Commit b29c7bcb authored by Jarek Samic's avatar Jarek Samic Committed by Mark Thompson

lavfi: add deshake_opencl filter

parent 5b5746b1
...@@ -3454,6 +3454,7 @@ delogo_filter_deps="gpl" ...@@ -3454,6 +3454,7 @@ delogo_filter_deps="gpl"
denoise_vaapi_filter_deps="vaapi" denoise_vaapi_filter_deps="vaapi"
derain_filter_select="dnn" derain_filter_select="dnn"
deshake_filter_select="pixelutils" deshake_filter_select="pixelutils"
deshake_opencl_filter_deps="opencl"
dilation_opencl_filter_deps="opencl" dilation_opencl_filter_deps="opencl"
drawtext_filter_deps="libfreetype" drawtext_filter_deps="libfreetype"
drawtext_filter_suggest="libfontconfig libfribidi" drawtext_filter_suggest="libfontconfig libfribidi"
......
...@@ -19795,6 +19795,75 @@ Make every semi-green pixel in the input transparent with some slight blending: ...@@ -19795,6 +19795,75 @@ Make every semi-green pixel in the input transparent with some slight blending:
@end example @end example
@end itemize @end itemize
@section deshake_opencl
Feature-point based video stabilization filter.
The filter accepts the following options:
@table @option
@item tripod
Simulates a tripod by preventing any camera movement whatsoever from the original frame. Defaults to @code{0}.
@item debug
Whether or not additional debug info should be displayed, both in the processed output and in the console.
Note that in order to see console debug output you will also need to pass @code{-v verbose} to ffmpeg.
Viewing point matches in the output video is only supported for RGB input.
Defaults to @code{0}.
@item adaptive_crop
Whether or not to do a tiny bit of cropping at the borders to cut down on the amount of mirrored pixels.
Defaults to @code{1}.
@item refine_features
Whether or not feature points should be refined at a sub-pixel level.
This can be turned off for a slight performance gain at the cost of precision.
Defaults to @code{1}.
@item smooth_strength
The strength of the smoothing applied to the camera path from @code{0.0} to @code{1.0}.
@code{1.0} is the maximum smoothing strength while values less than that result in less smoothing.
@code{0.0} causes the filter to adaptively choose a smoothing strength on a per-frame basis.
Defaults to @code{0.0}.
@item smooth_window_multiplier
Controls the size of the smoothing window (the number of frames buffered to determine motion information from).
The size of the smoothing window is determined by multiplying the framerate of the video by this number.
Acceptable values range from @code{0.1} to @code{10.0}.
Larger values increase the amount of motion data available for determining how to smooth the camera path,
potentially improving smoothness, but also increase latency and memory usage.
Defaults to @code{2.0}.
@end table
@subsection Examples
@itemize
@item
Stabilize a video with a fixed, medium smoothing strength:
@example
-i INPUT -vf "hwupload, deshake_opencl=smooth_strength=0.5, hwdownload" OUTPUT
@end example
@item
Stabilize a video with debugging (both in console and in rendered video):
@example
-i INPUT -filter_complex "[0:v]format=rgba, hwupload, deshake_opencl=debug=1, hwdownload, format=rgba, format=yuv420p" -v verbose OUTPUT
@end example
@end itemize
@section nlmeans_opencl @section nlmeans_opencl
Non-local Means denoise filter through OpenCL, this filter accepts same options as @ref{nlmeans}. Non-local Means denoise filter through OpenCL, this filter accepts same options as @ref{nlmeans}.
......
...@@ -211,6 +211,8 @@ OBJS-$(CONFIG_DEINTERLACE_VAAPI_FILTER) += vf_deinterlace_vaapi.o vaapi_vpp ...@@ -211,6 +211,8 @@ OBJS-$(CONFIG_DEINTERLACE_VAAPI_FILTER) += vf_deinterlace_vaapi.o vaapi_vpp
OBJS-$(CONFIG_DEJUDDER_FILTER) += vf_dejudder.o OBJS-$(CONFIG_DEJUDDER_FILTER) += vf_dejudder.o
OBJS-$(CONFIG_DELOGO_FILTER) += vf_delogo.o OBJS-$(CONFIG_DELOGO_FILTER) += vf_delogo.o
OBJS-$(CONFIG_DENOISE_VAAPI_FILTER) += vf_misc_vaapi.o vaapi_vpp.o OBJS-$(CONFIG_DENOISE_VAAPI_FILTER) += vf_misc_vaapi.o vaapi_vpp.o
OBJS-$(CONFIG_DESHAKE_OPENCL_FILTER) += vf_deshake_opencl.o opencl.o \
opencl/deshake.o
OBJS-$(CONFIG_DESHAKE_FILTER) += vf_deshake.o OBJS-$(CONFIG_DESHAKE_FILTER) += vf_deshake.o
OBJS-$(CONFIG_DESPILL_FILTER) += vf_despill.o OBJS-$(CONFIG_DESPILL_FILTER) += vf_despill.o
OBJS-$(CONFIG_DETELECINE_FILTER) += vf_detelecine.o OBJS-$(CONFIG_DETELECINE_FILTER) += vf_detelecine.o
......
...@@ -200,6 +200,7 @@ extern AVFilter ff_vf_delogo; ...@@ -200,6 +200,7 @@ extern AVFilter ff_vf_delogo;
extern AVFilter ff_vf_denoise_vaapi; extern AVFilter ff_vf_denoise_vaapi;
extern AVFilter ff_vf_derain; extern AVFilter ff_vf_derain;
extern AVFilter ff_vf_deshake; extern AVFilter ff_vf_deshake;
extern AVFilter ff_vf_deshake_opencl;
extern AVFilter ff_vf_despill; extern AVFilter ff_vf_despill;
extern AVFilter ff_vf_detelecine; extern AVFilter ff_vf_detelecine;
extern AVFilter ff_vf_dilation; extern AVFilter ff_vf_dilation;
......
/*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*
* Copyright (C) 2000, Intel Corporation, all rights reserved.
* Copyright (C) 2013, OpenCV Foundation, all rights reserved.
* Third party copyrights are property of their respective owners.
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met:
*
* * Redistribution's of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistribution's in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* * The name of the copyright holders may not be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* This software is provided by the copyright holders and contributors "as is" and
* any express or implied warranties, including, but not limited to, the implied
* warranties of merchantability and fitness for a particular purpose are disclaimed.
* In no event shall the Intel Corporation or contributors be liable for any direct,
* indirect, incidental, special, exemplary, or consequential damages
* (including, but not limited to, procurement of substitute goods or services;
* loss of use, data, or profits; or business interruption) however caused
* and on any theory of liability, whether in contract, strict liability,
* or tort (including negligence or otherwise) arising in any way out of
* the use of this software, even if advised of the possibility of such damage.
*/
#define HARRIS_THRESHOLD 3.0f
// Block size over which to compute harris response
//
// Note that changing this will require fiddling with the local array sizes in
// harris_response
#define HARRIS_RADIUS 2
#define DISTANCE_THRESHOLD 80
// Sub-pixel refinement window for feature points
#define REFINE_WIN_HALF_W 5
#define REFINE_WIN_HALF_H 5
#define REFINE_WIN_W 11 // REFINE_WIN_HALF_W * 2 + 1
#define REFINE_WIN_H 11
// Non-maximum suppression window size
#define NONMAX_WIN 30
#define NONMAX_WIN_HALF 15 // NONMAX_WIN / 2
typedef struct PointPair {
// Previous frame
float2 p1;
// Current frame
float2 p2;
} PointPair;
typedef struct SmoothedPointPair {
// Non-smoothed point in current frame
int2 p1;
// Smoothed point in current frame
float2 p2;
} SmoothedPointPair;
typedef struct MotionVector {
PointPair p;
// Used to mark vectors as potential outliers
int should_consider;
} MotionVector;
const sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE |
CLK_ADDRESS_CLAMP_TO_EDGE |
CLK_FILTER_NEAREST;
const sampler_t sampler_linear = CLK_NORMALIZED_COORDS_FALSE |
CLK_ADDRESS_CLAMP_TO_EDGE |
CLK_FILTER_LINEAR;
const sampler_t sampler_linear_mirror = CLK_NORMALIZED_COORDS_TRUE |
CLK_ADDRESS_MIRRORED_REPEAT |
CLK_FILTER_LINEAR;
// Writes to a 1D array at loc, treating it as a 2D array with the same
// dimensions as the global work size.
static void write_to_1d_arrf(__global float *buf, int2 loc, float val) {
buf[loc.x + loc.y * get_global_size(0)] = val;
}
static void write_to_1d_arrul8(__global ulong8 *buf, int2 loc, ulong8 val) {
buf[loc.x + loc.y * get_global_size(0)] = val;
}
static void write_to_1d_arrvec(__global MotionVector *buf, int2 loc, MotionVector val) {
buf[loc.x + loc.y * get_global_size(0)] = val;
}
static void write_to_1d_arrf2(__global float2 *buf, int2 loc, float2 val) {
buf[loc.x + loc.y * get_global_size(0)] = val;
}
static ulong8 read_from_1d_arrul8(__global const ulong8 *buf, int2 loc) {
return buf[loc.x + loc.y * get_global_size(0)];
}
static float2 read_from_1d_arrf2(__global const float2 *buf, int2 loc) {
return buf[loc.x + loc.y * get_global_size(0)];
}
// Returns the grayscale value at the given point.
static float pixel_grayscale(__read_only image2d_t src, int2 loc) {
float4 pixel = read_imagef(src, sampler, loc);
return (pixel.x + pixel.y + pixel.z) / 3.0f;
}
static float convolve(
__local const float *grayscale,
int local_idx_x,
int local_idx_y,
float mask[3][3]
) {
float ret = 0;
// These loops touch each pixel surrounding loc as well as loc itself
for (int i = 1, i2 = 0; i >= -1; --i, ++i2) {
for (int j = -1, j2 = 0; j <= 1; ++j, ++j2) {
ret += mask[i2][j2] * grayscale[(local_idx_x + 3 + j) + (local_idx_y + 3 + i) * 14];
}
}
return ret;
}
// Sums dx * dy for all pixels within radius of loc
static float sum_deriv_prod(
__local const float *grayscale,
float mask_x[3][3],
float mask_y[3][3]
) {
float ret = 0;
for (int i = HARRIS_RADIUS; i >= -HARRIS_RADIUS; --i) {
for (int j = -HARRIS_RADIUS; j <= HARRIS_RADIUS; ++j) {
ret += convolve(grayscale, get_local_id(0) + j, get_local_id(1) + i, mask_x) *
convolve(grayscale, get_local_id(0) + j, get_local_id(1) + i, mask_y);
}
}
return ret;
}
// Sums d<>^2 (determined by mask) for all pixels within radius of loc
static float sum_deriv_pow(__local const float *grayscale, float mask[3][3])
{
float ret = 0;
for (int i = HARRIS_RADIUS; i >= -HARRIS_RADIUS; --i) {
for (int j = -HARRIS_RADIUS; j <= HARRIS_RADIUS; ++j) {
float deriv = convolve(grayscale, get_local_id(0) + j, get_local_id(1) + i, mask);
ret += deriv * deriv;
}
}
return ret;
}
// Fills a box with the given radius and pixel around loc
static void draw_box(__write_only image2d_t dst, int2 loc, float4 pixel, int radius)
{
for (int i = -radius; i <= radius; ++i) {
for (int j = -radius; j <= radius; ++j) {
write_imagef(
dst,
(int2)(
// Clamp to avoid writing outside image bounds
clamp(loc.x + i, 0, get_image_dim(dst).x - 1),
clamp(loc.y + j, 0, get_image_dim(dst).y - 1)
),
pixel
);
}
}
}
// Converts the src image to grayscale
__kernel void grayscale(
__read_only image2d_t src,
__write_only image2d_t grayscale
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
write_imagef(grayscale, loc, (float4)(pixel_grayscale(src, loc), 0.0f, 0.0f, 1.0f));
}
// This kernel computes the harris response for the given grayscale src image
// within the given radius and writes it to harris_buf
__kernel void harris_response(
__read_only image2d_t grayscale,
__global float *harris_buf
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
if (loc.x > get_image_width(grayscale) - 1 || loc.y > get_image_height(grayscale) - 1) {
write_to_1d_arrf(harris_buf, loc, 0);
return;
}
float scale = 1.0f / ((1 << 2) * HARRIS_RADIUS * 255.0f);
float sobel_mask_x[3][3] = {
{-1, 0, 1},
{-2, 0, 2},
{-1, 0, 1}
};
float sobel_mask_y[3][3] = {
{ 1, 2, 1},
{ 0, 0, 0},
{-1, -2, -1}
};
// 8 x 8 local work + 3 pixels around each side (needed to accomodate for the
// block size radius of 2)
__local float grayscale_data[196];
int idx = get_group_id(0) * get_local_size(0);
int idy = get_group_id(1) * get_local_size(1);
for (int i = idy - 3, it = 0; i < idy + (int)get_local_size(1) + 3; i++, it++) {
for (int j = idx - 3, jt = 0; j < idx + (int)get_local_size(0) + 3; j++, jt++) {
grayscale_data[jt + it * 14] = read_imagef(grayscale, sampler, (int2)(j, i)).x;
}
}
barrier(CLK_LOCAL_MEM_FENCE);
float sumdxdy = sum_deriv_prod(grayscale_data, sobel_mask_x, sobel_mask_y);
float sumdx2 = sum_deriv_pow(grayscale_data, sobel_mask_x);
float sumdy2 = sum_deriv_pow(grayscale_data, sobel_mask_y);
float trace = sumdx2 + sumdy2;
// r = det(M) - k(trace(M))^2
// k usually between 0.04 to 0.06
float r = (sumdx2 * sumdy2 - sumdxdy * sumdxdy) - 0.04f * (trace * trace) * pown(scale, 4);
// Threshold the r value
harris_buf[loc.x + loc.y * get_image_width(grayscale)] = r * step(HARRIS_THRESHOLD, r);
}
// Gets a patch centered around a float coordinate from a grayscale image using
// bilinear interpolation
static void get_rect_sub_pix(
__read_only image2d_t grayscale,
float *buffer,
int size_x,
int size_y,
float2 center
) {
float2 offset = ((float2)(size_x, size_y) - 1.0f) * 0.5f;
for (int i = 0; i < size_y; i++) {
for (int j = 0; j < size_x; j++) {
buffer[i * size_x + j] = read_imagef(
grayscale,
sampler_linear,
(float2)(j, i) + center - offset
).x * 255.0f;
}
}
}
// Refines detected features at a sub-pixel level
//
// This function is ported from OpenCV
static float2 corner_sub_pix(
__read_only image2d_t grayscale,
float2 feature,
float *mask
) {
float2 init = feature;
int src_width = get_global_size(0);
int src_height = get_global_size(1);
const int max_iters = 40;
const float eps = 0.001f * 0.001f;
int i, j, k;
int iter = 0;
float err = 0;
float subpix[(REFINE_WIN_W + 2) * (REFINE_WIN_H + 2)];
const float flt_epsilon = 0x1.0p-23f;
do {
float2 feature_tmp;
float a = 0, b = 0, c = 0, bb1 = 0, bb2 = 0;
get_rect_sub_pix(grayscale, subpix, REFINE_WIN_W + 2, REFINE_WIN_H + 2, feature);
float *subpix_ptr = subpix;
subpix_ptr += REFINE_WIN_W + 2 + 1;
// process gradient
for (i = 0, k = 0; i < REFINE_WIN_H; i++, subpix_ptr += REFINE_WIN_W + 2) {
float py = i - REFINE_WIN_HALF_H;
for (j = 0; j < REFINE_WIN_W; j++, k++) {
float m = mask[k];
float tgx = subpix_ptr[j + 1] - subpix_ptr[j - 1];
float tgy = subpix_ptr[j + REFINE_WIN_W + 2] - subpix_ptr[j - REFINE_WIN_W - 2];
float gxx = tgx * tgx * m;
float gxy = tgx * tgy * m;
float gyy = tgy * tgy * m;
float px = j - REFINE_WIN_HALF_W;
a += gxx;
b += gxy;
c += gyy;
bb1 += gxx * px + gxy * py;
bb2 += gxy * px + gyy * py;
}
}
float det = a * c - b * b;
if (fabs(det) <= flt_epsilon * flt_epsilon) {
break;
}
// 2x2 matrix inversion
float scale = 1.0f / det;
feature_tmp.x = (float)(feature.x + (c * scale * bb1) - (b * scale * bb2));
feature_tmp.y = (float)(feature.y - (b * scale * bb1) + (a * scale * bb2));
err = dot(feature_tmp - feature, feature_tmp - feature);
feature = feature_tmp;
if (feature.x < 0 || feature.x >= src_width || feature.y < 0 || feature.y >= src_height) {
break;
}
} while (++iter < max_iters && err > eps);
// Make sure new point isn't too far from the initial point (indicates poor convergence)
if (fabs(feature.x - init.x) > REFINE_WIN_HALF_W || fabs(feature.y - init.y) > REFINE_WIN_HALF_H) {
feature = init;
}
return feature;
}
// Performs non-maximum suppression on the harris response and writes the resulting
// feature locations to refined_features.
//
// Assumes that refined_features and the global work sizes are set up such that the image
// is split up into a grid of 32x32 blocks where each block has a single slot in the
// refined_features buffer. This kernel finds the best corner in each block (if the
// block has any) and writes it to the corresponding slot in the buffer.
//
// If subpixel_refine is true, the features are additionally refined at a sub-pixel
// level for increased precision.
__kernel void refine_features(
__read_only image2d_t grayscale,
__global const float *harris_buf,
__global float2 *refined_features,
int subpixel_refine
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
// The location in the grayscale buffer rather than the compacted grid
int2 loc_i = (int2)(loc.x * 32, loc.y * 32);
float new_val;
float max_val = 0;
float2 loc_max = (float2)(-1, -1);
int end_x = min(loc_i.x + 32, (int)get_image_dim(grayscale).x - 1);
int end_y = min(loc_i.y + 32, (int)get_image_dim(grayscale).y - 1);
for (int i = loc_i.x; i < end_x; ++i) {
for (int j = loc_i.y; j < end_y; ++j) {
new_val = harris_buf[i + j * get_image_dim(grayscale).x];
if (new_val > max_val) {
max_val = new_val;
loc_max = (float2)(i, j);
}
}
}
if (max_val == 0) {
// There are no features in this part of the frame
write_to_1d_arrf2(refined_features, loc, loc_max);
return;
}
if (subpixel_refine) {
float mask[REFINE_WIN_H * REFINE_WIN_W];
for (int i = 0; i < REFINE_WIN_H; i++) {
float y = (float)(i - REFINE_WIN_HALF_H) / REFINE_WIN_HALF_H;
float vy = exp(-y * y);
for (int j = 0; j < REFINE_WIN_W; j++) {
float x = (float)(j - REFINE_WIN_HALF_W) / REFINE_WIN_HALF_W;
mask[i * REFINE_WIN_W + j] = (float)(vy * exp(-x * x));
}
}
loc_max = corner_sub_pix(grayscale, loc_max, mask);
}
write_to_1d_arrf2(refined_features, loc, loc_max);
}
// Extracts BRIEF descriptors from the grayscale src image for the given features
// using the provided sampler.
__kernel void brief_descriptors(
__read_only image2d_t grayscale,
__global const float2 *refined_features,
// for 512 bit descriptors
__global ulong8 *desc_buf,
__global const PointPair *brief_pattern
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
float2 feature = read_from_1d_arrf2(refined_features, loc);
// There was no feature in this part of the frame
if (feature.x == -1) {
write_to_1d_arrul8(desc_buf, loc, (ulong8)(0));
return;
}
ulong8 desc = 0;
ulong *p = &desc;
for (int i = 0; i < 8; ++i) {
for (int j = 0; j < 64; ++j) {
PointPair pair = brief_pattern[j * (i + 1)];
float l1 = read_imagef(grayscale, sampler_linear, feature + pair.p1).x;
float l2 = read_imagef(grayscale, sampler_linear, feature + pair.p2).x;
if (l1 < l2) {
p[i] |= 1UL << j;
}
}
}
write_to_1d_arrul8(desc_buf, loc, desc);
}
// Given buffers with descriptors for the current and previous frame, determines
// which ones match, writing correspondences to matches_buf.
//
// Feature and descriptor buffers are assumed to be compacted (each element sourced
// from a 32x32 block in the frame being processed).
__kernel void match_descriptors(
__global const float2 *prev_refined_features,
__global const float2 *refined_features,
__global const ulong8 *desc_buf,
__global const ulong8 *prev_desc_buf,
__global MotionVector *matches_buf
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
ulong8 desc = read_from_1d_arrul8(desc_buf, loc);
const int search_radius = 3;
MotionVector invalid_vector = (MotionVector) {
(PointPair) {
(float2)(-1, -1),
(float2)(-1, -1)
},
0
};
if (desc.s0 == 0 && desc.s1 == 0) {
// There was no feature in this part of the frame
write_to_1d_arrvec(
matches_buf,
loc,
invalid_vector
);
return;
}
int2 start = max(loc - search_radius, 0);
int2 end = min(loc + search_radius, (int2)(get_global_size(0) - 1, get_global_size(1) - 1));
for (int i = start.x; i < end.x; ++i) {
for (int j = start.y; j < end.y; ++j) {
int2 prev_point = (int2)(i, j);
int total_dist = 0;
ulong8 prev_desc = read_from_1d_arrul8(prev_desc_buf, prev_point);
if (prev_desc.s0 == 0 && prev_desc.s1 == 0) {
continue;
}
ulong *prev_desc_p = &prev_desc;
ulong *desc_p = &desc;
for (int i = 0; i < 8; i++) {
total_dist += popcount(desc_p[i] ^ prev_desc_p[i]);
}
if (total_dist < DISTANCE_THRESHOLD) {
write_to_1d_arrvec(
matches_buf,
loc,
(MotionVector) {
(PointPair) {
read_from_1d_arrf2(prev_refined_features, prev_point),
read_from_1d_arrf2(refined_features, loc)
},
1
}
);
return;
}
}
}
// There is no found match for this point
write_to_1d_arrvec(
matches_buf,
loc,
invalid_vector
);
}
// Returns the position of the given point after the transform is applied
static float2 transformed_point(float2 p, __global const float *transform) {
float2 ret;
ret.x = p.x * transform[0] + p.y * transform[1] + transform[2];
ret.y = p.x * transform[3] + p.y * transform[4] + transform[5];
return ret;
}
// Performs the given transform on the src image
__kernel void transform(
__read_only image2d_t src,
__write_only image2d_t dst,
__global const float *transform
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
float2 norm = convert_float2(get_image_dim(src));
write_imagef(
dst,
loc,
read_imagef(
src,
sampler_linear_mirror,
transformed_point((float2)(loc.x, loc.y), transform) / norm
)
);
}
// Returns the new location of the given point using the given crop bounding box
// and the width and height of the original frame.
static float2 cropped_point(
float2 p,
float2 top_left,
float2 bottom_right,
int2 orig_dim
) {
float2 ret;
float crop_width = bottom_right.x - top_left.x;
float crop_height = bottom_right.y - top_left.y;
float width_norm = p.x / (float)orig_dim.x;
float height_norm = p.y / (float)orig_dim.y;
ret.x = (width_norm * crop_width) + top_left.x;
ret.y = (height_norm * crop_height) + ((float)orig_dim.y - bottom_right.y);
return ret;
}
// Upscales the given cropped region to the size of the original frame
__kernel void crop_upscale(
__read_only image2d_t src,
__write_only image2d_t dst,
float2 top_left,
float2 bottom_right
) {
int2 loc = (int2)(get_global_id(0), get_global_id(1));
write_imagef(
dst,
loc,
read_imagef(
src,
sampler_linear,
cropped_point((float2)(loc.x, loc.y), top_left, bottom_right, get_image_dim(dst))
)
);
}
// Draws boxes to represent the given point matches and uses the given transform
// and crop info to make sure their positions are accurate on the transformed frame.
//
// model_matches is an array of three points that were used by the RANSAC process
// to generate the given transform
__kernel void draw_debug_info(
__write_only image2d_t dst,
__global const MotionVector *matches,
__global const MotionVector *model_matches,
int num_model_matches,
__global const float *transform
) {
int loc = get_global_id(0);
MotionVector vec = matches[loc];
// Black box: matched point that RANSAC considered an outlier
float4 big_rect_color = (float4)(0.1f, 0.1f, 0.1f, 1.0f);
if (vec.should_consider) {
// Green box: matched point that RANSAC considered an inlier
big_rect_color = (float4)(0.0f, 1.0f, 0.0f, 1.0f);
}
for (int i = 0; i < num_model_matches; i++) {
if (vec.p.p2.x == model_matches[i].p.p2.x && vec.p.p2.y == model_matches[i].p.p2.y) {
// Orange box: point used to calculate model
big_rect_color = (float4)(1.0f, 0.5f, 0.0f, 1.0f);
}
}
float2 transformed_p1 = transformed_point(vec.p.p1, transform);
float2 transformed_p2 = transformed_point(vec.p.p2, transform);
draw_box(dst, (int2)(transformed_p2.x, transformed_p2.y), big_rect_color, 5);
// Small light blue box: the point in the previous frame
draw_box(dst, (int2)(transformed_p1.x, transformed_p1.y), (float4)(0.0f, 0.3f, 0.7f, 1.0f), 3);
}
...@@ -23,6 +23,7 @@ extern const char *ff_opencl_source_avgblur; ...@@ -23,6 +23,7 @@ extern const char *ff_opencl_source_avgblur;
extern const char *ff_opencl_source_colorkey; extern const char *ff_opencl_source_colorkey;
extern const char *ff_opencl_source_colorspace_common; extern const char *ff_opencl_source_colorspace_common;
extern const char *ff_opencl_source_convolution; extern const char *ff_opencl_source_convolution;
extern const char *ff_opencl_source_deshake;
extern const char *ff_opencl_source_neighbor; extern const char *ff_opencl_source_neighbor;
extern const char *ff_opencl_source_nlmeans; extern const char *ff_opencl_source_nlmeans;
extern const char *ff_opencl_source_overlay; extern const char *ff_opencl_source_overlay;
......
...@@ -31,7 +31,7 @@ ...@@ -31,7 +31,7 @@
#define LIBAVFILTER_VERSION_MAJOR 7 #define LIBAVFILTER_VERSION_MAJOR 7
#define LIBAVFILTER_VERSION_MINOR 58 #define LIBAVFILTER_VERSION_MINOR 58
#define LIBAVFILTER_VERSION_MICRO 100 #define LIBAVFILTER_VERSION_MICRO 101
#define LIBAVFILTER_VERSION_INT AV_VERSION_INT(LIBAVFILTER_VERSION_MAJOR, \ #define LIBAVFILTER_VERSION_INT AV_VERSION_INT(LIBAVFILTER_VERSION_MAJOR, \
......
/*
* This file is part of FFmpeg.
*
* FFmpeg is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 2.1 of the License, or (at your option) any later version.
*
* FFmpeg is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with FFmpeg; if not, write to the Free Software
* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
*
* Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
* Copyright (C) 2009, Willow Garage Inc., all rights reserved.
* Copyright (C) 2013, OpenCV Foundation, all rights reserved.
* Third party copyrights are property of their respective owners.
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met:
*
* * Redistribution's of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistribution's in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* * The name of the copyright holders may not be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* This software is provided by the copyright holders and contributors "as is" and
* any express or implied warranties, including, but not limited to, the implied
* warranties of merchantability and fitness for a particular purpose are disclaimed.
* In no event shall the Intel Corporation or contributors be liable for any direct,
* indirect, incidental, special, exemplary, or consequential damages
* (including, but not limited to, procurement of substitute goods or services;
* loss of use, data, or profits; or business interruption) however caused
* and on any theory of liability, whether in contract, strict liability,
* or tort (including negligence or otherwise) arising in any way out of
* the use of this software, even if advised of the possibility of such damage.
*/
#include <stdbool.h>
#include <float.h>
#include <libavutil/lfg.h>
#include "libavutil/opt.h"
#include "libavutil/imgutils.h"
#include "libavutil/mem.h"
#include "libavutil/fifo.h"
#include "libavutil/common.h"
#include "libavutil/avassert.h"
#include "libavutil/pixfmt.h"
#include "avfilter.h"
#include "framequeue.h"
#include "filters.h"
#include "transform.h"
#include "formats.h"
#include "internal.h"
#include "opencl.h"
#include "opencl_source.h"
#include "video.h"
/*
This filter matches feature points between frames (dealing with outliers) and then
uses the matches to estimate an affine transform between frames. This transform is
decomposed into various values (translation, scale, rotation) and the values are
summed relative to the start of the video to obtain on absolute camera position
for each frame. This "camera path" is then smoothed via a gaussian filter, resulting
in a new path that is turned back into an affine transform and applied to each
frame to render it.
High-level overview:
All of the work to extract motion data from frames occurs in queue_frame. Motion data
is buffered in a smoothing window, so queue_frame simply computes the absolute camera
positions and places them in ringbuffers.
filter_frame is responsible for looking at the absolute camera positions currently
in the ringbuffers, applying the gaussian filter, and then transforming the frames.
*/
// Number of bits for BRIEF descriptors
#define BREIFN 512
// Size of the patch from which a BRIEF descriptor is extracted
// This is the size used in OpenCV
#define BRIEF_PATCH_SIZE 31
#define BRIEF_PATCH_SIZE_HALF (BRIEF_PATCH_SIZE / 2)
#define MATCHES_CONTIG_SIZE 2000
#define ROUNDED_UP_DIV(a, b) ((a + (b - 1)) / b)
typedef struct PointPair {
// Previous frame
cl_float2 p1;
// Current frame
cl_float2 p2;
} PointPair;
typedef struct MotionVector {
PointPair p;
// Used to mark vectors as potential outliers
cl_int should_consider;
} MotionVector;
// Denotes the indices for the different types of motion in the ringbuffers array
enum RingbufferIndices {
RingbufX,
RingbufY,
RingbufRot,
RingbufScaleX,
RingbufScaleY,
// Should always be last
RingbufCount
};
// Struct that holds data for drawing point match debug data
typedef struct DebugMatches {
MotionVector *matches;
// The points used to calculate the affine transform for a frame
MotionVector model_matches[3];
int num_matches;
// For cases where we couldn't calculate a model
int num_model_matches;
} DebugMatches;
// Groups together the ringbuffers that store absolute distortion / position values
// for each frame
typedef struct AbsoluteFrameMotion {
// Array with the various ringbuffers, indexed via the RingbufferIndices enum
AVFifoBuffer *ringbuffers[RingbufCount];
// Offset to get to the current frame being processed
// (not in bytes)
int curr_frame_offset;
// Keeps track of where the start and end of contiguous motion data is (to
// deal with cases where no motion data is found between two frames)
int data_start_offset;
int data_end_offset;
AVFifoBuffer *debug_matches;
} AbsoluteFrameMotion;
// Takes care of freeing the arrays within the DebugMatches inside of the
// debug_matches ringbuffer and then freeing the buffer itself.
static void free_debug_matches(AbsoluteFrameMotion *afm) {
DebugMatches dm;
if (!afm->debug_matches) {
return;
}
while (av_fifo_size(afm->debug_matches) > 0) {
av_fifo_generic_read(
afm->debug_matches,
&dm,
sizeof(DebugMatches),
NULL
);
av_freep(&dm.matches);
}
av_fifo_freep(&afm->debug_matches);
}
// Stores the translation, scale, rotation, and skew deltas between two frames
typedef struct FrameDelta {
cl_float2 translation;
float rotation;
cl_float2 scale;
cl_float2 skew;
} FrameDelta;
typedef struct SimilarityMatrix {
// The 2x3 similarity matrix
double matrix[6];
} SimilarityMatrix;
typedef struct CropInfo {
// The top left corner of the bounding box for the crop
cl_float2 top_left;
// The bottom right corner of the bounding box for the crop
cl_float2 bottom_right;
} CropInfo;
// Returned from function that determines start and end values for iteration
// around the current frame in a ringbuffer
typedef struct IterIndices {
int start;
int end;
} IterIndices;
typedef struct DeshakeOpenCLContext {
OpenCLFilterContext ocf;
// Whether or not the above `OpenCLFilterContext` has been initialized
int initialized;
// These variables are used in the activate callback
int64_t duration;
bool eof;
// State for random number generation
AVLFG alfg;
// FIFO frame queue used to buffer future frames for processing
FFFrameQueue fq;
// Ringbuffers for frame positions
AbsoluteFrameMotion abs_motion;
// The number of frames' motion to consider before and after the frame we are
// smoothing
int smooth_window;
// The number of the frame we are currently processing
int curr_frame;
// Stores a 1d array of normalised gaussian kernel values for convolution
float *gauss_kernel;
// Buffer for error values used in RANSAC code
float *ransac_err;
// Information regarding how to crop the smoothed luminance (or RGB) planes
CropInfo crop_y;
// Information regarding how to crop the smoothed chroma planes
CropInfo crop_uv;
// Whether or not we are processing YUV input (as oppposed to RGB)
bool is_yuv;
// The underlying format of the hardware surfaces
int sw_format;
// Buffer to copy `matches` into for the CPU to work with
MotionVector *matches_host;
MotionVector *matches_contig_host;
MotionVector *inliers;
cl_command_queue command_queue;
cl_kernel kernel_grayscale;
cl_kernel kernel_harris_response;
cl_kernel kernel_refine_features;
cl_kernel kernel_brief_descriptors;
cl_kernel kernel_match_descriptors;
cl_kernel kernel_transform;
cl_kernel kernel_crop_upscale;
// Stores a frame converted to grayscale
cl_mem grayscale;
// Stores the harris response for a frame (measure of "cornerness" for each pixel)
cl_mem harris_buf;
// Detected features after non-maximum suppression and sub-pixel refinement
cl_mem refined_features;
// Saved from the previous frame
cl_mem prev_refined_features;
// BRIEF sampling pattern that is randomly initialized
cl_mem brief_pattern;
// Feature point descriptors for the current frame
cl_mem descriptors;
// Feature point descriptors for the previous frame
cl_mem prev_descriptors;
// Vectors between points in current and previous frame
cl_mem matches;
cl_mem matches_contig;
// Holds the matrix to transform luminance (or RGB) with
cl_mem transform_y;
// Holds the matrix to transform chroma with
cl_mem transform_uv;
// Configurable options
int tripod_mode;
int debug_on;
int should_crop;
// Whether or not feature points should be refined at a sub-pixel level
cl_int refine_features;
// If the user sets a value other than the default, 0, this percentage is
// translated into a sigma value ranging from 0.5 to 40.0
float smooth_percent;
// This number is multiplied by the video frame rate to determine the size
// of the smooth window
float smooth_window_multiplier;
// Debug stuff
cl_kernel kernel_draw_debug_info;
cl_mem debug_matches;
cl_mem debug_model_matches;
// These store the total time spent executing the different kernels in nanoseconds
unsigned long long grayscale_time;
unsigned long long harris_response_time;
unsigned long long refine_features_time;
unsigned long long brief_descriptors_time;
unsigned long long match_descriptors_time;
unsigned long long transform_time;
unsigned long long crop_upscale_time;
// Time spent copying matched features from the device to the host
unsigned long long read_buf_time;
} DeshakeOpenCLContext;
// Returns a random uniformly-distributed number in [low, high]
static int rand_in(int low, int high, AVLFG *alfg) {
return (av_lfg_get(alfg) % (high - low)) + low;
}
// Returns the average execution time for an event given the total time and the
// number of frames processed.
static double averaged_event_time_ms(unsigned long long total_time, int num_frames) {
return (double)total_time / (double)num_frames / 1000000.0;
}
// The following code is loosely ported from OpenCV
// Estimates affine transform from 3 point pairs
// model is a 2x3 matrix:
// a b c
// d e f
static void run_estimate_kernel(const MotionVector *point_pairs, double *model)
{
// src points
double x1 = point_pairs[0].p.p1.s[0];
double y1 = point_pairs[0].p.p1.s[1];
double x2 = point_pairs[1].p.p1.s[0];
double y2 = point_pairs[1].p.p1.s[1];
double x3 = point_pairs[2].p.p1.s[0];
double y3 = point_pairs[2].p.p1.s[1];
// dest points
double X1 = point_pairs[0].p.p2.s[0];
double Y1 = point_pairs[0].p.p2.s[1];
double X2 = point_pairs[1].p.p2.s[0];
double Y2 = point_pairs[1].p.p2.s[1];
double X3 = point_pairs[2].p.p2.s[0];
double Y3 = point_pairs[2].p.p2.s[1];
double d = 1.0 / ( x1*(y2-y3) + x2*(y3-y1) + x3*(y1-y2) );
model[0] = d * ( X1*(y2-y3) + X2*(y3-y1) + X3*(y1-y2) );
model[1] = d * ( X1*(x3-x2) + X2*(x1-x3) + X3*(x2-x1) );
model[2] = d * ( X1*(x2*y3 - x3*y2) + X2*(x3*y1 - x1*y3) + X3*(x1*y2 - x2*y1) );
model[3] = d * ( Y1*(y2-y3) + Y2*(y3-y1) + Y3*(y1-y2) );
model[4] = d * ( Y1*(x3-x2) + Y2*(x1-x3) + Y3*(x2-x1) );
model[5] = d * ( Y1*(x2*y3 - x3*y2) + Y2*(x3*y1 - x1*y3) + Y3*(x1*y2 - x2*y1) );
}
// Checks that the 3 points in the given array are not collinear
static bool points_not_collinear(const cl_float2 **points)
{
int j, k, i = 2;
for (j = 0; j < i; j++) {
double dx1 = points[j]->s[0] - points[i]->s[0];
double dy1 = points[j]->s[1] - points[i]->s[1];
for (k = 0; k < j; k++) {
double dx2 = points[k]->s[0] - points[i]->s[0];
double dy2 = points[k]->s[1] - points[i]->s[1];
// Assuming a 3840 x 2160 video with a point at (0, 0) and one at
// (3839, 2159), this prevents a third point from being within roughly
// 0.5 of a pixel of the line connecting the two on both axes
if (fabs(dx2*dy1 - dy2*dx1) <= 1.0) {
return false;
}
}
}
return true;
}
// Checks a subset of 3 point pairs to make sure that the points are not collinear
// and not too close to each other
static bool check_subset(const MotionVector *pairs_subset)
{
const cl_float2 *prev_points[] = {
&pairs_subset[0].p.p1,
&pairs_subset[1].p.p1,
&pairs_subset[2].p.p1
};
const cl_float2 *curr_points[] = {
&pairs_subset[0].p.p2,
&pairs_subset[1].p.p2,
&pairs_subset[2].p.p2
};
return points_not_collinear(prev_points) && points_not_collinear(curr_points);
}
// Selects a random subset of 3 points from point_pairs and places them in pairs_subset
static bool get_subset(
AVLFG *alfg,
const MotionVector *point_pairs,
const int num_point_pairs,
MotionVector *pairs_subset,
int max_attempts
) {
int idx[3];
int i = 0, j, iters = 0;
for (; iters < max_attempts; iters++) {
for (i = 0; i < 3 && iters < max_attempts;) {
int idx_i = 0;
for (;;) {
idx_i = idx[i] = rand_in(0, num_point_pairs, alfg);
for (j = 0; j < i; j++) {
if (idx_i == idx[j]) {
break;
}
}
if (j == i) {
break;
}
}
pairs_subset[i] = point_pairs[idx[i]];
i++;
}
if (i == 3 && !check_subset(pairs_subset)) {
continue;
}
break;
}
return i == 3 && iters < max_attempts;
}
// Computes the error for each of the given points based on the given model.
static void compute_error(
const MotionVector *point_pairs,
const int num_point_pairs,
const double *model,
float *err
) {
double F0 = model[0], F1 = model[1], F2 = model[2];
double F3 = model[3], F4 = model[4], F5 = model[5];
for (int i = 0; i < num_point_pairs; i++) {
const cl_float2 *f = &point_pairs[i].p.p1;
const cl_float2 *t = &point_pairs[i].p.p2;
double a = F0*f->s[0] + F1*f->s[1] + F2 - t->s[0];
double b = F3*f->s[0] + F4*f->s[1] + F5 - t->s[1];
err[i] = a*a + b*b;
}
}
// Determines which of the given point matches are inliers for the given model
// based on the specified threshold.
//
// err must be an array of num_point_pairs length
static int find_inliers(
MotionVector *point_pairs,
const int num_point_pairs,
const double *model,
float *err,
double thresh
) {
float t = (float)(thresh * thresh);
int i, n = num_point_pairs, num_inliers = 0;
compute_error(point_pairs, num_point_pairs, model, err);
for (i = 0; i < n; i++) {
if (err[i] <= t) {
// This is an inlier
point_pairs[i].should_consider = true;
num_inliers += 1;
} else {
point_pairs[i].should_consider = false;
}
}
return num_inliers;
}
// Determines the number of iterations required to achieve the desired confidence level.
//
// The equation used to determine the number of iterations to do is:
// 1 - confidence = (1 - inlier_probability^num_points)^num_iters
//
// Solving for num_iters:
//
// num_iters = log(1 - confidence) / log(1 - inlier_probability^num_points)
//
// A more in-depth explanation can be found at https://en.wikipedia.org/wiki/Random_sample_consensus
// under the 'Parameters' heading
static int ransac_update_num_iters(double confidence, double num_outliers, int max_iters)
{
double num, denom;
confidence = av_clipd(confidence, 0.0, 1.0);
num_outliers = av_clipd(num_outliers, 0.0, 1.0);
// avoid inf's & nan's
num = FFMAX(1.0 - confidence, DBL_MIN);
denom = 1.0 - pow(1.0 - num_outliers, 3);
if (denom < DBL_MIN) {
return 0;
}
num = log(num);
denom = log(denom);
return denom >= 0 || -num >= max_iters * (-denom) ? max_iters : (int)round(num / denom);
}
// Estimates an affine transform between the given pairs of points using RANdom
// SAmple Consensus
static bool estimate_affine_2d(
DeshakeOpenCLContext *deshake_ctx,
MotionVector *point_pairs,
DebugMatches *debug_matches,
const int num_point_pairs,
double *model_out,
const double threshold,
const int max_iters,
const double confidence
) {
bool result = false;
double best_model[6], model[6];
MotionVector pairs_subset[3], best_pairs[3];
int iter, niters = FFMAX(max_iters, 1);
int good_count, max_good_count = 0;
// We need at least 3 points to build a model from
if (num_point_pairs < 3) {
return false;
} else if (num_point_pairs == 3) {
// There are only 3 points, so RANSAC doesn't apply here
run_estimate_kernel(point_pairs, model_out);
for (int i = 0; i < 3; ++i) {
point_pairs[i].should_consider = true;
}
return true;
}
for (iter = 0; iter < niters; ++iter) {
bool found = get_subset(&deshake_ctx->alfg, point_pairs, num_point_pairs, pairs_subset, 10000);
if (!found) {
if (iter == 0) {
return false;
}
break;
}
run_estimate_kernel(pairs_subset, model);
good_count = find_inliers(point_pairs, num_point_pairs, model, deshake_ctx->ransac_err, threshold);
if (good_count > FFMAX(max_good_count, 2)) {
for (int mi = 0; mi < 6; ++mi) {
best_model[mi] = model[mi];
}
for (int pi = 0; pi < 3; pi++) {
best_pairs[pi] = pairs_subset[pi];
}
max_good_count = good_count;
niters = ransac_update_num_iters(
confidence,
(double)(num_point_pairs - good_count) / num_point_pairs,
niters
);
}
}
if (max_good_count > 0) {
for (int mi = 0; mi < 6; ++mi) {
model_out[mi] = best_model[mi];
}
for (int pi = 0; pi < 3; ++pi) {
debug_matches->model_matches[pi] = best_pairs[pi];
}
debug_matches->num_model_matches = 3;
// Find the inliers again for the best model for debugging
find_inliers(point_pairs, num_point_pairs, best_model, deshake_ctx->ransac_err, threshold);
result = true;
}
return result;
}
// "Wiggles" the first point in best_pairs around a tiny bit in order to decrease the
// total error
static void optimize_model(
DeshakeOpenCLContext *deshake_ctx,
MotionVector *best_pairs,
MotionVector *inliers,
const int num_inliers,
float best_err,
double *model_out
) {
float move_x_val = 0.01;
float move_y_val = 0.01;
bool move_x = true;
float old_move_x_val = 0;
double model[6];
int last_changed = 0;
for (int iters = 0; iters < 200; iters++) {
float total_err = 0;
if (move_x) {
best_pairs[0].p.p2.s[0] += move_x_val;
} else {
best_pairs[0].p.p2.s[0] += move_y_val;
}
run_estimate_kernel(best_pairs, model);
compute_error(inliers, num_inliers, model, deshake_ctx->ransac_err);
for (int j = 0; j < num_inliers; j++) {
total_err += deshake_ctx->ransac_err[j];
}
if (total_err < best_err) {
for (int mi = 0; mi < 6; ++mi) {
model_out[mi] = model[mi];
}
best_err = total_err;
last_changed = iters;
} else {
// Undo the change
if (move_x) {
best_pairs[0].p.p2.s[0] -= move_x_val;
} else {
best_pairs[0].p.p2.s[0] -= move_y_val;
}
if (iters - last_changed > 4) {
// We've already improved the model as much as we can
break;
}
old_move_x_val = move_x_val;
if (move_x) {
move_x_val *= -1;
} else {
move_y_val *= -1;
}
if (old_move_x_val < 0) {
move_x = false;
} else {
move_x = true;
}
}
}
}
// Uses a process similar to that of RANSAC to find a transform that minimizes
// the total error for a set of point matches determined to be inliers
//
// (Pick random subsets, compute model, find total error, iterate until error
// is minimized.)
static bool minimize_error(
DeshakeOpenCLContext *deshake_ctx,
MotionVector *inliers,
DebugMatches *debug_matches,
const int num_inliers,
double *model_out,
const int max_iters
) {
bool result = false;
float best_err = FLT_MAX;
double best_model[6], model[6];
MotionVector pairs_subset[3], best_pairs[3];
for (int i = 0; i < max_iters; i++) {
float total_err = 0;
bool found = get_subset(&deshake_ctx->alfg, inliers, num_inliers, pairs_subset, 10000);
if (!found) {
if (i == 0) {
return false;
}
break;
}
run_estimate_kernel(pairs_subset, model);
compute_error(inliers, num_inliers, model, deshake_ctx->ransac_err);
for (int j = 0; j < num_inliers; j++) {
total_err += deshake_ctx->ransac_err[j];
}
if (total_err < best_err) {
for (int mi = 0; mi < 6; ++mi) {
best_model[mi] = model[mi];
}
for (int pi = 0; pi < 3; pi++) {
best_pairs[pi] = pairs_subset[pi];
}
best_err = total_err;
}
}
for (int mi = 0; mi < 6; ++mi) {
model_out[mi] = best_model[mi];
}
for (int pi = 0; pi < 3; ++pi) {
debug_matches->model_matches[pi] = best_pairs[pi];
}
debug_matches->num_model_matches = 3;
result = true;
optimize_model(deshake_ctx, best_pairs, inliers, num_inliers, best_err, model_out);
return result;
}
// End code from OpenCV
// Decomposes a similarity matrix into translation, rotation, scale, and skew
//
// See http://frederic-wang.fr/decomposition-of-2d-transform-matrices.html
static FrameDelta decompose_transform(double *model)
{
FrameDelta ret;
double a = model[0];
double c = model[1];
double e = model[2];
double b = model[3];
double d = model[4];
double f = model[5];
double delta = a * d - b * c;
ret.translation.s[0] = e;
ret.translation.s[1] = f;
// This is the QR method
if (a != 0 || b != 0) {
double r = hypot(a, b);
ret.rotation = FFSIGN(b) * acos(a / r);
ret.scale.s[0] = r;
ret.scale.s[1] = delta / r;
ret.skew.s[0] = atan((a * c + b * d) / (r * r));
ret.skew.s[1] = 0;
} else if (c != 0 || d != 0) {
double s = sqrt(c * c + d * d);
ret.rotation = M_PI / 2 - FFSIGN(d) * acos(-c / s);
ret.scale.s[0] = delta / s;
ret.scale.s[1] = s;
ret.skew.s[0] = 0;
ret.skew.s[1] = atan((a * c + b * d) / (s * s));
} // otherwise there is only translation
return ret;
}
// Move valid vectors from the 2d buffer into a 1d buffer where they are contiguous
static int make_vectors_contig(
DeshakeOpenCLContext *deshake_ctx,
int size_y,
int size_x
) {
int num_vectors = 0;
for (int i = 0; i < size_y; ++i) {
for (int j = 0; j < size_x; ++j) {
MotionVector v = deshake_ctx->matches_host[j + i * size_x];
if (v.should_consider) {
deshake_ctx->matches_contig_host[num_vectors] = v;
++num_vectors;
}
// Make sure we do not exceed the amount of space we allocated for these vectors
if (num_vectors == MATCHES_CONTIG_SIZE - 1) {
return num_vectors;
}
}
}
return num_vectors;
}
// Returns the gaussian kernel value for the given x coordinate and sigma value
static float gaussian_for(int x, float sigma) {
return 1.0f / expf(((float)x * (float)x) / (2.0f * sigma * sigma));
}
// Makes a normalized gaussian kernel of the given length for the given sigma
// and places it in gauss_kernel
static void make_gauss_kernel(float *gauss_kernel, float length, float sigma)
{
float gauss_sum = 0;
int window_half = length / 2;
for (int i = 0; i < length; ++i) {
float val = gaussian_for(i - window_half, sigma);
gauss_sum += val;
gauss_kernel[i] = val;
}
// Normalize the gaussian values
for (int i = 0; i < length; ++i) {
gauss_kernel[i] /= gauss_sum;
}
}
// Returns indices to start and end iteration at in order to iterate over a window
// of length size centered at the current frame in a ringbuffer
//
// Always returns numbers that result in a window of length size, even if that
// means specifying negative indices or indices past the end of the values in the
// ringbuffers. Make sure you clip indices appropriately within your loop.
static IterIndices start_end_for(DeshakeOpenCLContext *deshake_ctx, int length) {
IterIndices indices;
indices.start = deshake_ctx->abs_motion.curr_frame_offset - (length / 2);
indices.end = deshake_ctx->abs_motion.curr_frame_offset + (length / 2) + (length % 2);
return indices;
}
// Sets val to the value in the given ringbuffer at the given offset, taking care of
// clipping the offset into the appropriate range
static void ringbuf_float_at(
DeshakeOpenCLContext *deshake_ctx,
AVFifoBuffer *values,
float *val,
int offset
) {
int clip_start, clip_end, offset_clipped;
if (deshake_ctx->abs_motion.data_end_offset != -1) {
clip_end = deshake_ctx->abs_motion.data_end_offset;
} else {
// This expression represents the last valid index in the buffer,
// which we use repeatedly at the end of the video.
clip_end = deshake_ctx->smooth_window - (av_fifo_space(values) / sizeof(float)) - 1;
}
if (deshake_ctx->abs_motion.data_start_offset != -1) {
clip_start = deshake_ctx->abs_motion.data_start_offset;
} else {
// Negative indices will occur at the start of the video, and we want
// them to be clipped to 0 in order to repeatedly use the position of
// the first frame.
clip_start = 0;
}
offset_clipped = av_clip(
offset,
clip_start,
clip_end
);
av_fifo_generic_peek_at(
values,
val,
offset_clipped * sizeof(float),
sizeof(float),
NULL
);
}
// Returns smoothed current frame value of the given buffer of floats based on the
// given Gaussian kernel and its length (also the window length, centered around the
// current frame) and the "maximum value" of the motion.
//
// This "maximum value" should be the width / height of the image in the case of
// translation and an empirically chosen constant for rotation / scale.
//
// The sigma chosen to generate the final gaussian kernel with used to smooth the
// camera path is either hardcoded (set by user, deshake_ctx->smooth_percent) or
// adaptively chosen.
static float smooth(
DeshakeOpenCLContext *deshake_ctx,
float *gauss_kernel,
int length,
float max_val,
AVFifoBuffer *values
) {
float new_large_s = 0, new_small_s = 0, new_best = 0, old, diff_between,
percent_of_max, inverted_percent;
IterIndices indices = start_end_for(deshake_ctx, length);
float large_sigma = 40.0f;
float small_sigma = 2.0f;
float best_sigma;
if (deshake_ctx->smooth_percent) {
best_sigma = (large_sigma - 0.5f) * deshake_ctx->smooth_percent + 0.5f;
} else {
// Strategy to adaptively smooth trajectory:
//
// 1. Smooth path with large and small sigma values
// 2. Take the absolute value of the difference between them
// 3. Get a percentage by putting the difference over the "max value"
// 4, Invert the percentage
// 5. Calculate a new sigma value weighted towards the larger sigma value
// 6. Determine final smoothed trajectory value using that sigma
make_gauss_kernel(gauss_kernel, length, large_sigma);
for (int i = indices.start, j = 0; i < indices.end; ++i, ++j) {
ringbuf_float_at(deshake_ctx, values, &old, i);
new_large_s += old * gauss_kernel[j];
}
make_gauss_kernel(gauss_kernel, length, small_sigma);
for (int i = indices.start, j = 0; i < indices.end; ++i, ++j) {
ringbuf_float_at(deshake_ctx, values, &old, i);
new_small_s += old * gauss_kernel[j];
}
diff_between = fabsf(new_large_s - new_small_s);
percent_of_max = diff_between / max_val;
inverted_percent = 1 - percent_of_max;
best_sigma = large_sigma * powf(inverted_percent, 40);
}
make_gauss_kernel(gauss_kernel, length, best_sigma);
for (int i = indices.start, j = 0; i < indices.end; ++i, ++j) {
ringbuf_float_at(deshake_ctx, values, &old, i);
new_best += old * gauss_kernel[j];
}
return new_best;
}
// Returns the position of the given point after the transform is applied
static cl_float2 transformed_point(float x, float y, float *transform) {
cl_float2 ret;
ret.s[0] = x * transform[0] + y * transform[1] + transform[2];
ret.s[1] = x * transform[3] + y * transform[4] + transform[5];
return ret;
}
// Creates an affine transform that scales from the center of a frame
static void transform_center_scale(
float x_shift,
float y_shift,
float angle,
float scale_x,
float scale_y,
float center_w,
float center_h,
float *matrix
) {
cl_float2 center_s;
float center_s_w, center_s_h;
ff_get_matrix(
0,
0,
0,
scale_x,
scale_y,
matrix
);
center_s = transformed_point(center_w, center_h, matrix);
center_s_w = center_w - center_s.s[0];
center_s_h = center_h - center_s.s[1];
ff_get_matrix(
x_shift + center_s_w,
y_shift + center_s_h,
angle,
scale_x,
scale_y,
matrix
);
}
// Determines the crop necessary to eliminate black borders from a smoothed frame
// and updates target crop accordingly
static void update_needed_crop(
CropInfo* crop,
float *transform,
float frame_width,
float frame_height
) {
float new_width, new_height, adjusted_width, adjusted_height, adjusted_x, adjusted_y;
cl_float2 top_left = transformed_point(0, 0, transform);
cl_float2 top_right = transformed_point(frame_width, 0, transform);
cl_float2 bottom_left = transformed_point(0, frame_height, transform);
cl_float2 bottom_right = transformed_point(frame_width, frame_height, transform);
float ar_h = frame_height / frame_width;
float ar_w = frame_width / frame_height;
if (crop->bottom_right.s[0] == 0) {
// The crop hasn't been set to the original size of the plane
crop->bottom_right.s[0] = frame_width;
crop->bottom_right.s[1] = frame_height;
}
crop->top_left.s[0] = FFMAX3(
crop->top_left.s[0],
top_left.s[0],
bottom_left.s[0]
);
crop->top_left.s[1] = FFMAX3(
crop->top_left.s[1],
top_left.s[1],
top_right.s[1]
);
crop->bottom_right.s[0] = FFMIN3(
crop->bottom_right.s[0],
bottom_right.s[0],
top_right.s[0]
);
crop->bottom_right.s[1] = FFMIN3(
crop->bottom_right.s[1],
bottom_right.s[1],
bottom_left.s[1]
);
// Make sure our potentially new bounding box has the same aspect ratio
new_height = crop->bottom_right.s[1] - crop->top_left.s[1];
new_width = crop->bottom_right.s[0] - crop->top_left.s[0];
adjusted_width = new_height * ar_w;
adjusted_x = crop->bottom_right.s[0] - adjusted_width;
if (adjusted_x >= crop->top_left.s[0]) {
crop->top_left.s[0] = adjusted_x;
} else {
adjusted_height = new_width * ar_h;
adjusted_y = crop->bottom_right.s[1] - adjusted_height;
crop->top_left.s[1] = adjusted_y;
}
}
static av_cold void deshake_opencl_uninit(AVFilterContext *avctx)
{
DeshakeOpenCLContext *ctx = avctx->priv;
cl_int cle;
for (int i = 0; i < RingbufCount; i++)
av_fifo_freep(&ctx->abs_motion.ringbuffers[i]);
if (ctx->debug_on)
free_debug_matches(&ctx->abs_motion);
if (ctx->gauss_kernel)
av_freep(&ctx->gauss_kernel);
if (ctx->ransac_err)
av_freep(&ctx->ransac_err);
if (ctx->matches_host)
av_freep(&ctx->matches_host);
if (ctx->matches_contig_host)
av_freep(&ctx->matches_contig_host);
if (ctx->inliers)
av_freep(&ctx->inliers);
ff_framequeue_free(&ctx->fq);
CL_RELEASE_KERNEL(ctx->kernel_grayscale);
CL_RELEASE_KERNEL(ctx->kernel_harris_response);
CL_RELEASE_KERNEL(ctx->kernel_refine_features);
CL_RELEASE_KERNEL(ctx->kernel_brief_descriptors);
CL_RELEASE_KERNEL(ctx->kernel_match_descriptors);
CL_RELEASE_KERNEL(ctx->kernel_crop_upscale);
if (ctx->debug_on)
CL_RELEASE_KERNEL(ctx->kernel_draw_debug_info);
CL_RELEASE_QUEUE(ctx->command_queue);
if (!ctx->is_yuv)
CL_RELEASE_MEMORY(ctx->grayscale);
CL_RELEASE_MEMORY(ctx->harris_buf);
CL_RELEASE_MEMORY(ctx->refined_features);
CL_RELEASE_MEMORY(ctx->prev_refined_features);
CL_RELEASE_MEMORY(ctx->brief_pattern);
CL_RELEASE_MEMORY(ctx->descriptors);
CL_RELEASE_MEMORY(ctx->prev_descriptors);
CL_RELEASE_MEMORY(ctx->matches);
CL_RELEASE_MEMORY(ctx->matches_contig);
CL_RELEASE_MEMORY(ctx->transform_y);
CL_RELEASE_MEMORY(ctx->transform_uv);
if (ctx->debug_on) {
CL_RELEASE_MEMORY(ctx->debug_matches);
CL_RELEASE_MEMORY(ctx->debug_model_matches);
}
ff_opencl_filter_uninit(avctx);
}
static int deshake_opencl_init(AVFilterContext *avctx)
{
DeshakeOpenCLContext *ctx = avctx->priv;
AVFilterLink *outlink = avctx->outputs[0];
AVFilterLink *inlink = avctx->inputs[0];
// Pointer to the host-side pattern buffer to be initialized and then copied
// to the GPU
PointPair *pattern_host;
cl_int cle;
int err;
cl_ulong8 zeroed_ulong8;
FFFrameQueueGlobal fqg;
cl_image_format grayscale_format;
cl_image_desc grayscale_desc;
cl_command_queue_properties queue_props;
const enum AVPixelFormat disallowed_formats[14] = {
AV_PIX_FMT_GBRP,
AV_PIX_FMT_GBRP9BE,
AV_PIX_FMT_GBRP9LE,
AV_PIX_FMT_GBRP10BE,
AV_PIX_FMT_GBRP10LE,
AV_PIX_FMT_GBRP16BE,
AV_PIX_FMT_GBRP16LE,
AV_PIX_FMT_GBRAP,
AV_PIX_FMT_GBRAP16BE,
AV_PIX_FMT_GBRAP16LE,
AV_PIX_FMT_GBRAP12BE,
AV_PIX_FMT_GBRAP12LE,
AV_PIX_FMT_GBRAP10BE,
AV_PIX_FMT_GBRAP10LE
};
// Number of elements for an array
const int image_grid_32 = ROUNDED_UP_DIV(outlink->h, 32) * ROUNDED_UP_DIV(outlink->w, 32);
const int descriptor_buf_size = image_grid_32 * (BREIFN / 8);
const int features_buf_size = image_grid_32 * sizeof(cl_float2);
const AVHWFramesContext *hw_frames_ctx = (AVHWFramesContext*)inlink->hw_frames_ctx->data;
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(hw_frames_ctx->sw_format);
av_assert0(hw_frames_ctx);
av_assert0(desc);
ff_framequeue_global_init(&fqg);
ff_framequeue_init(&ctx->fq, &fqg);
ctx->eof = false;
ctx->smooth_window = (int)(av_q2d(avctx->inputs[0]->frame_rate) * ctx->smooth_window_multiplier);
ctx->curr_frame = 0;
memset(&zeroed_ulong8, 0, sizeof(cl_ulong8));
ctx->gauss_kernel = av_malloc_array(ctx->smooth_window, sizeof(float));
if (!ctx->gauss_kernel) {
err = AVERROR(ENOMEM);
goto fail;
}
ctx->ransac_err = av_malloc_array(MATCHES_CONTIG_SIZE, sizeof(float));
if (!ctx->ransac_err) {
err = AVERROR(ENOMEM);
goto fail;
}
for (int i = 0; i < RingbufCount; i++) {
ctx->abs_motion.ringbuffers[i] = av_fifo_alloc_array(
ctx->smooth_window,
sizeof(float)
);
if (!ctx->abs_motion.ringbuffers[i]) {
err = AVERROR(ENOMEM);
goto fail;
}
}
if (ctx->debug_on) {
ctx->abs_motion.debug_matches = av_fifo_alloc_array(
ctx->smooth_window / 2,
sizeof(DebugMatches)
);
if (!ctx->abs_motion.debug_matches) {
err = AVERROR(ENOMEM);
goto fail;
}
}
ctx->abs_motion.curr_frame_offset = 0;
ctx->abs_motion.data_start_offset = -1;
ctx->abs_motion.data_end_offset = -1;
pattern_host = av_malloc_array(BREIFN, sizeof(PointPair));
if (!pattern_host) {
err = AVERROR(ENOMEM);
goto fail;
}
ctx->matches_host = av_malloc_array(image_grid_32, sizeof(MotionVector));
if (!ctx->matches_host) {
err = AVERROR(ENOMEM);
goto fail;
}
ctx->matches_contig_host = av_malloc_array(MATCHES_CONTIG_SIZE, sizeof(MotionVector));
if (!ctx->matches_contig_host) {
err = AVERROR(ENOMEM);
goto fail;
}
ctx->inliers = av_malloc_array(MATCHES_CONTIG_SIZE, sizeof(MotionVector));
if (!ctx->inliers) {
err = AVERROR(ENOMEM);
goto fail;
}
// Initializing the patch pattern for building BREIF descriptors with
av_lfg_init(&ctx->alfg, 234342424);
for (int i = 0; i < BREIFN; ++i) {
PointPair pair;
for (int j = 0; j < 2; ++j) {
pair.p1.s[j] = rand_in(-BRIEF_PATCH_SIZE_HALF, BRIEF_PATCH_SIZE_HALF + 1, &ctx->alfg);
pair.p2.s[j] = rand_in(-BRIEF_PATCH_SIZE_HALF, BRIEF_PATCH_SIZE_HALF + 1, &ctx->alfg);
}
pattern_host[i] = pair;
}
for (int i = 0; i < 14; i++) {
if (ctx->sw_format == disallowed_formats[i]) {
av_log(avctx, AV_LOG_ERROR, "unsupported format in deshake_opencl.\n");
err = AVERROR(ENOSYS);
goto fail;
}
}
if (desc->flags & AV_PIX_FMT_FLAG_RGB) {
ctx->is_yuv = false;
} else {
ctx->is_yuv = true;
}
ctx->sw_format = hw_frames_ctx->sw_format;
err = ff_opencl_filter_load_program(avctx, &ff_opencl_source_deshake, 1);
if (err < 0)
goto fail;
if (ctx->debug_on) {
queue_props = CL_QUEUE_PROFILING_ENABLE;
} else {
queue_props = 0;
}
ctx->command_queue = clCreateCommandQueue(
ctx->ocf.hwctx->context,
ctx->ocf.hwctx->device_id,
queue_props,
&cle
);
CL_FAIL_ON_ERROR(AVERROR(EIO), "Failed to create OpenCL command queue %d.\n", cle);
CL_CREATE_KERNEL(ctx, grayscale);
CL_CREATE_KERNEL(ctx, harris_response);
CL_CREATE_KERNEL(ctx, refine_features);
CL_CREATE_KERNEL(ctx, brief_descriptors);
CL_CREATE_KERNEL(ctx, match_descriptors);
CL_CREATE_KERNEL(ctx, transform);
CL_CREATE_KERNEL(ctx, crop_upscale);
if (ctx->debug_on)
CL_CREATE_KERNEL(ctx, draw_debug_info);
if (!ctx->is_yuv) {
grayscale_format.image_channel_order = CL_R;
grayscale_format.image_channel_data_type = CL_FLOAT;
grayscale_desc = (cl_image_desc) {
.image_type = CL_MEM_OBJECT_IMAGE2D,
.image_width = outlink->w,
.image_height = outlink->h,
.image_depth = 0,
.image_array_size = 0,
.image_row_pitch = 0,
.image_slice_pitch = 0,
.num_mip_levels = 0,
.num_samples = 0,
.buffer = NULL,
};
ctx->grayscale = clCreateImage(
ctx->ocf.hwctx->context,
0,
&grayscale_format,
&grayscale_desc,
NULL,
&cle
);
CL_FAIL_ON_ERROR(AVERROR(EIO), "Failed to create grayscale image: %d.\n", cle);
}
CL_CREATE_BUFFER(ctx, harris_buf, outlink->h * outlink->w * sizeof(float));
CL_CREATE_BUFFER(ctx, refined_features, features_buf_size);
CL_CREATE_BUFFER(ctx, prev_refined_features, features_buf_size);
CL_CREATE_BUFFER_FLAGS(
ctx,
brief_pattern,
CL_MEM_READ_WRITE | CL_MEM_COPY_HOST_PTR,
BREIFN * sizeof(PointPair),
pattern_host
);
CL_CREATE_BUFFER(ctx, descriptors, descriptor_buf_size);
CL_CREATE_BUFFER(ctx, prev_descriptors, descriptor_buf_size);
CL_CREATE_BUFFER(ctx, matches, image_grid_32 * sizeof(MotionVector));
CL_CREATE_BUFFER(ctx, matches_contig, MATCHES_CONTIG_SIZE * sizeof(MotionVector));
CL_CREATE_BUFFER(ctx, transform_y, 9 * sizeof(float));
CL_CREATE_BUFFER(ctx, transform_uv, 9 * sizeof(float));
if (ctx->debug_on) {
CL_CREATE_BUFFER(ctx, debug_matches, MATCHES_CONTIG_SIZE * sizeof(MotionVector));
CL_CREATE_BUFFER(ctx, debug_model_matches, 3 * sizeof(MotionVector));
}
ctx->initialized = 1;
av_freep(&pattern_host);
return 0;
fail:
if (!pattern_host)
av_freep(&pattern_host);
return err;
}
// Logs debug information about the transform data
static void transform_debug(AVFilterContext *avctx, float *new_vals, float *old_vals, int curr_frame) {
av_log(avctx, AV_LOG_VERBOSE,
"Frame %d:\n"
"\tframe moved from: %f x, %f y\n"
"\t to: %f x, %f y\n"
"\t rotated from: %f degrees\n"
"\t to: %f degrees\n"
"\t scaled from: %f x, %f y\n"
"\t to: %f x, %f y\n"
"\n"
"\tframe moved by: %f x, %f y\n"
"\t rotated by: %f degrees\n"
"\t scaled by: %f x, %f y\n",
curr_frame,
old_vals[RingbufX], old_vals[RingbufY],
new_vals[RingbufX], new_vals[RingbufY],
old_vals[RingbufRot] * (180.0 / M_PI),
new_vals[RingbufRot] * (180.0 / M_PI),
old_vals[RingbufScaleX], old_vals[RingbufScaleY],
new_vals[RingbufScaleX], new_vals[RingbufScaleY],
old_vals[RingbufX] - new_vals[RingbufX], old_vals[RingbufY] - new_vals[RingbufY],
old_vals[RingbufRot] * (180.0 / M_PI) - new_vals[RingbufRot] * (180.0 / M_PI),
new_vals[RingbufScaleX] / old_vals[RingbufScaleX], new_vals[RingbufScaleY] / old_vals[RingbufScaleY]
);
}
// Uses the buffered motion information to determine a transform that smooths the
// given frame and applies it
static int filter_frame(AVFilterLink *link, AVFrame *input_frame)
{
AVFilterContext *avctx = link->dst;
AVFilterLink *outlink = avctx->outputs[0];
DeshakeOpenCLContext *deshake_ctx = avctx->priv;
AVFrame *cropped_frame = NULL, *transformed_frame = NULL;
int err;
cl_int cle;
float new_vals[RingbufCount];
float old_vals[RingbufCount];
// Luma (in the case of YUV) transform, or just the transform in the case of RGB
float transform_y[9];
// Chroma transform
float transform_uv[9];
// Luma crop transform (or RGB)
float transform_crop_y[9];
// Chroma crop transform
float transform_crop_uv[9];
float transform_debug_rgb[9];
size_t global_work[2];
int64_t duration;
cl_mem src, transformed, dst;
cl_mem transforms[3];
CropInfo crops[3];
cl_event transform_event, crop_upscale_event;
DebugMatches debug_matches;
cl_int num_model_matches;
const float center_w = (float)input_frame->width / 2;
const float center_h = (float)input_frame->height / 2;
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(deshake_ctx->sw_format);
const int chroma_width = AV_CEIL_RSHIFT(input_frame->width, desc->log2_chroma_w);
const int chroma_height = AV_CEIL_RSHIFT(input_frame->height, desc->log2_chroma_h);
const float center_w_chroma = (float)chroma_width / 2;
const float center_h_chroma = (float)chroma_height / 2;
const float luma_w_over_chroma_w = ((float)input_frame->width / (float)chroma_width);
const float luma_h_over_chroma_h = ((float)input_frame->height / (float)chroma_height);
if (deshake_ctx->debug_on) {
av_fifo_generic_read(
deshake_ctx->abs_motion.debug_matches,
&debug_matches,
sizeof(DebugMatches),
NULL
);
}
if (input_frame->pkt_duration) {
duration = input_frame->pkt_duration;
} else {
duration = av_rescale_q(1, av_inv_q(outlink->frame_rate), outlink->time_base);
}
deshake_ctx->duration = input_frame->pts + duration;
// Get the absolute transform data for this frame
for (int i = 0; i < RingbufCount; i++) {
av_fifo_generic_peek_at(
deshake_ctx->abs_motion.ringbuffers[i],
&old_vals[i],
deshake_ctx->abs_motion.curr_frame_offset * sizeof(float),
sizeof(float),
NULL
);
}
if (deshake_ctx->tripod_mode) {
// If tripod mode is turned on we simply undo all motion relative to the
// first frame
new_vals[RingbufX] = 0.0f;
new_vals[RingbufY] = 0.0f;
new_vals[RingbufRot] = 0.0f;
new_vals[RingbufScaleX] = 1.0f;
new_vals[RingbufScaleY] = 1.0f;
} else {
// Tripod mode is off and we need to smooth a moving camera
new_vals[RingbufX] = smooth(
deshake_ctx,
deshake_ctx->gauss_kernel,
deshake_ctx->smooth_window,
input_frame->width,
deshake_ctx->abs_motion.ringbuffers[RingbufX]
);
new_vals[RingbufY] = smooth(
deshake_ctx,
deshake_ctx->gauss_kernel,
deshake_ctx->smooth_window,
input_frame->height,
deshake_ctx->abs_motion.ringbuffers[RingbufY]
);
new_vals[RingbufRot] = smooth(
deshake_ctx,
deshake_ctx->gauss_kernel,
deshake_ctx->smooth_window,
M_PI / 4,
deshake_ctx->abs_motion.ringbuffers[RingbufRot]
);
new_vals[RingbufScaleX] = smooth(
deshake_ctx,
deshake_ctx->gauss_kernel,
deshake_ctx->smooth_window,
2.0f,
deshake_ctx->abs_motion.ringbuffers[RingbufScaleX]
);
new_vals[RingbufScaleY] = smooth(
deshake_ctx,
deshake_ctx->gauss_kernel,
deshake_ctx->smooth_window,
2.0f,
deshake_ctx->abs_motion.ringbuffers[RingbufScaleY]
);
}
transform_center_scale(
old_vals[RingbufX] - new_vals[RingbufX],
old_vals[RingbufY] - new_vals[RingbufY],
old_vals[RingbufRot] - new_vals[RingbufRot],
new_vals[RingbufScaleX] / old_vals[RingbufScaleX],
new_vals[RingbufScaleY] / old_vals[RingbufScaleY],
center_w,
center_h,
transform_y
);
transform_center_scale(
(old_vals[RingbufX] - new_vals[RingbufX]) / luma_w_over_chroma_w,
(old_vals[RingbufY] - new_vals[RingbufY]) / luma_h_over_chroma_h,
old_vals[RingbufRot] - new_vals[RingbufRot],
new_vals[RingbufScaleX] / old_vals[RingbufScaleX],
new_vals[RingbufScaleY] / old_vals[RingbufScaleY],
center_w_chroma,
center_h_chroma,
transform_uv
);
CL_BLOCKING_WRITE_BUFFER(deshake_ctx->command_queue, deshake_ctx->transform_y, 9 * sizeof(float), transform_y, NULL);
CL_BLOCKING_WRITE_BUFFER(deshake_ctx->command_queue, deshake_ctx->transform_uv, 9 * sizeof(float), transform_uv, NULL);
if (deshake_ctx->debug_on)
transform_debug(avctx, new_vals, old_vals, deshake_ctx->curr_frame);
cropped_frame = ff_get_video_buffer(outlink, outlink->w, outlink->h);
if (!cropped_frame) {
err = AVERROR(ENOMEM);
goto fail;
}
transformed_frame = ff_get_video_buffer(outlink, outlink->w, outlink->h);
if (!transformed_frame) {
err = AVERROR(ENOMEM);
goto fail;
}
transforms[0] = deshake_ctx->transform_y;
transforms[1] = transforms[2] = deshake_ctx->transform_uv;
for (int p = 0; p < FF_ARRAY_ELEMS(transformed_frame->data); p++) {
// Transform all of the planes appropriately
src = (cl_mem)input_frame->data[p];
transformed = (cl_mem)transformed_frame->data[p];
if (!transformed)
break;
err = ff_opencl_filter_work_size_from_image(avctx, global_work, input_frame, p, 0);
if (err < 0)
goto fail;
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_transform,
global_work,
NULL,
&transform_event,
{ sizeof(cl_mem), &src },
{ sizeof(cl_mem), &transformed },
{ sizeof(cl_mem), &transforms[p] },
);
}
if (deshake_ctx->debug_on && !deshake_ctx->is_yuv && debug_matches.num_matches > 0) {
CL_BLOCKING_WRITE_BUFFER(
deshake_ctx->command_queue,
deshake_ctx->debug_matches,
debug_matches.num_matches * sizeof(MotionVector),
debug_matches.matches,
NULL
);
CL_BLOCKING_WRITE_BUFFER(
deshake_ctx->command_queue,
deshake_ctx->debug_model_matches,
debug_matches.num_model_matches * sizeof(MotionVector),
debug_matches.model_matches,
NULL
);
num_model_matches = debug_matches.num_model_matches;
// Invert the transform
transform_center_scale(
new_vals[RingbufX] - old_vals[RingbufX],
new_vals[RingbufY] - old_vals[RingbufY],
new_vals[RingbufRot] - old_vals[RingbufRot],
old_vals[RingbufScaleX] / new_vals[RingbufScaleX],
old_vals[RingbufScaleY] / new_vals[RingbufScaleY],
center_w,
center_h,
transform_debug_rgb
);
CL_BLOCKING_WRITE_BUFFER(deshake_ctx->command_queue, deshake_ctx->transform_y, 9 * sizeof(float), transform_debug_rgb, NULL);
transformed = (cl_mem)transformed_frame->data[0];
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_draw_debug_info,
(size_t[]){ debug_matches.num_matches },
NULL,
NULL,
{ sizeof(cl_mem), &transformed },
{ sizeof(cl_mem), &deshake_ctx->debug_matches },
{ sizeof(cl_mem), &deshake_ctx->debug_model_matches },
{ sizeof(cl_int), &num_model_matches },
{ sizeof(cl_mem), &deshake_ctx->transform_y }
);
}
if (deshake_ctx->should_crop) {
// Generate transforms for cropping
transform_center_scale(
(old_vals[RingbufX] - new_vals[RingbufX]) / 5,
(old_vals[RingbufY] - new_vals[RingbufY]) / 5,
(old_vals[RingbufRot] - new_vals[RingbufRot]) / 5,
new_vals[RingbufScaleX] / old_vals[RingbufScaleX],
new_vals[RingbufScaleY] / old_vals[RingbufScaleY],
center_w,
center_h,
transform_crop_y
);
update_needed_crop(&deshake_ctx->crop_y, transform_crop_y, input_frame->width, input_frame->height);
transform_center_scale(
(old_vals[RingbufX] - new_vals[RingbufX]) / (5 * luma_w_over_chroma_w),
(old_vals[RingbufY] - new_vals[RingbufY]) / (5 * luma_h_over_chroma_h),
(old_vals[RingbufRot] - new_vals[RingbufRot]) / 5,
new_vals[RingbufScaleX] / old_vals[RingbufScaleX],
new_vals[RingbufScaleY] / old_vals[RingbufScaleY],
center_w_chroma,
center_h_chroma,
transform_crop_uv
);
update_needed_crop(&deshake_ctx->crop_uv, transform_crop_uv, chroma_width, chroma_height);
crops[0] = deshake_ctx->crop_y;
crops[1] = crops[2] = deshake_ctx->crop_uv;
for (int p = 0; p < FF_ARRAY_ELEMS(cropped_frame->data); p++) {
// Crop all of the planes appropriately
dst = (cl_mem)cropped_frame->data[p];
transformed = (cl_mem)transformed_frame->data[p];
if (!dst)
break;
err = ff_opencl_filter_work_size_from_image(avctx, global_work, input_frame, p, 0);
if (err < 0)
goto fail;
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_crop_upscale,
global_work,
NULL,
&crop_upscale_event,
{ sizeof(cl_mem), &transformed },
{ sizeof(cl_mem), &dst },
{ sizeof(cl_float2), &crops[p].top_left },
{ sizeof(cl_float2), &crops[p].bottom_right },
);
}
}
if (deshake_ctx->curr_frame < deshake_ctx->smooth_window / 2) {
// This means we are somewhere at the start of the video. We need to
// increment the current frame offset until it reaches the center of
// the ringbuffers (as the current frame will be located there for
// the rest of the video).
//
// The end of the video is taken care of by draining motion data
// one-by-one out of the buffer, causing the (at that point fixed)
// offset to move towards later frames' data.
++deshake_ctx->abs_motion.curr_frame_offset;
}
if (deshake_ctx->abs_motion.data_end_offset != -1) {
// Keep the end offset in sync with the frame it's supposed to be
// positioned at
--deshake_ctx->abs_motion.data_end_offset;
if (deshake_ctx->abs_motion.data_end_offset == deshake_ctx->abs_motion.curr_frame_offset - 1) {
// The end offset would be the start of the new video sequence; flip to
// start offset
deshake_ctx->abs_motion.data_end_offset = -1;
deshake_ctx->abs_motion.data_start_offset = deshake_ctx->abs_motion.curr_frame_offset;
}
} else if (deshake_ctx->abs_motion.data_start_offset != -1) {
// Keep the start offset in sync with the frame it's supposed to be
// positioned at
--deshake_ctx->abs_motion.data_start_offset;
}
if (deshake_ctx->debug_on) {
deshake_ctx->transform_time += ff_opencl_get_event_time(transform_event);
if (deshake_ctx->should_crop) {
deshake_ctx->crop_upscale_time += ff_opencl_get_event_time(crop_upscale_event);
}
}
++deshake_ctx->curr_frame;
if (deshake_ctx->debug_on)
av_freep(&debug_matches.matches);
if (deshake_ctx->should_crop) {
err = av_frame_copy_props(cropped_frame, input_frame);
if (err < 0)
goto fail;
av_frame_free(&transformed_frame);
av_frame_free(&input_frame);
return ff_filter_frame(outlink, cropped_frame);
} else {
err = av_frame_copy_props(transformed_frame, input_frame);
if (err < 0)
goto fail;
av_frame_free(&cropped_frame);
av_frame_free(&input_frame);
return ff_filter_frame(outlink, transformed_frame);
}
fail:
clFinish(deshake_ctx->command_queue);
if (deshake_ctx->debug_on)
if (debug_matches.matches)
av_freep(&debug_matches.matches);
av_frame_free(&input_frame);
av_frame_free(&transformed_frame);
av_frame_free(&cropped_frame);
return err;
}
// Add the given frame to the frame queue to eventually be processed.
//
// Also determines the motion from the previous frame and updates the stored
// motion information accordingly.
static int queue_frame(AVFilterLink *link, AVFrame *input_frame)
{
AVFilterContext *avctx = link->dst;
DeshakeOpenCLContext *deshake_ctx = avctx->priv;
int err;
int num_vectors;
int num_inliers = 0;
cl_int cle;
FrameDelta relative;
SimilarityMatrix model;
size_t global_work[2];
size_t harris_global_work[2];
size_t grid_32_global_work[2];
int grid_32_h, grid_32_w;
size_t local_work[2];
cl_mem src, temp;
float prev_vals[5];
float new_vals[5];
cl_event grayscale_event, harris_response_event, refine_features_event,
brief_event, match_descriptors_event, read_buf_event;
DebugMatches debug_matches;
num_vectors = 0;
local_work[0] = 8;
local_work[1] = 8;
err = ff_opencl_filter_work_size_from_image(avctx, global_work, input_frame, 0, 0);
if (err < 0)
goto fail;
err = ff_opencl_filter_work_size_from_image(avctx, harris_global_work, input_frame, 0, 8);
if (err < 0)
goto fail;
err = ff_opencl_filter_work_size_from_image(avctx, grid_32_global_work, input_frame, 0, 32);
if (err < 0)
goto fail;
// We want a single work-item for each 32x32 block of pixels in the input frame
grid_32_global_work[0] /= 32;
grid_32_global_work[1] /= 32;
grid_32_h = ROUNDED_UP_DIV(input_frame->height, 32);
grid_32_w = ROUNDED_UP_DIV(input_frame->width, 32);
if (deshake_ctx->is_yuv) {
deshake_ctx->grayscale = (cl_mem)input_frame->data[0];
} else {
src = (cl_mem)input_frame->data[0];
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_grayscale,
global_work,
NULL,
&grayscale_event,
{ sizeof(cl_mem), &src },
{ sizeof(cl_mem), &deshake_ctx->grayscale }
);
}
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_harris_response,
harris_global_work,
local_work,
&harris_response_event,
{ sizeof(cl_mem), &deshake_ctx->grayscale },
{ sizeof(cl_mem), &deshake_ctx->harris_buf }
);
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_refine_features,
grid_32_global_work,
NULL,
&refine_features_event,
{ sizeof(cl_mem), &deshake_ctx->grayscale },
{ sizeof(cl_mem), &deshake_ctx->harris_buf },
{ sizeof(cl_mem), &deshake_ctx->refined_features },
{ sizeof(cl_int), &deshake_ctx->refine_features }
);
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_brief_descriptors,
grid_32_global_work,
NULL,
&brief_event,
{ sizeof(cl_mem), &deshake_ctx->grayscale },
{ sizeof(cl_mem), &deshake_ctx->refined_features },
{ sizeof(cl_mem), &deshake_ctx->descriptors },
{ sizeof(cl_mem), &deshake_ctx->brief_pattern}
);
if (av_fifo_size(deshake_ctx->abs_motion.ringbuffers[RingbufX]) == 0) {
// This is the first frame we've been given to queue, meaning there is
// no previous frame to match descriptors to
goto no_motion_data;
}
CL_RUN_KERNEL_WITH_ARGS(
deshake_ctx->command_queue,
deshake_ctx->kernel_match_descriptors,
grid_32_global_work,
NULL,
&match_descriptors_event,
{ sizeof(cl_mem), &deshake_ctx->prev_refined_features },
{ sizeof(cl_mem), &deshake_ctx->refined_features },
{ sizeof(cl_mem), &deshake_ctx->descriptors },
{ sizeof(cl_mem), &deshake_ctx->prev_descriptors },
{ sizeof(cl_mem), &deshake_ctx->matches }
);
cle = clEnqueueReadBuffer(
deshake_ctx->command_queue,
deshake_ctx->matches,
CL_TRUE,
0,
grid_32_h * grid_32_w * sizeof(MotionVector),
deshake_ctx->matches_host,
0,
NULL,
&read_buf_event
);
CL_FAIL_ON_ERROR(AVERROR(EIO), "Failed to read matches to host: %d.\n", cle);
num_vectors = make_vectors_contig(deshake_ctx, grid_32_h, grid_32_w);
if (num_vectors < 10) {
// Not enough matches to get reliable motion data for this frame
//
// From this point on all data is relative to this frame rather than the
// original frame. We have to make sure that we don't mix values that were
// relative to the original frame with the new values relative to this
// frame when doing the gaussian smoothing. We keep track of where the old
// values end using this data_end_offset field in order to accomplish
// that goal.
//
// If no motion data is present for multiple frames in a short window of
// time, we leave the end where it was to avoid mixing 0s in with the
// old data (and just treat them all as part of the new values)
if (deshake_ctx->abs_motion.data_end_offset == -1) {
deshake_ctx->abs_motion.data_end_offset =
av_fifo_size(deshake_ctx->abs_motion.ringbuffers[RingbufX]) / sizeof(float) - 1;
}
goto no_motion_data;
}
if (!estimate_affine_2d(
deshake_ctx,
deshake_ctx->matches_contig_host,
&debug_matches,
num_vectors,
model.matrix,
10.0,
3000,
0.999999999999
)) {
goto no_motion_data;
}
for (int i = 0; i < num_vectors; i++) {
if (deshake_ctx->matches_contig_host[i].should_consider) {
deshake_ctx->inliers[num_inliers] = deshake_ctx->matches_contig_host[i];
num_inliers++;
}
}
if (!minimize_error(
deshake_ctx,
deshake_ctx->inliers,
&debug_matches,
num_inliers,
model.matrix,
400
)) {
goto no_motion_data;
}
relative = decompose_transform(model.matrix);
// Get the absolute transform data for the previous frame
for (int i = 0; i < RingbufCount; i++) {
av_fifo_generic_peek_at(
deshake_ctx->abs_motion.ringbuffers[i],
&prev_vals[i],
av_fifo_size(deshake_ctx->abs_motion.ringbuffers[i]) - sizeof(float),
sizeof(float),
NULL
);
}
new_vals[RingbufX] = prev_vals[RingbufX] + relative.translation.s[0];
new_vals[RingbufY] = prev_vals[RingbufY] + relative.translation.s[1];
new_vals[RingbufRot] = prev_vals[RingbufRot] + relative.rotation;
new_vals[RingbufScaleX] = prev_vals[RingbufScaleX] / relative.scale.s[0];
new_vals[RingbufScaleY] = prev_vals[RingbufScaleY] / relative.scale.s[1];
if (deshake_ctx->debug_on) {
if (!deshake_ctx->is_yuv) {
deshake_ctx->grayscale_time += ff_opencl_get_event_time(grayscale_event);
}
deshake_ctx->harris_response_time += ff_opencl_get_event_time(harris_response_event);
deshake_ctx->refine_features_time += ff_opencl_get_event_time(refine_features_event);
deshake_ctx->brief_descriptors_time += ff_opencl_get_event_time(brief_event);
deshake_ctx->match_descriptors_time += ff_opencl_get_event_time(match_descriptors_event);
deshake_ctx->read_buf_time += ff_opencl_get_event_time(read_buf_event);
}
goto end;
no_motion_data:
new_vals[RingbufX] = 0.0f;
new_vals[RingbufY] = 0.0f;
new_vals[RingbufRot] = 0.0f;
new_vals[RingbufScaleX] = 1.0f;
new_vals[RingbufScaleY] = 1.0f;
for (int i = 0; i < num_vectors; i++) {
deshake_ctx->matches_contig_host[i].should_consider = false;
}
debug_matches.num_model_matches = 0;
if (deshake_ctx->debug_on) {
av_log(avctx, AV_LOG_VERBOSE,
"\n[ALERT] No motion data found in queue_frame, motion reset to 0\n\n"
);
}
goto end;
end:
// Swap the descriptor buffers (we don't need the previous frame's descriptors
// again so we will use that space for the next frame's descriptors)
temp = deshake_ctx->prev_descriptors;
deshake_ctx->prev_descriptors = deshake_ctx->descriptors;
deshake_ctx->descriptors = temp;
// Same for the refined features
temp = deshake_ctx->prev_refined_features;
deshake_ctx->prev_refined_features = deshake_ctx->refined_features;
deshake_ctx->refined_features = temp;
if (deshake_ctx->debug_on) {
if (num_vectors == 0) {
debug_matches.matches = NULL;
} else {
debug_matches.matches = av_malloc_array(num_vectors, sizeof(MotionVector));
if (!debug_matches.matches) {
err = AVERROR(ENOMEM);
goto fail;
}
}
for (int i = 0; i < num_vectors; i++) {
debug_matches.matches[i] = deshake_ctx->matches_contig_host[i];
}
debug_matches.num_matches = num_vectors;
av_fifo_generic_write(
deshake_ctx->abs_motion.debug_matches,
&debug_matches,
sizeof(DebugMatches),
NULL
);
}
for (int i = 0; i < RingbufCount; i++) {
av_fifo_generic_write(
deshake_ctx->abs_motion.ringbuffers[i],
&new_vals[i],
sizeof(float),
NULL
);
}
return ff_framequeue_add(&deshake_ctx->fq, input_frame);
fail:
clFinish(deshake_ctx->command_queue);
av_frame_free(&input_frame);
return err;
}
static int activate(AVFilterContext *ctx)
{
AVFilterLink *inlink = ctx->inputs[0];
AVFilterLink *outlink = ctx->outputs[0];
DeshakeOpenCLContext *deshake_ctx = ctx->priv;
AVFrame *frame = NULL;
int ret, status;
int64_t pts;
FF_FILTER_FORWARD_STATUS_BACK(outlink, inlink);
if (!deshake_ctx->eof) {
ret = ff_inlink_consume_frame(inlink, &frame);
if (ret < 0)
return ret;
if (ret > 0) {
if (!frame->hw_frames_ctx)
return AVERROR(EINVAL);
if (!deshake_ctx->initialized) {
ret = deshake_opencl_init(ctx);
if (ret < 0)
return ret;
}
// If there is no more space in the ringbuffers, remove the oldest
// values to make room for the new ones
if (av_fifo_space(deshake_ctx->abs_motion.ringbuffers[RingbufX]) == 0) {
for (int i = 0; i < RingbufCount; i++) {
av_fifo_drain(deshake_ctx->abs_motion.ringbuffers[i], sizeof(float));
}
}
ret = queue_frame(inlink, frame);
if (ret < 0)
return ret;
if (ret >= 0) {
// See if we have enough buffered frames to process one
//
// "enough" is half the smooth window of queued frames into the future
if (ff_framequeue_queued_frames(&deshake_ctx->fq) >= deshake_ctx->smooth_window / 2) {
return filter_frame(inlink, ff_framequeue_take(&deshake_ctx->fq));
}
}
}
}
if (!deshake_ctx->eof && ff_inlink_acknowledge_status(inlink, &status, &pts)) {
if (status == AVERROR_EOF) {
deshake_ctx->eof = true;
}
}
if (deshake_ctx->eof) {
// Finish processing the rest of the frames in the queue.
while(ff_framequeue_queued_frames(&deshake_ctx->fq) != 0) {
for (int i = 0; i < RingbufCount; i++) {
av_fifo_drain(deshake_ctx->abs_motion.ringbuffers[i], sizeof(float));
}
ret = filter_frame(inlink, ff_framequeue_take(&deshake_ctx->fq));
if (ret < 0) {
return ret;
}
}
if (deshake_ctx->debug_on) {
av_log(ctx, AV_LOG_VERBOSE,
"Average kernel execution times:\n"
"\t grayscale: %0.3f ms\n"
"\t harris_response: %0.3f ms\n"
"\t refine_features: %0.3f ms\n"
"\tbrief_descriptors: %0.3f ms\n"
"\tmatch_descriptors: %0.3f ms\n"
"\t transform: %0.3f ms\n"
"\t crop_upscale: %0.3f ms\n"
"Average buffer read times:\n"
"\t features buf: %0.3f ms\n",
averaged_event_time_ms(deshake_ctx->grayscale_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->harris_response_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->refine_features_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->brief_descriptors_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->match_descriptors_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->transform_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->crop_upscale_time, deshake_ctx->curr_frame),
averaged_event_time_ms(deshake_ctx->read_buf_time, deshake_ctx->curr_frame)
);
}
ff_outlink_set_status(outlink, AVERROR_EOF, deshake_ctx->duration);
return 0;
}
if (!deshake_ctx->eof) {
FF_FILTER_FORWARD_WANTED(outlink, inlink);
}
return FFERROR_NOT_READY;
}
static const AVFilterPad deshake_opencl_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = &ff_opencl_filter_config_input,
},
{ NULL }
};
static const AVFilterPad deshake_opencl_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = &ff_opencl_filter_config_output,
},
{ NULL }
};
#define OFFSET(x) offsetof(DeshakeOpenCLContext, x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM|AV_OPT_FLAG_VIDEO_PARAM
static const AVOption deshake_opencl_options[] = {
{
"tripod", "simulates a tripod by preventing any camera movement whatsoever "
"from the original frame",
OFFSET(tripod_mode), AV_OPT_TYPE_BOOL, {.i64 = 0}, 0, 1, FLAGS
},
{
"debug", "turn on additional debugging information",
OFFSET(debug_on), AV_OPT_TYPE_BOOL, {.i64 = 0}, 0, 1, FLAGS
},
{
"adaptive_crop", "attempt to subtly crop borders to reduce mirrored content",
OFFSET(should_crop), AV_OPT_TYPE_BOOL, {.i64 = 1}, 0, 1, FLAGS
},
{
"refine_features", "refine feature point locations at a sub-pixel level",
OFFSET(refine_features), AV_OPT_TYPE_BOOL, {.i64 = 1}, 0, 1, FLAGS
},
{
"smooth_strength", "smoothing strength (0 attempts to adaptively determine optimal strength)",
OFFSET(smooth_percent), AV_OPT_TYPE_FLOAT, {.dbl = 0.0f}, 0.0f, 1.0f, FLAGS
},
{
"smooth_window_multiplier", "multiplier for number of frames to buffer for motion data",
OFFSET(smooth_window_multiplier), AV_OPT_TYPE_FLOAT, {.dbl = 2.0}, 0.1, 10.0, FLAGS
},
{ NULL }
};
AVFILTER_DEFINE_CLASS(deshake_opencl);
AVFilter ff_vf_deshake_opencl = {
.name = "deshake_opencl",
.description = NULL_IF_CONFIG_SMALL("Feature-point based video stabilization filter"),
.priv_size = sizeof(DeshakeOpenCLContext),
.priv_class = &deshake_opencl_class,
.init = &ff_opencl_filter_init,
.uninit = &deshake_opencl_uninit,
.query_formats = &ff_opencl_filter_query_formats,
.activate = activate,
.inputs = deshake_opencl_inputs,
.outputs = deshake_opencl_outputs,
.flags_internal = FF_FILTER_FLAG_HWFRAME_AWARE
};
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