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

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

ROCCO - Framework to train Neural Networks for Semantic Segmentation

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

A simple banknote recognition convNN

Apply Albumentations to COCO Dataset

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

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

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

🐱 Classify cat and dog images using a convolutional neural network in Python with TensorFlow, enhancing your machine learning skills and understanding of image recognition.

Batch augmentation: paired images plus landmarks

Apply some image augmentation techniques for better classification

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.

Full experimentation notebook for my Keras Example on using RandAugment.

Implementation of torchvision-like based on albumentations

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

Predefined pipelines for image augmentation

Explore and build ImgAug augmentations with Supervisely