.com/lacmus-foundation/lacmus/blob/f1dd0da5fb1c04d12ad25e7f67b5dd2a98f595d4/cli_inference_openvino.py#L57

As seen here this is assuming 4 dims when output has 3.

opened by suvojit-0x55aa 1
Add Cutmix
Add cutmix generator for beter results. The cutmix generator can be useful for training models and achieving better results. This will help take existing models to a higher level of quality.

Resources that may be useful:

https://arxiv.org/abs/1905.04899 - the original article

https://github.com/clovaai/CutMix-PyTorch - a pytorch implementation

https://github.com/DevBruce/CutMixImageDataGenerator_For_Keras - keras implenentation (not compartable with retinanet)

enhancement
opened by gosha20777 0

Releases(2.5.0)

2.5.0(Aug 18, 2021)
openvino support

tf 2.4.x support

remove keras

Source code(tar.gz)
Source code(zip)
0.3.2(Nov 13, 2019)
Change log

update to latest avaloniaUI-0.9-preview6

fix critical bug with windows #48

fix multiple bugs with osx

fix multiple bugs Linux

better performance

windows fully supported

osx Catalina fully supported

add show and hide bounding box function

add favorites images

convert GPS tags to correct format (Google, Yandex comparable)

add material disign

Ussage

system requirements CPU support for Windows/Linux/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

Installation

CPU

install docker and docker service (and add user to docker group for linux)

unzip archive with your runtime

GPU

install docker and docker service (and add user to docker group for linux)

install nvidia-docker and run it

unzip archive with your runtime use runtime with -gpu suffix

Usage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux-gpu.zip(35.33 MB)
linux.zip(35.33 MB)
osx.zip(33.38 MB)
ubuntu16-gpu.zip(35.33 MB)
ubuntu16.zip(35.33 MB)
ubuntu18-gpu.zip(35.33 MB)
ubuntu18.zip(35.33 MB)
win10.zip(37.02 MB)
0.3.2-preview(Nov 8, 2019)
Change log

update to latest avaloniaUI-0.9-preview6

fix criticlal bug with windows #48

fix multiple bugs with osx

fix multiple bugs linux

better performance

windows fully supported

osx catalina fully supported

Ussage

system requirements CPU support for Windows/Linux/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

Installation

CPU

install docker and docker service (and add user to docker group for linux)

unzip archive with your runtime

GPU

install docker and docker service (and add user to docker group for linux)

install nvidia-docker and run it

unzip archive with your runtime use runtime with -gpu suffix

Usage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux-gpu.zip(35.00 MB)
linux.zip(35.00 MB)
osx.zip(33.04 MB)
ubuntu16-gpu.zip(35.00 MB)
ubuntu16.zip(35.00 MB)
ubuntu18-gpu.zip(35.00 MB)
ubuntu18.zip(35.00 MB)
win10.zip(36.69 MB)
0.3.1(Oct 26, 2019)
Change log

fix bugs with model updating

add auth function and crypt keys

Ussage

system requirements CPU support for Windows/Linux (recommend)/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

Attention: Windows version have a critical bug with CPU cash. It happens cause Windows works with glx incorrect. We are working on ti. See #48 for more details.

Installation

CPU

install docker and docker service (and add user to docker group for linux)

unzip archive with your runtime

GPU

install docker and docker service (and add user to docker group for linux)

install nvidia-docker and run it

unzip archive with your runtime use runtime with -gpu suffix

Usage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux-gpu.zip(35.00 MB)
linux.zip(35.00 MB)
osx.zip(33.04 MB)
ubuntu16-gpu.zip(35.00 MB)
ubuntu16.zip(35.00 MB)
ubuntu18-gpu.zip(35.00 MB)
ubuntu18.zip(35.00 MB)
win10.zip(36.69 MB)
0.3.0(Sep 26, 2019)
Change log

fix bugs with model updating

add message boxes

add geo-tags support

add help and about function

add ability to save images with objects in specific folder

Ussage

system requirements CPU support for Windows/Linux (recommend)/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

Attention: Windows version have a critical bug with CPU cash. It happens cause Windows works with glx incorrect. We are working on ti. See #48 for more details.

Installation

CPU

install docker and docker service (and add user to docker group for linux)

unzip archive with your runtime

GPU

install docker and docker service (and add user to docker group for linux)

install nvidia-docker and run it

unzip archive with your runtime use runtime with -gpu suffix

Usage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux-gpu.zip(34.96 MB)
linux.zip(34.96 MB)
osx.zip(33.00 MB)
ubuntu16-gpu.zip(34.96 MB)
ubuntu16.zip(34.96 MB)
ubuntu18-gpu.zip(34.96 MB)
ubuntu18.zip(34.96 MB)
win10.zip(36.65 MB)
0.2.9(Sep 26, 2019)
Change log

fix bugs with model updating

add message boxes

add geo-tags support

add help and about function

add ability to save images with objects in specific folder

Ussage

system requirements

CPU support for Windows/Linux (recommend)/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

Attention: Windows version have a critical bug with CPU cashe. It heppens couse Windows works with glx incorrect. We are working on ti.

Instalation

CPU

install docker and docker service (and add user to docker group for linux)

unzip archive with your runtime

GPU

install docker and docker service (and add user to docker group for linux)

install nvidia-docker and run it

unzip archive with your runtime use runtime with -gpu suffix

Ussage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux-gpu.zip(34.96 MB)
linux.zip(34.96 MB)
osx.zip(33.00 MB)
ubuntu16-gpu.zip(34.96 MB)
ubuntu16.zip(34.96 MB)
ubuntu18-gpu.zip(34.96 MB)
ubuntu18.zip(34.96 MB)
win10.zip(36.65 MB)
0.2.8(Sep 5, 2019)
Change log

fix bugs with docker

fix render timer bug at avalonia 0.8.x

update avalonia ui 0.8.0 => 0.8.2

speed up image loading on linux

smaller docker images size

add gpu support

add api versioning support

Ussage

system requirements CPU support for Windows/Linux (recommend)/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

Attention: Windows version have a critical bug with CPU cashe. It heppens couse Windows works with glx incorrect. We are working on ti.

Instalation

CPU

install docker and docker service (and add user to docker group for linux)

unzip archive with your runtime

GPU

install docker and docker service (and add user to docker group for linux)

install nvidia-docker and run it

unzip archive with your runtime use runtime with -gpu suffix

Ussage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux-gpu.zip(34.50 MB)
linux.zip(34.50 MB)
osx.zip(32.53 MB)
ubuntu16-gpu.zip(34.62 MB)
ubuntu16.zip(34.50 MB)
ubuntu18-gpu.zip(34.62 MB)
ubuntu18.zip(34.50 MB)
win10.zip(36.50 MB)
0.2.7(Aug 23, 2019)
Change log

fix bugs with docker tags

smaller archive sizes

Ussage

system requirements CPU support for Windows/Linux (recommend)/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

OS: Windows 10 / Lunux / MacOS X (x64 only!). CPU: 2x+ Core CPU (with AVX, SSE SSE2 SSE3 SSE4 SSE4.1) Intel Core i3/i5/i7/xeon Sandy Bridge / AMD Buldozer and higher (Note: intel celeron does not support!) GPU (Optional): GTX, 4Gb vRAM, CUDA 9.1+ comparable (including CUDA 10 and higher), no CUDA driver required, e.g. GTX 950m and higher RAM: 4096 mb RAM and higher Storage: 5gb free disk space (10gb free disk space for GPU version)

UPD: Windows version have a critical bug with CPU cashe. It heppens couse Windows works with glx incorrect. We are working on ti.

Instalation

CPU

install docker and docker service

unzip archive with your runtime

GPU (experemental support in this release)

install docker and docker service

install nvidia-docker and run it

unzip archive with your runtime

Ussage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes (x64 only!)

win10 - windows 10 pro (x64 only!)

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04 (x64 only!)

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra or higher (x64 only!)

Source code(tar.gz)
Source code(zip)
linux.zip(34.49 MB)
osx.zip(32.53 MB)
ununtu16.zip(34.50 MB)
ununtu18.zip(34.50 MB)
win10.zip(34.59 MB)
0.2.6(Aug 14, 2019)
Change log

client app works without docker

add docker manager

add neoro-model auto updator

better models

update dataset

Ussage

CPU support for Windows/Linux (recommend)/CentOS/MacOS X GPU support ONLY for linux, only nvidia graphic support

Instalation

CPU

install docker and docker service

unzip archive with your runtime

GPU (experemental support in this release)

install docker and docker service

install nvidia-docker and run it

unzip archive with your runtime

Ussage

Linux\CentOS\OSX

cd /directory/with/app/ ./ReacuerLaApp

Windows

go to directory with app run ReacuerLaApp.exe

Supported Runtimes

win10 - windows 10 x64 pro

ubuntu16; ubuntu18 - linux ubuntu 16.04 and 18.04

linux - most computer linux distributions (x64 only!), such as CentOS, Debian, Fedora, Arch, Gentoo and their derivatives

osx - macOS 10.12 Sierra x64 or higher

Source code(tar.gz)
Source code(zip)
linux.zip(34.61 MB)
osx.zip(34.35 MB)
ununtu16.zip(34.61 MB)
ununtu18.zip(34.61 MB)
win10.zip(34.68 MB)

0.2.5(Jun 28, 2019)

Change log

Update zoom feature - add more useful navigation. (press up down left right arrows on keyboard to move image)
Fix some critical bugs

Ussage

Use dockerfile to launch it.

CPU support for Windows/Linux (recommend)/MacOS X GPU support ONLY for linux, only nvidia graphic support

Instalation

CPU

docker build -t rescuer_la .

GPU

docker build --file Dockerfile.gpu -t rescuer_la_gpu .

Ussage

In some distributive (e.g. Debian / Ubuntu) you should run this command before (see issue #8)

sudo xhost +

CPU

docker run --rm \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

GPU

docker run --rm \
--runtime=nvidia \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la_gpu

Source code(tar.gz)
Source code(zip)

0.2.4(Jun 27, 2019)

Change log

Add zoom feature
Fix bugs
Speedup image zooming

Ussage

Use dockerfile to launch it.

CPU support for Windows/Linux (recommend)/MacOS X GPU support ONLY for linux, only nvidia graphic support

Instalation

CPU

docker build -t rescuer_la .

GPU

docker build --file Dockerfile.gpu -t rescuer_la_gpu .

Ussage

In some distributive (e.g. Debian / Ubuntu) you should run this command before (see issue #8)

sudo xhost +

CPU

docker run --rm \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

GPU

docker run --rm \
--runtime=nvidia \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la_gpu

Source code(tar.gz)
Source code(zip)

0.2.3(Jun 26, 2019)

Change log

Add save annotation function
Add console applications to work with datasets
Update LADD dataset
Fix bugs

Liza Alert Drone Ddataset v2

You can download Liza Alert Drone Dataset

Ussage

Use dockerfile to launch it.

CPU support for Windows/Linux (recommend)/MacOS X GPU support ONLY for linux, only nvidia graphic support

Instalation

CPU

docker build -t rescuer_la .

GPU

docker build --file Dockerfile.gpu -t rescuer_la_gpu .

Ussage

In some distributive (e.g. Debian / Ubuntu) you should run this command before (see issue #8)

sudo xhost +

CPU

docker run --rm \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

GPU

docker run --rm \
--runtime=nvidia \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la_gpu

Source code(tar.gz)
Source code(zip)

0.2.2(Jun 19, 2019)

Change log

Update model inference
Fix bugs
Speedup image loading
Speedup image proсessing
Go to the newest version avalonUI
Reduce resource consumption
Add automatic build (by @ortho)
Code refactoring (by @worldbeater)

Ussage

Use dockerfile to launch it.

CPU support for Windows/Linux (recommend)/MacOS X GPU support ONLY for linux, only nvidia graphic support

Instalation

CPU

docker build -t rescuer_la .

GPU

docker build --file Dockerfile.gpu -t rescuer_la_gpu .

Ussage

In some distributive (e.g. Debian / Ubuntu) you should run this command before (see issue #8)

sudo xhost +

CPU

docker run --rm \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

GPU

docker run --rm \
--runtime=nvidia \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la_gpu

Source code(tar.gz)
Source code(zip)

0.2.1(Jun 3, 2019)

Fix the Issue #7

Use dockerfile to launch it.

CPU support for Windows/Linux (recommend)/MacOS X GPU support ONLY for linux, only nvidia graphic support

Ussage

Instalation

CPU

docker build -t rescuer_la .

GPU

docker build --file Dockerfile.gpu -t rescuer_la .

Ussage

In some distributive (e.g. Debian / Ubuntu) you should run this command before (see issue #8)

sudo xhost +

CPU

docker run --rm \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

GPU

docker run --rm \
--runtime=nvidia
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

Source code(tar.gz)
Source code(zip)

0.2.0(May 17, 2019)

Create cross platform gui application

Use dockerfile to launch it.

CPU support for Windows/Linux (recommend)/MacOS X GPU support ONLY for linux, only nvidia graphic support

Ussage

Instalation

CPU

docker build -t rescuer_la .

GPU

docker build --file Dockerfile.gpu -t rescuer_la .

Ussage

CPU

docker run --rm \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

GPU

docker run --rm \
--runtime=nvidia
-v /tmp/.X11-unix:/tmp/.X11-unix \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
rescuer_la

Source code(tar.gz)
Source code(zip)
screen.png(279.21 KB)

0.1.1(Mar 17, 2019)

mAP = 0.943
Source code(tar.gz)
Source code(zip)
resnet50_liza_alert_v1.h5(416.60 MB)
resnet50_liza_alert_v1_interface.h5(139.47 MB)
0.1.0(Mar 13, 2019)
Video Demo

resnet50_base_best trained on SDD (stenfort drone dataset).

resnet50_liza_alert_v01 trained on LADD (Liza Alert Drone Dataset) v.0.1

Source code(tar.gz)
Source code(zip)
resnet50_base_best.h5(416.20 MB)
resnet50_base_best_interfase.h5(139.33 MB)
resnet50_liza_alert_v01.h5(237.59 MB)
resnet50_liza_alert_v01_interfase.h5(139.47 MB)

Owner

Lacmus Foundation

open-source fondation engaged in the search for missing people and developments in the field of computer vision and deep learning

GitHub Repository https:/lacmus.ml/

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Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

Related tags

Overview

lacmus

Demonstration

Training data

Usage

Pretrained models

Partners

Comments

Releases(2.5.0)

2.5.0(Aug 18, 2021)

0.3.2(Nov 13, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.3.2-preview(Nov 8, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.3.1(Oct 26, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.3.0(Sep 26, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.2.9(Sep 26, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.2.8(Sep 5, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.2.7(Aug 23, 2019)

Change log

Ussage

Supported Runtimes (x64 only!)

0.2.6(Aug 14, 2019)

Change log

Ussage

Supported Runtimes

0.2.5(Jun 28, 2019)

Change log

Ussage

0.2.4(Jun 27, 2019)

Change log

Ussage

0.2.3(Jun 26, 2019)

Change log

Liza Alert Drone Ddataset v2

Ussage

0.2.2(Jun 19, 2019)

Change log

Ussage

0.2.1(Jun 3, 2019)

Ussage

0.2.0(May 17, 2019)

Ussage

0.1.1(Mar 17, 2019)

0.1.0(Mar 13, 2019)

Owner

Lacmus Foundation

Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network

Understanding Convolution for Semantic Segmentation

Contains a bunch of different python programm tasks

A collection of easy-to-use, ready-to-use, interesting deep neural network models

An algorithm that handles large-scale aerial photo co-registration, based on SURF, RANSAC and PyTorch autograd.

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation

Data and codes for ACL 2021 paper: Towards Emotional Support Dialog Systems

DI-smartcross - Decision Intelligence Platform for Traffic Crossing Signal Control

ReConsider is a re-ranking model that re-ranks the top-K (passage, answer-span) predictions of an Open-Domain QA Model like DPR (Karpukhin et al., 2020).

A PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detection.

Barbershop: GAN-based Image Compositing using Segmentation Masks (SIGGRAPH Asia 2021)

Source code for paper "ATP: AMRize Than Parse! Enhancing AMR Parsing with PseudoAMRs" @NAACL-2022

Vertex AI: Serverless framework for MLOPs (ESP / ENG)

CSAC - Collaborative Semantic Aggregation and Calibration for Separated Domain Generalization