Example request: Expand object detection predictions to the original image

What is the task? Object detection

Is this example for a specific model? Not as far as I can tell. What I am wondering about is how to adapt results from the inference phase of the object detection scenario to be displayable over the original image as opposed to transformed sample. Here’s is some code to illustrate

def predict_from_url(image_url):
    # this is just a helper defined previously
    img = image_from_url(image_url)

    infer_tfms = tfms.A.Adapter([*tfms.A.resize_and_pad(384), tfms.A.Normalize()])
    infer_ds = Dataset.from_images([img], infer_tfms)
    infer_dl = faster_rcnn.infer_dl(infer_ds, batch_size=1)
    
    batch, samples = faster_rcnn.build_infer_batch(infer_ds)
    preds = faster_rcnn.predict(model=model, batch=batch)

    imgs = [sample["img"] for sample in samples]
  
    # This works as expected for a sample which are transformed original image (resized and padded)
    #  I would like to understand how to transform BBox'es returned in predictions so i can overlay them over the 
    #  original image 
    show_preds(
        samples=imgs,
        preds=preds,
        class_map=data_class_map,
        denormalize_fn=denormalize_imagenet,
        show=True,
    )

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Don’t remove Main issue for examples: #39

[lgvaz]

@tumbleintoyourheart not right now, but I’m sure other people will have in the community. Join the discord server and ask there =)

[FraPochetti]

This currently works thanks to the end2end_detect function.