Metadata-Version: 2.1
Name: easy-inference
Version: 0.1.1
Summary: Got a working detection model file? Want to quickly setup inference pipelines? You are in the right place!
Home-page: UNKNOWN
Author: Chadi Salmi
License: MIT
Description: # Easy Inference
        
        Welcome to the easy inference repository! The main goal of this repository is to provide a clean, simple and short way of setting up inference pipelines for 2D (and 3D) visual detection.
        The interfaces to camera drivers are abstracted away as python `generators`. A simple inference pipeline for a webcam based inference pipeline looks as follows:
        
        ```Python3
        from easy_inference.providers.webcam import Webcam
        
        provider = Webcam(source=0)
        
        for frame in provider:
        
          # run my detection 
        ```
        
        See the examples directory for some `yolov7` pipelines.
        
        
        ### Sidenote
        
        Many examples is this repository include `yolov7` pipelines using the onnx-runtime. To generate onnx model files follow the steps on the yolov7 repository [readme](https://github.com/WongKinYiu/yolov7/blob/8c0bf3f78947a2e81a1d552903b4934777acfa5f/README.md?plain=1#L156).
        
        To export a model for yolov7 including pose detection, checkout the following branch of [yolov7](https://github.com/WongKinYiu/yolov7/tree/pose) and download the pytorch model [yolov7-w6-pose.pt](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-w6-pose.pt). Then run the following to export an onnx model with your desired configuration:
        
        ```bash
        cd yolov7
        python models/export.py --weights yolov7-w6-pose.pt --grid --simplify --export-nms --batch-size 2 --img-size 512 640
        ```
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: ros
