Metadata-Version: 2.1
Name: dnnlab
Version: 1.2.9
Summary: DnnLab
Home-page: UNKNOWN
Author: Tobias Hoefer, Kevin Hirschmann Frederik Weishaeupl
Author-email: tobias.hoefer.hm@gmail.com,  kevin.hirschmann@noventi.de, Frederik.Weishaeupl@noventi.de
License: UNKNOWN
Description: # DnnLab
        Dnnlab is a small framework for deep learning models based on TensorFlow.
        
        
        
        It provides custom training loops for:
        * Generative Models (GAN, cGan, cycleGAN)
        * Image Detection (custom YOLO)
        
        
        Additonaly custom Keras Layer:
        * Non-Local-Blocks (Self-Attention)
        * Squeeze and Excitation Blocks (SEBlocks)
        * YOLO-Decoding Layer
        
        Input pipeline functionality:
        * YOLO (Tfrecords to Datasets)
        * YOLO data augmentation
        * Generative Models (Tfrecords to Datasets)
        
        TensorBoard output:
        * YOLO coco metrics (Precision (mAP) & Recall)
        * YOLO loss (loss_class, loss_conf, loss_xywh, total_loss)
        * YOLO bounding boxes
        * Generative Models (Loss & Images)
        
        
        ## Requirements
        TensorFlow 2.3.0
        
        ## Installation
        Run the following to install:
        ```python
        pip install dnnlab
        ```
        
        
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: dev
