Sharib Ali's repositories
annotationTools
tools to extract annotation from AIDA and others
endoscopyDataCuration
Software for data curation and pre-processing
EPSRC-CDT-HDS-M04-DL-Imaging-TeachingMaterial
Basic_deepLearning_exercise
HSI_Analysis_ML
Deep learning and machine learning methods for hyper-spectral imaging data
AdaBins
Official implementation of Adabins: Depth Estimation using adaptive bins
colabtools
Python libraries for Google Colaboratory
ColonSegNet
PyTorch implementation of ColonSegNet in our paper "Real-Time Polyp Detection, Localization and segmentation in Colonoscopy Using Deep Learning" (IEEE Access)
cupy
A NumPy-compatible array library accelerated by CUDA
CVPR2023-CMPAE
[CVPR 2023] Collecting Cross-Modal Presence-Absence Evidence for Weakly-Supervised Audio-Visual Event Perception
DUTCode
Pytorch implementation of DUT: Learning Video Stabilization by Simply Watching Unstable Videos
FLARE
Official Repository of MICCAI FLARE Challenges
IJCAI-2022-ZLA
Codes for IJCAI'2022 Paper: Zero-Shot Logit Adjustment
innvestigate
A toolbox to iNNvestigate neural networks' predictions!
p2ilf-docker
This is a sample docker container created for P2ILF challenge teams
review_object_detection_metrics
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
Segment-and-Track-Anything
An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.
segmenter
[ICCV2021] Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation
shapely
Manipulation and analysis of geometric objects
sharib-vision.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes