gtdong-ustc's repositories
LiDARSceneFlow
[CVPR 2022] "Exploiting Rigidity Constraints for LiDAR Scene Flow Estimation"
tof-mpi-remove
ECCV2020_Spatial Hierarchy Aware Residual Pyramid Network for Time-of-Flight Depth Denoising
Agricultural-Price-Prediction-and-Visualization-on-Android-App
In Agriculture Price Monitioring , I have used data provided by open government site data.gov.in, which updates prices of market daily . Working Interface Details: We have provided user choice to see current market prices based on two choices: market wise or commodity wise use increase assesibility options. Market wise: User have to provide State,District and Market name and then select market wise button. Then user will be shown the prices of all the commodities present in the market in graphical format, so that he can analyse the rates on one scale. This feature is mostly helpful for a regular buyer to decide the choice of commodity to buy. He is also given feature to download the data in a tabular format(csv) for accurate analysis. Commodity Wise: User have to provide State,District and Commodity name and then select Commodity wise button. Then user will be shown the prices of all the markets present in the region with the commodity in graphical format, so that he can analyse the cheapest commodity rate. This feature is mostly helpful for wholesale buyers. He is also given feature to download the data in a tabular format(csv) for accurate analysis. On the first activity user is also given forecasting choice. It can be used to forecast the wholesale prices of various commodities at some later year. Regression techniques on timeseries data is used to predict future prices. Select the type of item and click link for future predictions. There are 3 java files Forecasts, DisplayGraphs, DisplayGraphs2 ..... Please change the localhost "server_name" at time of testing as the server name changes each time a new server is made. Things Used: We have used pandas , numpy , scikit learn , seaborn and matplotlib libraries for the same . The dataset is thoroughly analysed using different function available in pandas in my .iPynb file . Not just in-built functions are used but also many user made functions are made to make the working smooth . Various graphs like pointplot , heat-map , barplot , kdeplot , distplot, pairplot , stripplot , jointplot, regplot , etc are made and also deployed on the android app as well . To integrate the android app and machine learning analysis outputs , we have used Flask to host our laptop as the server . We have a separate file for the Flask as server.py . Where all the the necessary stuff of clint request and server response have been dealt with . We have used npm package ngrok for tunneling purpose and hosting . A different .iPynb file is used for the time series predictions using regression algorithms and would send the csv file of prediction along with the graph to the andoid app when given a request .
All4Depth
Self-Supervised Depth Estimation on Monocular Sequences
cryptofeed
Cryptocurrency Exchange Feed Handler with synthetic NBBO
deepBoosting
Deep Boosting for Image Denoising in ECCV 2018 and its Real-world Extension in IEEE Transactions on Pattern Analysis and Machine Intelligence
dopamine
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
ERRNet
Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements (CVPR 2019)
fast-depth
ICRA 2019 "FastDepth: Fast Monocular Depth Estimation on Embedded Systems"
gin-config
Gin provides a lightweight configuration framework for Python
MegaDepth
Code of single-view depth prediction algorithm on Internet Photos described in "MegaDepth: Learning Single-View Depth Prediction from Internet Photos, Z. Li and N. Snavely, CVPR 2018".
Monocular_Depth_Estimation
Learning Depth from Monocular Videos using Direct Methods, CVPR 2018
PI-REC
:fire: PI-REC: Progressive Image Reconstruction Network With Edge and Color Domain. :fire: 图像翻译，条件GAN，AI绘画
PlanarSegmentation
Segmentation of a video frame into ground and upright objects using sparse and dense optical flow techniques in OpenCV.
plane_fit_ground_filter
3D lidar recognition and segmentation of ground
plant-seg
A tool for cell instance aware segmentation in densely packed 3D volumetric images
recurrent_tof_denoising
recurrent_tof_denoising
Revisiting_Single_Depth_Estimation
official implementation of "Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries"
seq2seq
A general-purpose encoder-decoder framework for Tensorflow
SfM_Depth_Estimation
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
StanfordDoggoProject
Stanford Doggo is an open source quadruped robot that jumps, flips, and trots!
synthetic-computer-vision
A list of synthetic dataset and tools for computer vision
Synthetic2Realistic
ECCV 2018 "T2Net: Synthetic-to-Realistic Translation for Depth Estimation Tasks"
tof-stereo-fusion
ToF-Stereo Sensor Fusion with Deep Learning
tof_rgbd_processing
Off-the-shelf deep alignment and refinement for weakly calibrated ToF RGB-D modules
ToolsPorject
option value prediction
VI-Stereo-DSO
Direct sparse odometry combined with stereo cameras and IMU