Log inference results to Weights & Biases

[soumik12345]

Optionally log inference results in Weights & Biases dashboard using bounding-box image overlays.

Add an optional parameter visualize_on_wandb to ImagesDetectionPrediction.show() which when set to True would log the predictions using the bounding-box image overlays in the Weights & Biases dashboard of the user.

Here's a sample code:

from super_gradients.training import models
from super_gradients.common.object_names import Models

import wandb

# Initialize Weights & Biases run
wandb.init(project="yolo-nas", entity="geekyrakshit")

net = models.get(Models.YOLO_NAS_S, pretrained_weights="coco")
prediction = net.predict([
    "https://cdn.autonomous.ai/static/upload/images/common/upload/20210919/5-Desk-Setup-with-a-Laptop--Monitor-Ideas-for-2021_10f89201411b.jpg",
    "https://p.imgci.com/db/PICTURES/CMS/352000/352019.jpg",
    "https://p.imgci.com/db/PICTURES/CMS/352200/352298.jpg",
    "https://www.encirclephotos.com/wp-content/uploads/Laos-Ban-Pak-Ou-Man-Riding-Asian-Elephant-1440x961.jpg"
])
prediction.show(visualize_on_wandb=True)

This would log the images to be visualized in a media panel in a Weights & Biases dashboard.

Here's how the results would look 👇

Here's a video of how to interact with the bounding-box overlay interface on Weights & Biases 👇

Screen.Recording.2023-05-09.at.6.24.17.PM.mov

[dagshub]

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