This repository contains various Image Classification projects which have been built using TensorFlow.
Tech. Stack :
- Python
- TensorFlow/Keras
- NumPy
- OpenCV
- PIL (pillow)
- tkinter
- Sci-kit Learn
- Matplotlib
- DNN Caffe Models - face detection
- mobilenet_v2 base model with pre-trained weights of 'imagenet'
Categories :
- Image Classification (Computer Vision)
- Deep Learning
- Transfer Learning
- Real-time Face Detection
- Image Augmentation
- Neural Network Architucture Implementation
- Model Evaluation
- It's binary class classification task - (People Wearing Mask & Without Mask)
- For Face Detection DNN based caffe model has been used.
- For Model training I have used Transfer Learning with 'mobilenet_v2' Neural Network base model with pre-trained weights of 'imagenet'.
- Made it Real-time with the help of OpenCV.
- It's multi-class classification task - (Predict digit between 0 to 9)
- Dataset Used : MNIST digit
- Deep Learning Model has been built in TensorFlow/Keras from scratch and trained using CNNs.
- With the help of OpenCV it's possible to detect Multiple Digits in Canvas made in tkinter.
- Detected digits are passed to Model for Prediction.
- It's multi-class classification task - (Predict Rock, Paper & Scissors)
- Animated Dataset has been used.
- Able to got ~98% Validation accuracy.
- Correclty classify all the unseen images except only 1.
- Note : Data Label - Paper 0, Rock 1, Scissors 2
- It's multi-class classification task - (Predict digit between 0 to 9)
- LeNet Architecture has been used for Image Classification on MNIST handwritten digit dataset.
- It's multi-class classification task - (Predict between 10 different classes)
- MiniVGGNet Architecture has been used for Image Classification on cifar10 dataset.
Note : For in-depth details go to respective links.