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YOLOv7 for ISU 2023 AI Workshop

Official YOLOv7

Installation

conda create -n yolov7
conda activate yolov7

# pip install required packages
conda install pip
pip install -r requirements.txt

Demo

  • Colab link

  • Run locally

    • Launch jupyterlab and open demo.ipynb
    jupyter lab 
    • If no curl on your system, download the model weight with [this link] and move it under this folder
    • The object classes that can be detected are:
    person, bicycle, car, motorcycle, airplane, bus, train, truck, boat, traffic light, fire hydrant, stop sign, parking meter, bench, bird, cat, dog, horse, sheep, cow, elephant, bear, zebra, giraffe, backpack, umbrella, handbag, tie, suitcase, frisbee, skis, snowboard, sports ball, kite, baseball bat, baseball glove, skateboard, surfboard, tennis racket, bottle, wine glass, cup, fork, knife, spoon, bowl, banana, apple, sandwich, orange, broccoli, carrot, hot dog, pizza, donut, cake, chair, couch, potted plant, bed, dining table, toilet, tv, laptop, mouse, remote, keyboard, cell phone, microwave, oven, toaster, sink, refrigerator, book, clock, vase, scissors, teddy bear, hair drier, toothbrush