AI BioMeasure
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PyQt5_YoLoV5_DeepSort PyQt5_YoLoV5_DeepSort Public
This is a PyQt5 GUI program, which is based on YoloV5 and DeepSort to track person, and give a warning when someone comes to the "dangerous area".
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deepcell-tf deepcell-tf Public
Forked from vanvalenlab/deepcell-tf
Deep Learning Library for Single Cell Analysis
Python 1
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datagym-core datagym-core Public
Forked from datagym-ai/datagym-core
Open source annotation and labeling tool for image and video assets
Java 1
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yolov3_tensorflow yolov3_tensorflow Public
Forked from zhang-minchao/yolov3_tensorflow
Jupyter Notebook
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Repositories
- labelGo-Yolov5AutoLabelImg Public Forked from cnyvfang/labelGo
💕YOLOV5 semi-automatic annotation tool (Based on labelImg)💕基于labelImg及YOLOV5的图形化半自动标注工具
- SAM_aggregate_detection Public Forked from caethugo/SAM_aggregate_detection
I tried to process cornea cells images in order to detect and classify some aggregates in it, using Meta's Segment-Anything-Model.
- Awesome-Segment-Anything Public Forked from Vision-Intelligence-and-Robots-Group/Awesome-Segment-Anything
A collection of project, papers, and source code for Meta AI's Segment Anything Model (SAM) and related studies.
- QuantumDeviceSEM Public Forked from shanto268/QuantumDeviceSEM
This program is designed to analyze Scanning Electron Microscope (SEM) images, specifically images of superconducting quantum devices. It uses the Segment Anything library from Meta to identify and segment objects in the image.
- Polyp-SAM Public Forked from ricklisz/Polyp-SAM
This repo contains the code and model weights for Polyp-SAM
- detection-to-segmentation Public Forked from fzhsbc/detection-to-segmentation
use SAM(segment anything) to transfer detection label to segmentation 利用segment anything把目标检测标注转化为实例分割标注
- napari-segment-anything Public Forked from royerlab/napari-segment-anything
Segment Anything Model (SAM) native Qt UI
- Count-Anything Public Forked from ylqi/Count-Anything
This method uses Segment Anything and CLIP to ground and count any object that matches a custom text prompt, without requiring any point or box annotation.
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