Notebooks

Computer Vision and Deep Learning IPython notebooks

Computer Vision and Image Processing

Custom_Object_Detector_using_yolov3.ipynb

Training Custom Object Detector using yolov3

Transfer_learning_based_classifier_to_classify_benign_malignant_tumor.ipynb

Training Transfer learning based classifier to classify benign/malignant tumor on Warwick QU Dataset on MobileNetV2

Using_Otsu’s_method_for_segmentation.ipynb

Using Otsu’s method to generate data for training of deep learning image segmentation models.

Multi_class_classifier_to_recognize_sign_language.ipynb

Multi class classifier to recognize sign language

Horses_vs_humans_using_Transfer_Learning.ipynb

Horses and humans classification using pre-trained InceptionV3 Network

GAN_keras.ipynb

Simple GAN trained on MNIST dataset

GAN_PyTorch.ipynb

Simple GAN trained on MNIST dataset

Cats_vs_Dogs_classifier.ipynb

Classify cats and dogs

Blurring_image.ipynb

Blurring image using opencv

Thresholding_image.ipynb

Thresholding image using opencv

Handwriting_digits_recognition.ipynb

Handwriting digits recognition on MNIST without convolutions

Intel_image_classification_from_kaggle_dataset.ipynb

Classification of Natural Scenes.

unet_keras.ipynb

Implementaion of unet in keras.

mask_rcnn_keras.ipynb

Using Mask RCNN to segment images

Data preprocessing

Downloading_dataset_from_kaggle.ipynb

Download dataset from kaggle to local system.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT