Virtual Dance Reality Stage: a feature that offers you to share a stage with another user virtually

Overview

Portrait Segmentation using Tensorflow

This script removes the background from an input image. You can read more about segmentation here

Setup

The script setup.sh downloads the trained model and sets it up so that the seg.py script can understand.

./setup.sh

Running the script

Go ahead and use the script as specified below, to execute fast but lower accuracy model:

python3 seg.py sample.jpg sample.png

For better accuracy, albiet a slower approach, go ahead and try :

python3 seg.py sample.jpg sample.png 1

Dependencies

tensorflow, PIL

Sample Result

Input: alt text

Output: alt text

Comments
  • AttributeError: module 'tensorflow' has no attribute 'GraphDef'

    AttributeError: module 'tensorflow' has no attribute 'GraphDef'

    $python3 seg.py sample.jpg sample.png

    Traceback (most recent call last): File "seg.py", line 89, in MODEL = DeepLabModel(modelType) File "seg.py", line 25, in init graph_def = tf.GraphDef.FromString(open(tarball_path + "/frozen_inference_graph.pb", "rb").read()) AttributeError: module 'tensorflow' has no attribute 'GraphDef'

    I am getting this error when execute the given command. Can you please help me on this?

    opened by tnavadiya 2
  • Remove background from image without loss of image resolution

    Remove background from image without loss of image resolution

    Remove background from image without loss of image resolution

    Changes:

    • The code base is completely rewritten
    • Changed model storage paths
    • Rewritten installation script from bash to python language
    • Added full script compatibility with Windows (NOT TESTED)
    • Improved manual
    • Added examples of using the program
    • Added versions of the necessary dependencies for the program (Added requirements.txt)
    • Tensorflow 2.0 compatible
    • Added comments to the code.
    • Added tqdm progress bar.
    • Removes background from image without loss of image resolution.
    • The script now not only processes a single file, but can also process all images from the input folder and save them in the output folder with the same name.
    • New sample images.
    • And many other minor changes and fixes.
    opened by OPHoperHPO 0
  • Remove background from image without loss of image resolution

    Remove background from image without loss of image resolution

    Remove background from image without loss of image resolution

    Changes:

    1. The code base is completely rewritten
    2. Changed model storage paths
    3. Rewritten installation script from bash to python language
    4. Added full script compatibility with Windows (NOT TESTED)
    5. Improved manual
    6. Added examples of using the program
    7. Added versions of the necessary dependencies for the program (Added requirements.txt)
    8. Tensorflow 2.0 compatible
    9. Added comments to the code.
    10. Added tqdm progress bar.
    11. Removes background from image without loss of image resolution.
    12. The script now not only processes a single file, but can also process all images from the input folder and save them in the output folder with the same name.
    13. New sample images.
    14. And many other minor changes and fixes.
    opened by OPHoperHPO 0
  • more accurate pretrained model ?

    more accurate pretrained model ?

    hi thanks for sharing your code, i was searching for a complete solution like yours for a while. the outputs are pretty good , but i was looking for a model to give me high definition output.

    could you please guide me where i can find the models ? thanks again

    opened by kamikazem 0
  • When running your code I got a error

    When running your code I got a error

    Hi @susheelsk, I got an error running your code.

    C:\image-background>python seg.py /input/0001.jpg /output/0001.png 1 Traceback (most recent call last): File "seg.py", line 89, in MODEL = DeepLabModel(modelType) File "seg.py", line 25, in init graph_def = tf.GraphDef.FromString(open(tarball_path + "/frozen_inference_graph.pb", "rb").read()) AttributeError: module 'tensorflow' has no attribute 'GraphDef'

    Can you help?

    opened by usalexsantos 5
Owner
null
An image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testingAn image base contains 490 images for learning (400 cars and 90 boats), and another 21 images for testing

SVM Données Une base d’images contient 490 images pour l’apprentissage (400 voitures et 90 bateaux), et encore 21 images pour fait des tests. Prétrait

Achraf Rahouti 3 Nov 30, 2021
A neuroanatomy-based augmented reality experience powered by computer vision. Features 3D visuals of the Atlas Brain Map slices.

Brain Augmented Reality (AR) A neuroanatomy-based augmented reality experience powered by computer vision that features 3D visuals of the Atlas Brain

Yasmeen Brain 10 Oct 6, 2022
[CVPR 2022] Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement

Back To Reality: Weak-supervised 3D Object Detection with Shape-guided Label Enhancement Announcement ?? We have not tested the code yet. We will fini

Xiuwei Xu 7 Oct 30, 2022
AI Virtual Calculator: This is a simple virtual calculator based on Artificial intelligence.

AI Virtual Calculator: This is a simple virtual calculator that works with gestures using OpenCV. We will use our hand in the air to click on the calc

Md. Rakibul Islam 1 Jan 13, 2022
Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition"

Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition", accepted at ACL 2021. For details of the model and experiments, please see our paper.

tricktreat 87 Dec 16, 2022
Code for our NeurIPS 2021 paper Mining the Benefits of Two-stage and One-stage HOI Detection

CDN Code for our NeurIPS 2021 paper "Mining the Benefits of Two-stage and One-stage HOI Detection". Contributed by Aixi Zhang*, Yue Liao*, Si Liu, Mia

null 71 Dec 14, 2022
Code for Mining the Benefits of Two-stage and One-stage HOI Detection

Status: Archive (code is provided as-is, no updates expected) PPO-EWMA [Paper] This is code for training agents using PPO-EWMA and PPG-EWMA, introduce

OpenAI 33 Dec 15, 2022
Tensorflow python implementation of "Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos"

Learning High Fidelity Depths of Dressed Humans by Watching Social Media Dance Videos This repository is the official tensorflow python implementation

Yasamin Jafarian 287 Jan 6, 2023
The personal repository of the work: *DanceNet3D: Music Based Dance Generation with Parametric Motion Transformer*.

DanceNet3D The personal repository of the work: DanceNet3D: Music Based Dance Generation with Parametric Motion Transformer. Dataset and Results Pleas

南嘉Nanga 36 Dec 21, 2022
PyTorch implementation of the cross-modality generative model that synthesizes dance from music.

Dancing to Music PyTorch implementation of the cross-modality generative model that synthesizes dance from music. Paper Hsin-Ying Lee, Xiaodong Yang,

NVIDIA Research Projects 485 Dec 26, 2022
Public repository created to store my custom-made tools for Just Dance (UbiArt Engine)

Woody's Just Dance Tools Public repository created to store my custom-made tools for Just Dance (UbiArt Engine) Development and updates Almost all of

Wodson de Andrade 8 Dec 24, 2022
It helps user to learn Pick-up lines and share if he has a better one

Pick-up-Lines-Generator(Open Source) It helps user to learn Pick-up lines Share and Add one or many to the DataBase Unique SQLite DataBase AI Undercon

knock_nott 0 May 4, 2022
The repository offers the official implementation of our paper in PyTorch.

Cloth Interactive Transformer (CIT) Cloth Interactive Transformer for Virtual Try-On Bin Ren1, Hao Tang1, Fanyang Meng2, Runwei Ding3, Ling Shao4, Phi

Bingoren 49 Dec 1, 2022
This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters.

openmc-plasma-source This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters. The OpenMC sources a

Fusion Energy 10 Oct 18, 2022
The pyrelational package offers a flexible workflow to enable active learning with as little change to the models and datasets as possible

pyrelational is a python active learning library developed by Relation Therapeutics for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximation), to creating novel active learning strategies.

Relation Therapeutics 95 Dec 27, 2022
Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer

Two-Stage Peer-Regularized Feature Recombination for Arbitrary Image Style Transfer Paper on arXiv Public PyTorch implementation of two-stage peer-reg

NNAISENSE 38 Oct 14, 2022
VOS: Learning What You Don’t Know by Virtual Outlier Synthesis

VOS This is the source code accompanying the paper VOS: Learning What You Don’t

null 248 Dec 25, 2022