عکس NahidEbrahimian
Repository for Deep Learning Mini-Project with TensorflowJupyter Notebook
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Deep-Learning-Course

01- CNN and MLP

  • Test accuracy comparison between MLP and Deep Learning
Dataset MLP (Machine Learning) CNN + MLP (Deep Learning)
Mnist 0.97 0.98
Fashion Mnist 0.86 0.89
Cfar 10 0.37 0.63
Cfar 100 0.13 0.28

02- Sheikh-Recognition

  • Train Neural Network for normal person and sheikh images classification

  • train.ipynb

  • inference.py

Dataset:

contain images from two classes, normal person and sheikh

For inference run the following command:

!python3 inference.py --input_image test/image3.jpg

03- Sheikh-Recognition-bot

  • Train Neural Network for normal person and sheikh images classification

  • train.ipynb

  • bot.py

Dataset:

contain images from two classes, normal person and sheikh

Usage:

  1. Click here to open the chat with the bot in the Telegram app

  2. Start the bot and send him a photo

04- Persian Face Recognition

  • train.ipynb

  • preprocess.py

  • inference.py

Preprocessing

Preprocess stage consists of 4 common stages: detect, align, represent and verify. link: Github

  1. You must first install retinaface:
!pip install retina-face
  1. Run the following command to apply preprocessing:
!python3 preprocess.py --input_images_dir "./input_images" --output_dir "./output_dir"

05- 17Flowers Classification

Dataset:

Contain images from 17 classes of flowers in two subset, train and test.

Dataset link: Flowers

Result:

Comparison accuracy of pretrained models that used in transfer learning on test data:

Model Accuracy
Vgg16 0.67
Vgg19 0.70
ResNet50V2 0.82
MobileNetV2 0.37

07- UTKFace-Age prediction-Regression

  • Train Neural Network on UTKFace dataset using tensorflow and keras

  • train.ipynb

  • inference.py

Dataset:

Dataset link: UTKFace-dataset

inference:

1- First install retina-face

!pip install retina-face

2- Run the following command:

!python3 inference.py --image_path 'input/08.jpg'

08- Gender Recognition

  • Train Neural Network on gender-recognition dataset using tensorflow and keras

  • train.ipynb

  • inference.py

Dataset:

Dataset link: celeba-dataset

10- Houses Price Image Regression

  • Train Neural Network for house price prediction using images

  • train.ipynb

  • inference.py

Reference: KerasRegressionandCNNs

11- DCGAN_on_Mnist_dataset

  • Training DCGAN on Mnist dataset

DCGAN-02

Reference: tensorflow-tutorials

12- DCGAN_on_Celeb_A_dataset

  • Face Generator, Training DCGAN on celeba dataset

DCGAN-Celeb_A-02 (1)

Dataset link: celeba-dataset