sandhyacs

3d-bat

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

Advanced-Deep-Learning-with-Keras

Advanced Deep Learning with Keras, published by Packt

aistplusplus_api

API to support AIST++ Dataset: https://google.github.io/aistplusplus_dataset

Andrew-NG-Notes

This is Andrew NG Coursera Handwritten Notes.

handtracking-with-Mediapipe

Hand tracking with Google Mediapipe and Tensorflow demo app

heic2JPGConverter

heictojpgconverter

historical_data

Programming-books

Books on programming and computer science

sandhyacs/3d-bat

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

sandhyacs/Andrew-NG-Notes

This is Andrew NG Coursera Handwritten Notes.

sandhyacs/heic2JPGConverter

sandhyacs/heictojpgconverter

sandhyacs/historical_data

sandhyacs/cnn-facial-landmark

Training code for facial landmark detection based on deep convolutional neural network.

sandhyacs/dlibproject

sandhyacs/draw3daxis

sandhyacs/ExifDataReader

sandhyacs/facial-landmark-detection-hrnet

A TensorFlow implementation of HRNet for facial landmark detection.

sandhyacs/feizbus

sandhyacs/feizbus1

sandhyacs/flaskproject

sandhyacs/Grocery-Product-Detection

This repository builds a product detection model to recognize products from grocery shelf images.

sandhyacs/image-segmentation-keras

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

sandhyacs/keras-io

Keras documentation, hosted live at keras.io

sandhyacs/landmarkpointssmoothening

sandhyacs/logger

sandhyacs/mb3-centernet

CenterNet: Tiny Object Detection for TFJS and NodeJS

sandhyacs/MeshTransformer

Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"

sandhyacs/NN-SVG

Publication-ready NN-architecture schematics.

sandhyacs/PacalvoctoJsonConversion

sandhyacs/PINTO_model_zoo

A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]

sandhyacs/PygenderCustom

sandhyacs/retinanet-examples

Fast and accurate object detection with end-to-end GPU optimization

sandhyacs/SelfieBarracuda

MediaPipe Selfie segmentation model on Unity Barracuda

sandhyacs/tflite2tensorflow

Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite, ONNX, OpenVINO, Myriad Inference Engine blob and .pb from .tflite. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support.

sandhyacs/tfliteconverter

sandhyacs/UniPose

We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.

sandhyacs/zipcreationofnestedfolder