The Oxford-IIIT-Pet dataset - Image classification using CNN

Cross-library augmentation toolbox supporting 300 operators over 8 libraries + AI transforms

Sample implementation codes for a variety of popular image augmentation Python packages

Apply some image augmentation techniques for better classification

Full experimentation notebook for my Keras Example on using RandAugment.

Data Augmentation with PyTorch, Tensorflow, Imgaug and Albumentations. It also involves bounding box augmentation.

Apply Albumentations to COCO Dataset

A simple banknote recognition convNN

ROCCO - Framework to train Neural Networks for Semantic Segmentation

about three thousand images were used for training CNN.It utilized opencv,NumPy,panda,imaging,Keras, TensorFlow,socketio,as major libraries.the neural network worked well on the first track.the model file stored the trained model.elu and softmax activation functions were employed.It can work on workstations without GPU but takes a considerable a…

Image Segmentation with UNET

Image and keypoint augmentor based on skimage and imgaug

Batch augmentation: paired images plus landmarks

Explore and build ImgAug augmentations with Supervisely

Implementation of Segnet, FCN, UNet , PSPNet and other models in Keras.

In this project, we will be doing object detection and segmentation of various things present in provided image

Implementation of torchvision-like based on albumentations

Predefined pipelines for image augmentation

The project leverages a pre-trained Mask R-CNN model fine-tuned on a custom dataset for accurate detection and classification. It includes functionalities for training, inference, and visualization of results, and it can be extended for real-time applications using OpenCV.