eduardoyamao

eduardoyamao's Stars

• amzn/computer-vision-basics-in-microsoft-excel

  Computer Vision Basics in Microsoft Excel (using just formulas)

  2.4k242

• wpeebles/G.pt

  Official PyTorch Implementation of "Learning to Learn with Generative Models of Neural Network Checkpoints"

  Language:Python33220

• alexlenail/NN-SVG

  Publication-ready NN-architecture schematics.

  Language:JavaScript4.5k578

• aharley/pips

  Particle Video Revisited

  Language:Python55049

• hukenovs/hagrid

  HAnd Gesture Recognition Image Dataset

  Language:Python52781

• biasvariancelabs/aitlas

  AiTLAS implements state-of-the-art AI methods for exploratory and predictive analysis of satellite images.

  Language:Python18537

• Megvii-BaseDetection/YOLOX

  YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

  Language:Python9.2k2.2k

• luxonis/depthai-experiments

  Experimental projects we've done with DepthAI.

  Language:Jupyter Notebook801357

• dineshreddy91/WALT

  [CVPR 2022] WALT: Watch And Learn 2D amodal representation from Time-lapse imagery

  Language:Python577

• Seyed-Ali-Ahmadi/Awesome_Satellite_Benchmark_Datasets

  Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.

  Language:Jupyter Notebook30027

• CVEO/OBIC-GCN

  Open-source codes and annotated datasets in CVEO recent work "Object-based Classification Framework of Remote Sensing Images with Graph Convolutional Networks" on IEEE Geoscience and Remote Sensing Letters.

  Language:Python347

• BGU-CS-VIL/DeepDPM

  "DeepDPM: Deep Clustering With An Unknown Number of Clusters" [Ronen, Finder, and Freifeld, CVPR 2022]

  Language:Python74776

• RijulGupta-DM/deepfake-satellite-images

  181

• kilerhg/Python-Studies

  All studies about python

  Language:Python6118

• filipematias23/cleanRfield

  cleanRfield: This package is a compilation of functions to clean and filter observations from yield monitors or other agricultural spatial point data. Yield monitors are prone to error, and filtering the observations or removing observations from near field boundaries can improve estimates of whole-field yield, combine speed, grain moisture, or other parameters. In this package, users can easily select filters thresholding for one or more traits and prepare a smaller dataset to make decisions.

  Language:R403

• jwwangchn/AI-TOD

  Official code for "Tiny Object Detection in Aerial Images".

  Language:Python17818

• hukaixuan19970627/yolov5_obb

  yolov5 + csl_label.(Oriented Object Detection)（Rotation Detection）（Rotated BBox）基于yolov5的旋转目标检测

  Language:Python1.8k421

• danfenghong/ISPRS_S2FL

  Danfeng Hong, JIngliang Hu, Jing Yao, Jocelyn Chanussot, Xiao Xiang Zhu. Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model, ISPRS JP&RS, 2021.

  Language:MATLAB9111

• google-research/pix2seq

  Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)

  Language:Jupyter Notebook84369

• GDAOSU/LOD2BuildingModel

  SAT2LoD2: Automated LoD-2 Model Reconstruction from Satellite-derived DSM and Orthophoto

  Language:Python16131

• QingyongHu/VISO

  [IEEE TGRS 2021] Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

  1259

• InnovAIco/Google-earth-Object-Recognition

  Object recognition in satellite images (Dior Dataset) using RetinaNet and YoloV5

  Language:Jupyter Notebook172

• malshaV/sar_transformer

  Language:Python4811

• janapc/pipeline-order

  This project is a pipeline of orders from the received to the sent product.

  Language:JavaScript3

• KevinMuyaoGuo/yolov5s_for_satellite_imagery

  基于YOLOv5的卫星图像目标检测demo | A demo for satellite imagery object detection based on YOLOv5

  Language:Python19842

• MarilynKeller/OSSO

  From a body shape, infer the anatomic skeleton.

  Language:Python20531

• zyxu1996/Efficient-Transformer

  Online !!! Application of an efficient transformer improved based on Swin transformer on remote sensing segmentation

  Language:Python737

• satellite-image-deep-learning/techniques

  Techniques for deep learning with satellite & aerial imagery

  8.2k1.4k

• retkowsky/Computer_vision_train_station

  Train Station Computer Vision demo

  Language:Jupyter Notebook143

• navinreddy20/Python-

  461457