leksandre / collaboration-neural-networks

обучение на тепловом набре "флир", с последующим объединением результатов работы с обычной нейросетью по идентификации

neuralnetorksRoad

D:\Python39\Lib\site-packages

I am using: pip install tensorflow==1.14.0 pip install keras==2.3.0 pip install numpy==1.16.6

pip install keras==2.4.2 pip install keras==2.4.3 pip install keras==2.5.0rc0

D:\Python37\lib\site-packages\imageai\Detection_init_.py

from keras import backend as K

import tensorflow.python.keras.backend as K

change from keras import backend as K to import tensorflow.python.keras.backend as K

width: 11px;height: 11px;

1.) смени интерпре6татор через ctrl+shift+P на python3.7 2.) запускайся из дирретории D:\Python39\Lib\site-packages

Папка без ботов

8b9a0ea3-b216-462e-99be-f9f474fcdb24

Аппка с ботами

fd35de59-6950-4300-97dd-7c432ac914bd

delete FROM re17535c.testview a WHERE a.ctid <>( SELECT min(b.ctid) FROM re17535c.testview b WHERE a.id1 = b.id1 and a.id2 = b.id2);

delete FROM re17535c.pwareddit a WHERE a.ctid <>( SELECT min(b.ctid) FROM re17535c.pwareddit b WHERE a.numpost = b.numpost and a.cid = b.cid);

pip install --user pipenv an then create a virtual environment using pipenv: cd project_directory pipenv install --python 3.8

WARNING: The scripts pipenv-resolver.exe and pipenv.exe are installed in 'C:\Users\jirdi\AppData\Roaming\Python\Python39\Scripts' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.

C:\Users\jirdi\AppData\Roaming\Python\Python39\Scripts\pipenv install C:\Users\jirdi\AppData\Roaming\Python\Python39\Scripts\pipenv install --python 3.7.6

set PATH=%PATH%;C:\your\path\here\

or Tensorflow GPU if you have NVIDIA GPU with CUDA and cuDNN installed.

Tensorflow pip install tensorflow==2.4.0

pip install tensorflow-cpu==2.4.0 pip install tensorflow-gpu==2.4.0 pip install tf-nightly-cpu==2.4.0 pip install tf-nightly-gpu==2.4.0 pip install tf-nightly==2.4.0

pip install keras==2.4.3 numpy==1.19.3 pillow==7.0.0 scipy==1.4.1 h5py==2.10.0 matplotlib==3.3.2 opencv-python keras-resnet==0.2.0 pip install imageai --upgrade

1.) remove pipenv 2.) select python3.7 3.) setup dependents

ERROR: Could not find a version that satisfies the requirement tensorflow==2.4.2 (from versions: 1.13.0rc1, 1.13.0rc2, 1.13.1, 1.13.2, 1.14.0rc0, 1.14.0rc1, 1.14.0, 1.15.0rc0, 1.15.0rc1, 1.15.0rc2, 1.15.0rc3, 1.15.0, 1.15.2, 1.15.3, 1.15.4, 1.15.5, 2.0.0a0, 2.0.0b0, 2.0.0b1, 2.0.0rc0, 2.0.0rc1, 2.0.0rc2, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.1.0rc0, 2.1.0rc1, 2.1.0rc2, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.2.0rc0, 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.2.1, 2.2.2, 2.3.0rc0, 2.3.0rc1, 2.3.0rc2, 2.3.0, 2.3.1, 2.3.2, 2.4.0rc0, 2.4.0rc1, 2.4.0rc2, 2.4.0rc3, 2.4.0rc4, 2.4.0, 2.4.1, 2.5.0rc0, 2.5.0rc1, 2.5.0rc2, 2.5.0rc3, 2.5.0)

ERROR: Could not find a version that satisfies the requirement keras==2.4.4 (from versions: 0.2.0, 0.3.0, 0.3.1, 0.3.2, 0.3.3, 1.0.0, 1.0.1, 1.0.2, 1.0.3, 1.0.4, 1.0.5, 1.0.6, 1.0.7, 1.0.8, 1.1.0, 1.1.1, 1.1.2, 1.2.0, 1.2.1, 1.2.2, 2.0.0, 2.0.1, 2.0.2, 2.0.3, 2.0.4, 2.0.5, 2.0.6, 2.0.7, 2.0.8, 2.0.9, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.1.5, 2.1.6, 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.2.4, 2.2.5, 2.3.0, 2.3.1, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.5.0rc0)

Could not find a version that satisfies the requirement imageai==2.0.1 (from versions: 2.0.2, 2.0.3, 2.1.0, 2.1.1, 2.1.2, 2.1.3, 2.1.4, 2.1.5, 2.1.6)

setup python3.7 pip install imageai --upgrade pip install tensorflow==2.4.0

SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.3\bin;%PATH% SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.3\extras\CUPTI\lib64;%PATH% SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.3\include;%PATH% SET PATH=C:\tools\cuda\bin;%PATH%

SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\bin;%PATH% SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\extras\CUPTI\lib64;%PATH% SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\include;%PATH% SET PATH=C:\tools\cuda\bin;%PATH%

D:\Python37\lib\site-packages\imageai\Detection\keras_retinanet\models_init_.py , compile=False 87 string

pip3 install six numpy wheel pip3 install keras_applications==1.0.6 --no-deps pip3 install keras_preprocessing==1.0.5 --no-deps

from keras.layers import LayerNormalization

pip freeze | %{$.split('==')[0]} | %{pip install --upgrade $}

pip freeze > requirements.txt pip install -r requirements.txt --upgrade

pip uninstall tf-nightly pip install tensorflow --upgrade --force-reinstall

pip install tensorflow pip install numpy pip install scipy pip install opencv-python pip install pillow pip install matplotlib pip install h5py pip install keras pip install https://github.com/OlafenwaMoses/ImageAI/releases/download/2.0.1/imageai-2.0.1-py3-none-any.whl

Name: Keras pip install keras==2.3.1 Version: 2.3.1 Summary: Deep Learning for humans

Name: tensorflow pip install tensorflow==2.2.0 Version: 2.2.0 Summary: TensorFlow is an open source machine learning framework for everyone.

Name: imageai pip install https://github.com/OlafenwaMoses/ImageAI/releases/download/2.0.1/imageai-2.0.1-py3-none-any.whl or pip install imageai==2.1.6 Version: 2.0.1 Summary: A flexible Computer Vision and Deep Learning library for applications and systems.

without tf-nightly tf-nightly-cpu tf-nightl-gpu tensorflow-gpu tensorflow-cpu

обучение идет при imageai=2.1.6, но поотм надо понижать keras resize_images переделывать в resize

evaluate training_model resnet50_coco_02_2step_INF.h5

Loading and preparing results... DONE (t=4.18s) creating index... index created! Running per image evaluation... Evaluate annotation type bbox DONE (t=48.71s). Accumulating evaluation results... DONE (t=4.49s). Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.255 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.524 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.210 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.182 Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.309 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.363 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.166 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.379 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.426 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.366 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.466 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.500