> -----Original Message-----
> From: ffmpeg-devel <ffmpeg-devel-boun...@ffmpeg.org> On Behalf Of
> Lynne
> Sent: 2021年4月9日 18:03
> To: FFmpeg development discussions and patches
> <ffmpeg-devel@ffmpeg.org>
> Subject: Re: [FFmpeg-devel] [PATCH V7 4/6] lavu: add side data
> AV_FRAME_DATA_BOUNDING_BOXES
>
> Apr 9, 2021, 06:12 by yejun....@intel.com:
>
> >
> >
> >> -----Original Message-----
> >> From: ffmpeg-devel <ffmpeg-devel-boun...@ffmpeg.org> On Behalf Of
> Lynne
> >> Sent: 2021年4月9日 0:57
> >> To: FFmpeg development discussions and patches
> <ffmpeg-devel@ffmpeg.org>
> >> Subject: Re: [FFmpeg-devel] [PATCH V7 4/6] lavu: add side data
> >> AV_FRAME_DATA_BOUNDING_BOXES
> >>
> >
> > First of all, thanks for the quick replies, I see, all the
> discussions/comments are to
> > make this patch better, thank you.
> >
> >> >> >
> >> >> >> >> > +
> >> >> >> >> > +typedef struct AVBoundingBoxHeader {
> >> >> >> >> > + /**
> >> >> >> >> > + * Information about how the bounding box is
> generated.
> >> >> >> >> > + * for example, the DNN model name.
> >> >> >> >> > + */
> >> >> >> >> > + char source[128];
> >> >> >> >> > +
> >> >> >> >> > + /**
> >> >> >> >> > + * The size of frame when it is detected.
> >> >> >> >> > + */
> >> >> >> >> > + int frame_width;
> >> >> >> >> > + int frame_height;
> >> >> >> >> >
> >> >> >> >>
> >> >> >> >> Why? This side data is attached to AVFrames only, where we
> >> >> >> >> already have width and height.
> >> >> >> >>
> >> >> >> >
> >> >> >> > The detection result will be used by other filters, for example,
> >> >> >> > dnn_classify (see
> https://github.com/guoyejun/ffmpeg/tree/classify).
> >> >> >> >
> >> >> >> > The filter dnn_detect detects all the objects (cat, dog, person
> >> >> >> > ...)
> in a
> >> >> >> > frame, while dnn_classify classifies one detected object (for
> example,
> >> >> person)
> >> >> >> > for its attribute (for example, emotion, etc.)
> >> >> >> >
> >> >> >> > The filter dnn_classify have to check if the frame size is changed
> after
> >> >> >> > it is detected, to handle the below filter chain:
> >> >> >> > dnn_detect -> scale -> dnn_classify
> >> >> >> >
> >> >> >>
> >> >> >> This doesn't look good. Why is dnn_classify needing to know
> >> >> >> the original frame size at all?
> >> >> >>
> >> >> >
> >> >> > For example, the original size of the frame is 100*100, and
> dnn_detect
> >> >> > detects a face at place (10, 10) -> (30, 40), such data will be saved
> >> >> > in
> >> >> > AVBoundingBox.top/left/right/bottom.
> >> >> >
> >> >> > Then, the frame is scaled into 50*50.
> >> >> >
> >> >> > Then, dnn_classify is used to analyze the emotion of the face, it
> needs to
> >> >> > know the frame size (100*100) when it is detected, otherwise, it
> does not
> >> >> > work with just (10,10), (30,40) and 50*50.
> >> >> >
> >> >>
> >> >> Why can't the scale filter also rescale this side data as well?
> >> >>
> >> >
> >> > I'm afraid that we could not make sure all such filters (including
> >> > filters
> in the
> >> > future) to do the rescale. And in the previous discussion, I got to
> know that
> >> > 'many other existing side-data types are invalidated by scaling'.
> >> >
> >> > So, we need frame_width and frame_height here.
> >> >
> >>
> >> No, you don't. You just need to make sure filters which change
> resolution
> >> or do cropping also change the side data parameters.
> >> It's called maintainership. As-is, this won't even work with cropping,
> >> only with basic aspect ratio preserving scaling.
> >> For the lack of a better term, this is a hack.
> >>
> >
> > As discussed in previous email, for the frame size change case,
> dnn_classify
> > (and other filters which use the detection result, for example drawbox)
> can
> > just output a warning message to tell user what happens, and don't do
> the
> > classification, otherwise, it will give a wrong/weird result which makes
> the
> > user confused.
> >
> >>
> >> I would accept just specifying that if the frame dimensions are
> >> altered in any way, the side-data is no longer valid and it's up
> >> to users to figure that out by out of bound coordinates.
> >> This is what we currently do with video_enc_params.
> >>
> >
> > frame_width/frame_height is not perfect (for the cases such as: scale
> down
> > + crop + scale up to the same size), but it provides more info than the
> checking
> > of 'out of bound coordinates'. There are many other possible issues
> when the
> > coordinates are within the frame.
> >
> > If we think we'd better not let user get more info from the warning
> message,
> > I'm ok to remove them.
> >
> > I'll remove them if there's another comment supporting the removal, and
> > there's no objection.
> >
>
> We definitely shouldn't include variables in public API structs
> that only serve to print a warning if they don't match.
Not just 'print a warning', it also impacts the behavior of dnn_classify.
> Especially one that's fragile and flawed like this one.
> Users should know that scaling or altering a frame could break
> this side data, and filters could detect obvious out of bounds
> results and report them.
I'll remove them since it is user's responsibility.
>
> In the meantime, the main scaling and cropping filters could
> receive separate patches to preserve metadata at a later data.
> This is how the avframe cropping field work - they're just metadata,
> and cropping/scaling filters update those.
>
>
> >> >> >> >> > diff --git a/libavutil/frame.h b/libavutil/frame.h
> >> >> >> >> > index a5ed91b20a..41e22de02a 100644
> >> >> >> >> > --- a/libavutil/frame.h
> >> >> >> >> > +++ b/libavutil/frame.h
> >> >> >> >> > @@ -198,6 +198,13 @@ enum AVFrameSideDataType {
> >> >> >> >> > * Must be present for every frame which should have film
> grain
> >> >> applied.
> >> >> >> >> > */
> >> >> >> >> > AV_FRAME_DATA_FILM_GRAIN_PARAMS,
> >> >> >> >> > +
> >> >> >> >> > + /**
> >> >> >> >> > + * Bounding boxes for object detection and
> classification, the
> >> >> data is
> >> >> >> a
> >> >> >> >> AVBoundingBoxHeader
> >> >> >> >> > + * followed with an array of AVBoudingBox, and
> >> >> >> >> AVBoundingBoxHeader.nb_bboxes is the number
> >> >> >> >> > + * of array element.
> >> >> >> >> > + */
> >> >> >> >> > + AV_FRAME_DATA_BOUNDING_BOXES,
> >> >> >> >> > };
> >> >> >> >> >
> >> >> >> >>
> >> >> >> >> Finally, why call it a Bounding Box? It's not descriptive at all.
> >> >> >> >> How about "Object Classification"? It makes much more sense,
> it's
> >> >> >> >> exactly what this is. So AVObjectClassification,
> AVObjectClassification,
> >> >> >> >> AV_FRAME_DATA_OBJECT_CLASSIFICATION and so on.
> >> >> >> >>
> >> >> >> >
> >> >> >> > In object detection papers, bounding box is usually used.
> >> >> >> > We'd better use the same term, imho, thanks.
> >> >> >> >
> >> >> >>
> >> >> >> Not in this case, API users won't have any idea what this is or
> what
> >> >> >> it's for. This is user-facing code after all.
> >> >> >> Papers in fields can get away with overloading language, but
> we're
> >> >> >> trying to make a concise API. Object classification makes sense
> >> >> >> because this is exactly what this is.
> >> >> >>
> >> >> >
> >> >> > The term bounding box is dominating the domain, for example,
> even
> >> >> > HEVC spec uses this term, see page 317 of
> >> >> >
> >> >>
> >>
> https://www.itu.int/rec/dologin_pub.asp?lang=e&id=T-REC-H.265-201911-I
> !!P
> >> >> DF-E&type=items
> >> >> >
> >> >> > also copy some here for your convenient.
> >> >> > ar_bounding_box_top[ ar_object_idx[ i ] ] u(16)
> >> >> > ar_bounding_box_left[ ar_object_idx[ i ] ] u(16)
> >> >> > ar_bounding_box_width[ ar_object_idx[ i ] ] u(16)
> >> >> > ar_bounding_box_height[ ar_object_idx[ i ] ] u(16)
> >> >> >
> >> >> > I would prefer to use bounding box.
> >> >> >
> >> >>
> >> >> It's for an entirely different thing, and like I said, it's just an
> overloaded
> >> >> language because they can get away. We're trying to be generic.
> >> >> This side data is for detecting _and_ classifying objects. In fact, most
> of
> >> >> the structure is dedicated towards classifying. If you'd like users to
> actually
> >> >> use this, give it a good name and don't leave them guessing what
> this
> >> >> structure is by throwing vague jargon some other paper or spec has
> >> >> because it's close enough.
> >> >>
> >> >
> >> > all the people in the domain accepts bounding box, they can
> understand this
> >> > struct name easily and clearly, they might be bothered if we use
> another
> >> name.
> >> >
> >> > btw, AVObjectClassification confuses people who just want object
> detection.
> >> >
> >>
> >> As I said, the name "bounding box" makes no sense once it gets
> overloaded
> >> with object classification.
> >>
> >
> > dnn_detect creates an array of 'bounding box' for all detected objects,
> and
> > dnn_classify assigns attributes for a set of bounding boxes (with same
> object
> > id). 'bounding box' serves both detection and classification properly.
> >
> >
> >> Object classification is still the main use of the filters,
> >> because the original proposal was to have all of this info be
> ffmpeg-private,
> >> which would forbid simple object detection.
> >>
> >
> > The original proposal is to add it as side data which is ffmpeg-public, and
> then,
> > we spent much time discussing/trying with ffmpeg-private as an
> temporary
> > method, and since it is not good to be temporary, we now switch back to
> > ffmpeg-public.
> >
> > During the whole period, we don't have any intention to
> > 'forbid simple object detection', not quite understand your point here.
> >
> >
> >> So I still maintain this should be called "Object classification". I'd
> >> accept
> >> "Object detection" as well, but definitely not "bounding box".
> >>
> >
> > imho, ' Object detection' and ' Object classification' are worse, they just
> > describe one aspect of the struct. The users might just use filter
> dnn_detect,
> > they might use filters dnn_detect + dnn_classify.
> >
>
> The whole reason why we have this side data is to both detect
> _and_ classify. Keyword being _both_. Hence object detection
> and object classification are much better names.
> I am opposed to merging this without a name change.
I understand it is not a good name with codec background, but it is a good
(possible best) name with object detection background.
To make things move forward, I'll change the name to 'object detection'
for both dnn_detect and dnn_classify, they would be:
AV_FRAME_DATA_OJBECT_DETECTION
AVObjectDetection
AVObjectDetectionHeader
>
>
> >> Since the decision was made to make the side data public, we have to
> make
> >> very sure it contains no hacks or is impossible to extend, since we don't
> want
> >> to have an
> >>
> "AV_SIDE_DATA_OBJECT_CLASSIFICATION_VERSION_2_SORRY_WE_SCREWE
> D_
> >> UP"
> >> faster than you can say "Recursive cascade correlation artificial neural
> >> networks".
> >>
> >
> > sorry, not quite understand your point here.
> >
>
> The point of this paragraph was to highlight the need to have other
> people look at the struct rather than just you. It's called peer review.
> It wasn't anything about the name at all.
sure, comments are welcome. And the struct has got many comments and
improved a lot in the past two months. Thanks all again.
> > 'bounding box' is designed for general purpose to contain the info for
> > detection/classification. It doesn't matter which DNN model is used, it
> > doesn't
> > matter if a traditional algorithm (non-dnn) is used.
> >
> > I'm open to use a better name. And bounding box is the best one for me
> > till now.
> > Everyone in the domain knows the exact meaning of bounding box
> > without
> > extra explanation. This word has been extended/evolved with such
> > meaning in
> > this domain.
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