| hybridgroup/gocv |
5,973 |
|
0 |
154 |
about 2 years ago |
54 |
October 12, 2023 |
302 |
other |
Go |
| Go package for computer vision using OpenCV 4 and beyond. |
| idealo/image-super-resolution |
4,392 |
|
0 |
0 |
over 2 years ago |
0 |
|
106 |
apache-2.0 |
Python |
| 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks. |
| exadel-inc/CompreFace |
3,570 |
|
0 |
0 |
about 2 years ago |
0 |
|
173 |
apache-2.0 |
Java |
| Leading free and open-source face recognition system |
| facebookresearch/habitat-lab |
1,565 |
|
0 |
0 |
about 2 years ago |
0 |
|
269 |
mit |
Python |
| A modular high-level library to train embodied AI agents across a variety of tasks and environments. |
| opendatacam/opendatacam |
1,521 |
|
0 |
0 |
over 2 years ago |
0 |
|
43 |
mit |
JavaScript |
| An open source tool to quantify the world |
| gnes-ai/gnes |
1,095 |
|
0 |
0 |
over 6 years ago |
0 |
|
16 |
other |
Python |
| GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network. |
| BMW-InnovationLab/BMW-TensorFlow-Training-GUI |
954 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy. |
| StanfordVL/GibsonEnv |
814 |
|
0 |
0 |
about 2 years ago |
0 |
|
48 |
mit |
C |
| Gibson Environments: Real-World Perception for Embodied Agents |
| roboflow/inference |
716 |
|
0 |
0 |
about 2 years ago |
17 |
December 05, 2023 |
7 |
other |
Python |
| A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models. |
| BMW-InnovationLab/BMW-YOLOv4-Training-Automation |
630 |
|
0 |
0 |
almost 3 years ago |
0 |
|
9 |
bsd-3-clause |
Python |
| This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy. |
