labelme
sentinel2-cloud-detector
Our great sponsors
| labelme | sentinel2-cloud-detector | |
|---|---|---|
| 6 | 3 | |
| 12,300 | 399 | |
| 3.0% | 3.5% | |
| 8.9 | 5.9 | |
| 10 days ago | 4 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Creative Commons Attribution Share Alike 4.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
labelme
-
labelme VS anylabeling - a user suggested alternative
2 projects | 15 Apr 2023
-
Use cases for PySide
Image, 3D, or data visualization applications using OpenCV and the SciPy ecosystem. The Graphics View Framework can display an image and let the user interact with it, and the Python ecosystem is very rich for image processing, data analysis, and visualization. For example, LabelMe for image labeling, PyQtGraph for scientific graphics, or custom QWidget integration in Maya.
- [D] What is a free tool for generating image segmentation masks?
-
Convert Yolov3 annotation to labelme
Ref. - https://github.com/wkentaro/labelme/
-
Mask RCNN Implementation for Image Segmentation | Tutorial
LabelMe is open-source tool for polygen image annotations inspired by MIT Label Me
-
C++ trainable semantic segmentation models
Create your own dataset. Using labelme through "pip install" and label your images. Split the output json files and images into folders just like below:
sentinel2-cloud-detector
-
Earth 2020 in 3 seconds, extracted from over 3 petabytes of satellite data | [OC]
You can find more info in this Jupyter notebook example, the first part is downloading the data (for this you need the account), but if you start later on with the assumption that you bring the data yourself. You can open the ticket if you run into any issues :)
What are some alternatives?
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
biodivMapR - biodivMapR: an R package for α- and β-diversity mapping using remotely-sensed images
Mask-RCNN-Implementation - Mask RCNN Implementation on Custom Data(Labelme)
eoreader - Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
Swin-Transformer-Semantic-Segmentation - This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Semantic Segmentation.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
bpycv - Computer vision utils for Blender (generate instance annoatation, depth and 6D pose by one line code)
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
anylabeling - Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything, MobileSAM!!
json - JSON for Modern C++