| aymericdamien/TensorFlow-Examples |
43,109 |
|
0 |
0 |
about 2 years ago |
0 |
|
218 |
other |
Jupyter Notebook |
| TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) |
| matterport/Mask_RCNN |
23,745 |
|
0 |
0 |
over 2 years ago |
5 |
March 05, 2019 |
1,993 |
other |
Python |
| Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow |
| huggingface/datasets |
17,925 |
|
9 |
760 |
about 2 years ago |
76 |
November 16, 2023 |
665 |
apache-2.0 |
Python |
| 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools |
| opencv/cvat |
10,831 |
|
0 |
3 |
about 2 years ago |
23 |
November 27, 2023 |
504 |
mit |
TypeScript |
| Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. |
| activeloopai/deeplake |
8,989 |
|
0 |
31 |
2 months ago |
118 |
December 08, 2023 |
68 |
apache-2.0 |
C++ |
| Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai |
| carpedm20/DCGAN-tensorflow |
6,761 |
|
0 |
0 |
over 5 years ago |
0 |
|
183 |
mit |
JavaScript |
| A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks" |
| cchen156/Learning-to-See-in-the-Dark |
5,326 |
|
0 |
0 |
about 3 years ago |
0 |
|
71 |
mit |
Python |
| Learning to See in the Dark. CVPR 2018 |
| tensorflow/datasets |
4,094 |
|
51 |
163 |
about 2 years ago |
36 |
September 08, 2023 |
653 |
apache-2.0 |
Python |
| TFDS is a collection of datasets ready to use with TensorFlow, Jax, ... |
| YunYang1994/tensorflow-yolov3 |
3,596 |
|
0 |
0 |
over 3 years ago |
0 |
|
490 |
mit |
Python |
| 🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement" |
| CLUEbenchmark/CLUE |
3,345 |
|
0 |
0 |
almost 3 years ago |
0 |
|
73 |
|
Python |
| 中文语言理解测评基准 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard |
