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From: <m.kaindl0208@gmail.com>
To: <ffmpeg-devel@ffmpeg.org>
Date: Tue, 25 Mar 2025 12:40:19 +0100
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Hi,
=20
I have been working on this feature =
<https://patchwork.ffmpeg.org/project/ffmpeg/list/?series=3D14066> and =
have completed my project already a while ago. I believe this could be a =
valuable addition to the FFmpeg project and would like to ask whether =
the community is interested in it.
=20
If there is interest, I would appreciate it if someone could co-author =
the submission with me. If the feature is not desired, I will not =
continue working on it.
=20
Furthermore, I would like to know the best approach to add this patch to =
my series. Should I create a new version, or is there a way to link it =
to my commit number 17?
=20
Thanks!
------=_NextPart_000_0272_01DB9D83.11C96710
Content-Type: application/octet-stream;
name="0021-libavfilter-classify-fix-category-post_processing-wi.patch"
Content-Transfer-Encoding: quoted-printable
Content-Disposition: attachment;
filename="0021-libavfilter-classify-fix-category-post_processing-wi.patch"
>From 499de7be409ba7668defac9214a8343344bd21ee Mon Sep 17 00:00:00 2001=0A=
From: MaximilianKaindl <m.kaindl0208@gmail.com>=0A=
Date: Wed, 12 Mar 2025 10:10:58 +0100=0A=
Subject: [PATCH v2 FFmpeg 21/20] libavfilter: classify fix category =
post_processing=0A=
with very low temperature=0A=
To: ffmpeg-devel@ffmpeg.org=0A=
=0A=
Signed-off-by: MaximilianKaindl <m.kaindl0208@gmail.com>=0A=
---=0A=
libavfilter/avf_dnn_classify.c | 24 ++++++++++++++----------=0A=
1 file changed, 14 insertions(+), 10 deletions(-)=0A=
=0A=
diff --git a/libavfilter/avf_dnn_classify.c =
b/libavfilter/avf_dnn_classify.c=0A=
index 7b469e3af0..ade55858ad 100644=0A=
--- a/libavfilter/avf_dnn_classify.c=0A=
+++ b/libavfilter/avf_dnn_classify.c=0A=
@@ -34,6 +34,7 @@=0A=
#include "libavutil/opt.h"=0A=
#include "libavutil/time.h"=0A=
#include "video.h"=0A=
+#include <float.h>=0A=
=0A=
/*=0A=
Labels that are being used to classify the image=0A=
@@ -579,7 +580,7 @@ static int =
get_category_total_label_count(CategoryClassifcationContext *cat_ctx,=0A=
static CategoryContext *get_best_category(CategoriesContext =
*categories_ctx, float *probabilities)=0A=
{=0A=
CategoryContext *best_category =3D NULL;=0A=
- float best_probability =3D -1.0f;=0A=
+ float best_probability =3D FLT_MIN;=0A=
int prob_offset =3D 0;=0A=
=0A=
// Calculate total probability for each category=0A=
@@ -592,7 +593,7 @@ static CategoryContext =
*get_best_category(CategoriesContext *categories_ctx, flo=0A=
category->total_probability +=3D probabilities[prob_offset =
+ label_idx];=0A=
}=0A=
=0A=
- if (category->total_probability > best_probability) {=0A=
+ if (category->total_probability > best_probability && =
category->total_probability > 0.0f) {=0A=
best_probability =3D category->total_probability;=0A=
best_category =3D category;=0A=
}=0A=
@@ -761,7 +762,8 @@ static int post_proc_clxp_categories(AVFrame *frame, =
DNNData *output, uint32_t b=0A=
av_freep(&ctx_labels);=0A=
return AVERROR(ENOMEM);=0A=
}=0A=
-=0A=
+=0A=
+ int category_count =3D 0;=0A=
// Process each context=0A=
for (int ctx_idx =3D 0; ctx_idx < cat_class_ctx->num_contexts; =
ctx_idx++) {=0A=
CategoriesContext *categories_ctx =3D =
cat_class_ctx->category_units[ctx_idx];=0A=
@@ -773,20 +775,22 @@ static int post_proc_clxp_categories(AVFrame =
*frame, DNNData *output, uint32_t b=0A=
// Find best category in context=0A=
best_category =3D get_best_category(categories_ctx, =
probabilities + prob_offset);=0A=
if (!best_category || !best_category->name) {=0A=
- av_log(filter_ctx, AV_LOG_ERROR, "Invalid best category at =
context %d\n", ctx_idx);=0A=
+ // No category classification found=0A=
continue;=0A=
}=0A=
=0A=
// Copy category name instead of assigning pointer=0A=
- av_strlcpy(ctx_labels[ctx_idx], best_category->name, =
AV_DETECTION_BBOX_LABEL_NAME_MAX_SIZE);=0A=
- ctx_probabilities[ctx_idx] =3D best_category->total_probability;=0A=
+ av_strlcpy(ctx_labels[category_count], best_category->name, =
AV_DETECTION_BBOX_LABEL_NAME_MAX_SIZE);=0A=
+ ctx_probabilities[category_count] =3D =
best_category->total_probability;=0A=
=0A=
prob_offset +=3D categories_ctx->label_count;=0A=
+ category_count++;=0A=
+ }=0A=
+ if(category_count > 0){=0A=
+ // Fill bbox with best categories=0A=
+ ret =3D fill_detection_bbox_with_best_labels(ctx_labels, =
ctx_probabilities, cat_class_ctx->num_contexts, bbox,=0A=
+ AV_NUM_DETECTION_BBOX_CLASSIFY, ctx->confidence);=0A=
}=0A=
-=0A=
- // Fill bbox with best labels=0A=
- ret =3D fill_detection_bbox_with_best_labels(ctx_labels, =
ctx_probabilities, cat_class_ctx->num_contexts, bbox,=0A=
- =
AV_NUM_DETECTION_BBOX_CLASSIFY, ctx->confidence);=0A=
=0A=
// Clean up=0A=
for (int i =3D 0; i < cat_class_ctx->num_contexts; i++) {=0A=
-- =0A=
2.34.1=0A=
=0A=
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