Predicting 10 different clothing types using Xception pre-trained model.

Last update: Dec 29, 2021

Overview

Predicting-Clothing-Types

Predicting 10 different clothing types using Xception pre-trained model from Keras library. It is reimplemented version from lesson 8-deep learning held by DataTalksClub.

Model Demo

About the Dataset

Data Source

I use the dataset from here: https://github.com/alexeygrigorev/clothing-dataset-small

Dataset Information

This is a small dataset contains 10 different clothing types (dress, hat, longsleeve, outwear, pants, shirt, shoes, shorts, skirt, t-shirt).

Short Description of the Files

training-final-dlmodel.ipynb -

used transfer learning to get Xception model pretrained on Imagnet.
freeze its CNN layers and train the dense layers.
used callbacks to save the best model over multiple epochs.
did some data augmentation to prevent overfitting and generalize our model.
Evalutaing the model, Aciheved 90% accuracy.

streamlit_DLapp.py It deploy the trained model to streamlit cloud
xception_v5_1_10_0.889.h5 - Best model from training saved in this binary format to load it easily.
Pipfile and Pipfile.lock - Python package dependencies, in the pipfile you can find all necessary librares and packages to be able to run the scripts with no problem.

How to run this model

open this link
Upload an image from test dataset or any image from your device that has one clothing type.
click on Predict Class button.

Note: watch this video to see the model in action

How to reproduce this model

clone this repo to get all the code.
clone the dataset using this command

!git clone git@github.com:alexeygrigorev/clothing-dataset-small.git

install pipenv -which is a packaging tool that will help installing all dependencies- , use this command on your terminal.

pip install pipenv

install all dependencies using pipenv by typing this command in your terminal inside your cloned repo folder

pipenv install

Deploying the app locally or on the web 5.1. Locally: open the terminal and use this command

streamlit run streamlit_DLapp.py

5.2. on the web: check the documentation from official website.

Note

If you like my project, I appreciate you starring this repo. Please feel free to fork the content and contact me if you have any questions.

my linkedIn account

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

Adaptive Segmentation Mask Attack This repository contains the implementation of the Adaptive Segmentation Mask Attack (ASMA), a targeted adversarial

53 Jul 4, 2022

The Hailo Model Zoo includes pre-trained models and a full building and evaluation environment

Hailo Model Zoo The Hailo Model Zoo provides pre-trained models for high-performance deep learning applications. Using the Hailo Model Zoo you can mea

50 Dec 7, 2022

🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

PyTorch implementation of OpenAI's Finetuned Transformer Language Model This is a PyTorch implementation of the TensorFlow code provided with OpenAI's

1.4k Jan 5, 2023

DziriBERT: a Pre-trained Language Model for the Algerian Dialect

DziriBERT DziriBERT is the first Transformer-based Language Model that has been pre-trained specifically for the Algerian Dialect. It handles Algerian

117 Jan 7, 2023

Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"

Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo

5 Nov 11, 2022

A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

9 Jan 12, 2022

SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss

"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i

28 Dec 12, 2022

Python KNN model: Predicting a probability of getting a work visa. Tableau: Non-immigrant visas over the years.

The value of international students to the United States. Probability of getting a non-immigrant visa. Project timeline: Jan 2021 - April 2021 Project

2 Nov 21, 2021

Ever felt tired after preprocessing the dataset, and not wanting to write any code further to train your model? Ever encountered a situation where you wanted to record the hyperparameters of the trained model and able to retrieve it afterward? Models Playground is here to help you do that. Models playground allows you to train your models right from the browser.

Models Playground 🗂️ Upload a Preprocessed Dataset 🌠 Choose whether to perform Classification or Regression 🦹 Enter the Dependent Variable ?

19 Dec 10, 2022

Predicting 10 different clothing types using Xception pre-trained model.

Related tags

Overview

Predicting-Clothing-Types

Model Demo

About the Dataset

Data Source

Dataset Information

Short Description of the Files

How to run this model

How to reproduce this model

Note

You might also like...

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

The Hailo Model Zoo includes pre-trained models and a full building and evaluation environment

🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI

DziriBERT: a Pre-trained Language Model for the Algerian Dialect

Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"

A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss

Python KNN model: Predicting a probability of getting a work visa. Tableau: Non-immigrant visas over the years.

Owner

AbdAssalam Ahmad

This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.

Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts

Code for "ShineOn: Illuminating Design Choices for Practical Video-based Virtual Clothing Try-on", accepted at WACV 2021 Generation of Human Behavior Workshop.

LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference

Official implementation of the ICCV 2021 paper: "The Power of Points for Modeling Humans in Clothing".

Rafael Project- Classifying rockets to different types using data science algorithms.

Chinese clinical named entity recognition using pre-trained BERT model

PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset

Annotate datasets with a semi-trained or fully trained YOLOv5 model

Trash Sorter Extraordinaire is a software which efficiently detects the different types of waste in a pile of random trash through feeding it pictures or videos.