NIMA: Neural IMage Assessment

Kyryl Truskovskyi

Last update: Dec 30, 2022

Related tags

Deep Learning python machine-learning computer-vision deep-learning neural-network pytorch arxiv nima

Overview

PyTorch NIMA: Neural IMage Assessment

PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from this post at Google Research Blog.

Installing

Docker

docker run -it truskovskiyk/nima:latest /bin/bash

PYPI package (In Progress)

pip install nima

VirtualEnv

git clone https://github.com/truskovskiyk/nima.pytorch.git
cd nima.pytorch
virtualenv -p python3.7 env
source ./env/bin/activate

Dataset

The model was trained on the AVA (Aesthetic Visual Analysis) dataset You can get it from here Here are some examples of images with theire scores

Pre-train model (In Progress)

Deployment (In progress)

Usage

nima-cli

Usage: cli.py [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  get_image_score  Get image scores
  prepare_dataset  Parse, clean and split dataset
  run_web_api      Start server for model serving
  train_model      Train model
  validate_model   Validate model

Previous version of this project is still valid and works

you can find here

Contributing

Contributing are welcome

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

Comments

Missing tensorboardX dependency

Thanks for releasing this.

The separate dependencies for GPU vs CPU vs Mac is very nice.

You need to add tensorboardX. I guess it should go in base.txt but not entirely sure.

opened by nlothian 1
Bump numpy from 1.16.4 to 1.22.0
Bumps numpy from 1.16.4 to 1.22.0.

Release notes

Sourced from numpy's releases.

v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.

A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.

NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.

New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.

A new configurable allocator for use by downstream projects.

These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)

... (truncated)

Commits

4adc87d Merge pull request #20685 from charris/prepare-for-1.22.0-release

fd66547 REL: Prepare for the NumPy 1.22.0 release.

125304b wip

c283859 Merge pull request #20682 from charris/backport-20416

5399c03 Merge pull request #20681 from charris/backport-20954

f9c45f8 Merge pull request #20680 from charris/backport-20663

794b36f Update armccompiler.py

d93b14e Update test_public_api.py

7662c07 Update init.py

311ab52 Update armccompiler.py

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dependencies
opened by dependabot[bot] 0
Bump ipython from 7.5.0 to 7.16.3
Bumps ipython from 7.5.0 to 7.16.3.

Commits

d43c7c7 release 7.16.3

5fa1e40 Merge pull request from GHSA-pq7m-3gw7-gq5x

8df8971 back to dev

9f477b7 release 7.16.2

138f266 bring back release helper from master branch

5aa3634 Merge pull request #13341 from meeseeksmachine/auto-backport-of-pr-13335-on-7...

bcae8e0 Backport PR #13335: What's new 7.16.2

8fcdcd3 Pin Jedi to <0.17.2.

2486838 release 7.16.1

20bdc6f fix conda build

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dependencies
opened by dependabot[bot] 0

Update to modern pytorch and fix model ckpt link

I fixed up the code to make inference possible out of the box

Inference example:

from nima.inference.inference_model import InferenceModel

model = InferenceModel(path_to_model=Path('./pretrain-model.pth'))

result = model.predict_from_pil_image(img)

opened by Dawars 1

Bump aiohttp from 3.5.4 to 3.7.4
Bumps aiohttp from 3.5.4 to 3.7.4.

Release notes

Sourced from aiohttp's releases.

aiohttp 3.7.3 release

Features

Use Brotli instead of brotlipy [#3803](https://github.com/aio-libs/aiohttp/issues/3803) <https://github.com/aio-libs/aiohttp/issues/3803>_

Made exceptions pickleable. Also changed the repr of some exceptions. [#4077](https://github.com/aio-libs/aiohttp/issues/4077) <https://github.com/aio-libs/aiohttp/issues/4077>_

Bugfixes

Raise a ClientResponseError instead of an AssertionError for a blank HTTP Reason Phrase. [#3532](https://github.com/aio-libs/aiohttp/issues/3532) <https://github.com/aio-libs/aiohttp/issues/3532>_

Fix web_middlewares.normalize_path_middleware behavior for patch without slash. [#3669](https://github.com/aio-libs/aiohttp/issues/3669) <https://github.com/aio-libs/aiohttp/issues/3669>_

Fix overshadowing of overlapped sub-applications prefixes. [#3701](https://github.com/aio-libs/aiohttp/issues/3701) <https://github.com/aio-libs/aiohttp/issues/3701>_

Make BaseConnector.close() a coroutine and wait until the client closes all connections. Drop deprecated "with Connector():" syntax. [#3736](https://github.com/aio-libs/aiohttp/issues/3736) <https://github.com/aio-libs/aiohttp/issues/3736>_

Reset the sock_read timeout each time data is received for a aiohttp.client response. [#3808](https://github.com/aio-libs/aiohttp/issues/3808) <https://github.com/aio-libs/aiohttp/issues/3808>_

Fixed type annotation for add_view method of UrlDispatcher to accept any subclass of View [#3880](https://github.com/aio-libs/aiohttp/issues/3880) <https://github.com/aio-libs/aiohttp/issues/3880>_

Fixed querying the address families from DNS that the current host supports. [#5156](https://github.com/aio-libs/aiohttp/issues/5156) <https://github.com/aio-libs/aiohttp/issues/5156>_

Change return type of MultipartReader.aiter() and BodyPartReader.aiter() to AsyncIterator. [#5163](https://github.com/aio-libs/aiohttp/issues/5163) <https://github.com/aio-libs/aiohttp/issues/5163>_

Provide x86 Windows wheels. [#5230](https://github.com/aio-libs/aiohttp/issues/5230) <https://github.com/aio-libs/aiohttp/issues/5230>_

Improved Documentation

Add documentation for aiohttp.web.FileResponse. [#3958](https://github.com/aio-libs/aiohttp/issues/3958) <https://github.com/aio-libs/aiohttp/issues/3958>_

Removed deprecation warning in tracing example docs [#3964](https://github.com/aio-libs/aiohttp/issues/3964) <https://github.com/aio-libs/aiohttp/issues/3964>_

Fixed wrong "Usage" docstring of aiohttp.client.request. [#4603](https://github.com/aio-libs/aiohttp/issues/4603) <https://github.com/aio-libs/aiohttp/issues/4603>_

Add aiohttp-pydantic to third party libraries [#5228](https://github.com/aio-libs/aiohttp/issues/5228) <https://github.com/aio-libs/aiohttp/issues/5228>_

Misc

... (truncated)

Changelog

Sourced from aiohttp's changelog.

3.7.4 (2021-02-25)

Bugfixes

(SECURITY BUG) Started preventing open redirects in the aiohttp.web.normalize_path_middleware middleware. For more details, see https://github.com/aio-libs/aiohttp/security/advisories/GHSA-v6wp-4m6f-gcjg.

Thanks to Beast Glatisant <https://github.com/g147>__ for finding the first instance of this issue and Jelmer Vernooĳ <https://jelmer.uk/>__ for reporting and tracking it down in aiohttp. [#5497](https://github.com/aio-libs/aiohttp/issues/5497) <https://github.com/aio-libs/aiohttp/issues/5497>_

Fix interpretation difference of the pure-Python and the Cython-based HTTP parsers construct a yarl.URL object for HTTP request-target.

Before this fix, the Python parser would turn the URI's absolute-path for //some-path into / while the Cython code preserved it as //some-path. Now, both do the latter. [#5498](https://github.com/aio-libs/aiohttp/issues/5498) <https://github.com/aio-libs/aiohttp/issues/5498>_

3.7.3 (2020-11-18)

Features

Use Brotli instead of brotlipy [#3803](https://github.com/aio-libs/aiohttp/issues/3803) <https://github.com/aio-libs/aiohttp/issues/3803>_

Made exceptions pickleable. Also changed the repr of some exceptions. [#4077](https://github.com/aio-libs/aiohttp/issues/4077) <https://github.com/aio-libs/aiohttp/issues/4077>_

Bugfixes

Raise a ClientResponseError instead of an AssertionError for a blank HTTP Reason Phrase. [#3532](https://github.com/aio-libs/aiohttp/issues/3532) <https://github.com/aio-libs/aiohttp/issues/3532>_

Fix web_middlewares.normalize_path_middleware behavior for patch without slash. [#3669](https://github.com/aio-libs/aiohttp/issues/3669) <https://github.com/aio-libs/aiohttp/issues/3669>_

Fix overshadowing of overlapped sub-applications prefixes. [#3701](https://github.com/aio-libs/aiohttp/issues/3701) <https://github.com/aio-libs/aiohttp/issues/3701>_

... (truncated)

Commits

0a26acc Bump aiohttp to v3.7.4 for a security release

021c416 Merge branch 'ghsa-v6wp-4m6f-gcjg' into master

4ed7c25 Bump chardet from 3.0.4 to 4.0.0 (#5333)

b61f0fd Fix how pure-Python HTTP parser interprets //

5c1efbc Bump pre-commit from 2.9.2 to 2.9.3 (#5322)

0075075 Bump pygments from 2.7.2 to 2.7.3 (#5318)

5085173 Bump multidict from 5.0.2 to 5.1.0 (#5308)

5d1a75e Bump pre-commit from 2.9.0 to 2.9.2 (#5290)

6724d0e Bump pre-commit from 2.8.2 to 2.9.0 (#5273)

c688451 Removed duplicate timeout parameter in ClientSession reference docs. (#5262) ...

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dependencies
opened by dependabot[bot] 0
Difference between deploy and released models

Based on the same image, 5.9 is received through your get-image-score command. But 6.58 out of your deploy url 'https://neural-image-assessment.herokuapp.com/api/get_scores'. Furthermore, on your github page, the result is 6.38. So, are there different models you used in these different ways. Looking forward to your reply.

opened by ChuanchuanZheng 0
CLI command can only be invoked by " - " rather than " _ " in the original setting.

I was just tried to run the get one image's score as
python nima/cli.py get_image_score --path_to_model_weight ./pretrain-model.pth --path_to_image test_image.jpg while find below error, then I check the help info, and the program run correctly if I use "get-image-score" as in help info. I wander why this would occur when the defination and call function in cli.py are all using " _ ".

opened by JustinAsdz 1

Owner

Kyryl Truskovskyi

Machine Learning Engineer 🇺🇦🇨🇦

GitHub

[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment

RADN [CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment [Paper on arXiv] Overview Update [2021/5/7] add codes for W

53 Dec 28, 2022

Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN", accepted to ACM MM 2021 BNI Track.

RecycleD Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN

23 Nov 5, 2022

Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"

DSN-IQA Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment" Requirements Python >=3.8.0 Pytorch >=1.7.1 Usage wit

7 Oct 13, 2022

Lightweight Face Image Quality Assessment

LightQNet This is a demo code of training and testing [LightQNet] using Tensorflow. Uncertainty Losses: IDQ loss PCNet loss Uncertainty Networks: Mobi

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No-reference Image Quality Assessment(NIQA) Algorithms (BRISQUE, NIQE, PIQE, RankIQA, MetaIQA)

No-Reference Image Quality Assessment Algorithms No-reference Image Quality Assessment(NIQA) is a task of evaluating an image without a reference imag

26 Jan 4, 2023

[CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

Attention Helps CNN See Better: Hybrid Image Quality Assessment Network [CVPRW 2022] Code for Hybrid Image Quality Assessment Network [paper] [code] T

49 Dec 11, 2022

Easy and comprehensive assessment of predictive power, with support for neuroimaging features

Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t

93 Nov 29, 2022

MagFace: A Universal Representation for Face Recognition and Quality Assessment

MagFace MagFace: A Universal Representation for Face Recognition and Quality Assessment in IEEE Conference on Computer Vision and Pattern Recognition

523 Jan 5, 2023

Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)

A Critical Assessment of State-of-the-Art in Entity Alignment This repository contains the source code for the paper A Critical Assessment of State-of

16 Oct 14, 2022

Repo for 2021 SDD assessment task 2, by Felix, Anna, and James.

SoftwareTask2 Repo for 2021 SDD assessment task 2, by Felix, Anna, and James. File/folder structure: helloworld.py - demonstrates various map backgrou

3 Dec 13, 2022

[ICCV 2021] Group-aware Contrastive Regression for Action Quality Assessment

CoRe Created by Xumin Yu*, Yongming Rao*, Wenliang Zhao, Jiwen Lu, Jie Zhou This is the PyTorch implementation for ICCV paper Group-aware Contrastive

31 Dec 24, 2022

Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

65 Dec 20, 2022

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

5 Sep 16, 2022

A user-friendly research and development tool built to standardize RL competency assessment for custom agents and environments.

Built with ❤️ by Sam Showalter Contents Overview Installation Dependencies Usage Scripts Standard Execution Environment Development Environment Benchm

1 Nov 18, 2021

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

2 Jan 5, 2022

Internship Assessment Task for BaggageAI.

BaggageAI Internship Task Problem Statement: You are given two sets of images:- background and threat objects. Background images are the background x-

10 Nov 14, 2022

NIMA: Neural IMage Assessment

Related tags

Overview

PyTorch NIMA: Neural IMage Assessment

Installing

Docker

PYPI package (In Progress)

VirtualEnv

Dataset

Pre-train model (In Progress)

Deployment (In progress)

Usage

Previous version of this project is still valid and works

Contributing

License

Acknowledgments

Comments

Missing tensorboardX dependency

Bump numpy from 1.16.4 to 1.22.0

v1.22.0

NumPy 1.22.0 Release Notes

Expired deprecations

Deprecated numeric style dtype strings have been removed

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

Bump ipython from 7.5.0 to 7.16.3

Update to modern pytorch and fix model ckpt link

Bump aiohttp from 3.5.4 to 3.7.4

aiohttp 3.7.3 release

Features

Bugfixes

Improved Documentation

Misc

3.7.4 (2021-02-25)

Bugfixes

3.7.3 (2020-11-18)

Features

Bugfixes

Difference between deploy and released models

CLI command can only be invoked by " - " rather than " _ " in the original setting.

Owner

Kyryl Truskovskyi

[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment

Official PyTorch implementation of the paper "Recycling Discriminator: Towards Opinion-Unaware Image Quality Assessment Using Wasserstein GAN", accepted to ACM MM 2021 BNI Track.

Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"

Lightweight Face Image Quality Assessment

No-reference Image Quality Assessment(NIQA) Algorithms (BRISQUE, NIQE, PIQE, RankIQA, MetaIQA)

[CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

Easy and comprehensive assessment of predictive power, with support for neuroimaging features

MagFace: A Universal Representation for Face Recognition and Quality Assessment

Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)

Repo for 2021 SDD assessment task 2, by Felix, Anna, and James.

[ICCV 2021] Group-aware Contrastive Regression for Action Quality Assessment

Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

A user-friendly research and development tool built to standardize RL competency assessment for custom agents and environments.

MRQy is a quality assurance and checking tool for quantitative assessment of magnetic resonance imaging (MRI) data.

ZEBRA: Zero Evidence Biometric Recognition Assessment

Pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

Internship Assessment Task for BaggageAI.

Expired deprecations for `loads`, `ndfromtxt`, and `mafromtxt` in npyio