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.

A simple banknote recognition convNN

ROCCO - Framework to train Neural Networks for Semantic Segmentation

Apply Albumentations to COCO Dataset

Batch augmentation: paired images plus landmarks

Image Segmentation with UNET

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 and keypoint augmentor based on skimage and imgaug

GPU‑accelerated image augmentation on Apple Silicon with MLX

Explore and build ImgAug augmentations with Supervisely

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

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

Implementation of torchvision-like based on albumentations

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.

Predefined pipelines for image augmentation