Hi! I’m unsure about how to interpret the inference results when using
learn.predict(img) for ImagePoint problems such as the Head Pose problem of Lesson 3. My goal is to collect the predicted coordinates and use them for further processing later. What confuses me is the direct output of
learn.predict(img). It doesn’t seem to make any sense to me.
When printed out,
learn.predict(img) outputs a touple where the first item is the original image shape (120x160 pixels) while 2nd and 3rd items seem to be equal:
(ImagePoints (120, 160),
The predicted coordinates don’t seem to be in the output, but still the correct ImagePoint is displayed with
img.show(y=learn.predict(img)), just like in the Regression example of https://docs.fast.ai/tutorial.inference.html. This is what I don’t get. Even though
img.show() is given the original image shape as
y=ImagePoints (120, 160), it still shows the predicted coordinate correctly on the image. What am I missing here? How can I find and collect the predicted ImagePoint or coordinates when using
learn.predict(img)? Any hints to put me on the right track are highly appreciated!
Thanks a lot for help folks!