Official YOLOv7

• Install conda: [link to miniconda]
• On the terminal:

conda create -n yolov7
conda activate yolov7

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

• 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