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roboflow / notebooks

Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
https://roboflow.com/models
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fixed super-gradient installation on yolo-nas notebook #201

Open arrafi-musabbir opened 1 year ago

arrafi-musabbir commented 1 year ago

Description

The current method !pip install -q super-gradients==3.1.1 to install super-gradient from pip results in pycocotools build failure. I followed the deci-ai's repository and found the proper way to install it. The following command will result in a successful installation: !pip install git+https://github.com/Deci-AI/super-gradients.git@stable

Type of change

Please delete options that are not relevant.

How has this change been tested, please provide a testcase or example of how you tested the change?

I just changed the way super-gradient package was being installed previously !pip install git+https://github.com/Deci-AI/super-gradients.git@stable

Any specific deployment considerations

For example, documentation changes, usability, usage/costs, secrets, etc.

Docs

In the Install YOLO-NAS block I fixed the way super-gradient is supposed to be installed correctly

I replaced this line !pip install -q super-gradients==3.1.1 with this: !pip install git+https://github.com/Deci-AI/super-gradients.git@stable

Now the pycocotools build failure is resolved.

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