akshara-ns

akshara-ns's Stars

• tensorflow/models

  Models and examples built with TensorFlow

  Language:Python77.2k2.7k7.3k45.8k

• ultralytics/yolov5

  YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  Language:Python50.8k3699.3k16.4k

• chenfei-wu/TaskMatrix

  Language:Python34.5k3003543.3k

• thuml/Transfer-Learning-Library

  Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

  Language:Python3.4k48202557

• NaturalIntelligence/imglab

  To speedup and simplify image labeling/ annotation process with multiple supported formats.

  Language:HTML98543118608

• Slava/label-tool

  Web application for image labeling and segmentation

  Language:JavaScript35181274

• frankfengdi/LidarMTL

  The official code release of LidarMTL, a simple and efficient multi-task network for 3D object detection and road understanding

  Language:Python1053911

• alexanderlavrushko/BLE-HUD-navigation-ESP32

  Shows navigation instructions received from the phone (e.g. "After 200m turn right")

  Language:C93131026

• Cow911/SingleImageWaterHazardDetectionWithRAU

  Single Image Water Hazard Detection using FCN with Reflection Attention Units

  Language:Python5231117

• IS2AI/kaz-image-captioning

  ExpansionNet v2 model trained on the COCO dataset with captions translated into Kazakh

  Language:Jupyter Notebook31121

• LeadingIndiaAI/Real-Time-Multiple-Object-Detection

  The ability of the computer to locate and identify each object in an image/video is known as object detection. Object detection has many applications in self-driving cars, pedestrian counting, face detection, vehicle detection etc. One of the crucial element of the self-driving car is the detection of various objects on the road like traffic signals, pedestrian’s other vehicles, sign boards etc. In this project, Convolutional Neural Network (CNN) based approach is used for real-time detection of multiple objects on the road. YOLO (You Only Look Once) v2 Deep Learning model is trained on PASCAL VOC dataset. We achieved mAP score of 78 on test dataset after training the model on NVIDIA DGX-1 V100 Super Computer. The trained model is then applied on recorded videos and on live streaming received through web cam.

  Language:Python273115

• shahjui2000/Drive-able-Road-Detection

  This code segments out the drive-able portion of the road from the surrounding.

  Language:Python10115

• GerasymenkoS/semantic-segmentation-editor

  Language:JavaScript6101

• PadmajaVB/listen-attend-and-walk

  Interpreting natural language navigational instructions

  Language:Python4404

• silviaraggi/Social-distancing-and-road-safety-policy-for-blind-people

  Stiamo vivendo un periodo particolare in cui l’attenzione non è mai troppa. La Pandemia ci sta mettendo a dura prova, il virus è un nemico comune che dobbiamo assolutamente abbattere ma l’unico strumento a nostro favore momentaneamente è il rispetto delle regole disposte dal Ministero della Salute per evitare il contagio.Per alcune persone è più complicato poter osservare le normative per la prevenzione contro il Covid-19, per cui il nostro pensiero va alle persone non vedenti che non hanno sempre la possibilità di riuscire a mantenere il social-distancing, ormai divenuto fondamentale per la convivenza in una comunità che ha bisogno, ora più che mai, della collaborazione tra i singoli individui, anche se, purtroppo, non si può sempre far affidamento sul buon senso dei cittadini. La Computer Vision in questo caso, può diventare un ottimo alleato per coloro che hanno bisogno di un’aiuto concreto.

  Language:Python4102

• harishsatishchandra/lane-detection-on-rural-roads

  detection of roads in unlaned scenes using fully convolutional networks (FCN)

  Language:Python3126